diff --git a/.DS_Store b/.DS_Store deleted file mode 100644 index b088689..0000000 Binary files a/.DS_Store and /dev/null differ diff --git a/.Rbuildignore b/.Rbuildignore new file mode 100644 index 0000000..b425821 --- /dev/null +++ b/.Rbuildignore @@ -0,0 +1,28 @@ +^renv$ +^renv\.lock$ +^.*\.Rproj$ +^\.Rproj\.user$ +^\.DS_Store$ +^\.git$ +^\.github$ +^\.claude$ +^mockdata-tools$ +^CODE_OF_CONDUCT\.md$ +^CONTRIBUTING\.md$ +^NEWS\.md$ +^\.tmp$ +^check_output.*\.txt$ +^R_CMD_CHECK_FIXES\.md$ +^CRITICAL_ISSUE_create_mock_data\.md$ +^PKGDOWN_FIX_SUMMARY\.md$ +^PKGDOWN_SETUP\.md$ +^SURVIVAL_SECTION_IMPLEMENTED\.md$ +^PR_REVIEW_STATUS\.md$ +^PR_REVIEW_RESPONSE\.md$ +^PR_DESCRIPTION_ADDENDUM\.md$ +^REVIEWER_QUICKSTART\.md$ +^LOCAL_TESTING_GUIDE\.md$ +^docs$ +^_pkgdown\.yml$ +^development$ +^\.claude$ diff --git a/.Rprofile b/.Rprofile new file mode 100644 index 0000000..81b960f --- /dev/null +++ b/.Rprofile @@ -0,0 +1 @@ +source("renv/activate.R") diff --git a/.claude/AI.md b/.claude/AI.md new file mode 100644 index 0000000..cc6aa5b --- /dev/null +++ b/.claude/AI.md @@ -0,0 +1,250 @@ +# MockData - AI Development Guidelines + +## R package development with pkgdown + Quarto + renv + +### Context: Cutting-edge stack (2024-2025) + +This project uses a relatively new combination: +- **pkgdown** for R package documentation sites +- **Quarto .qmd vignettes** (replacing traditional .Rmd) +- **renv** for reproducible dependency management +- **GitHub Actions** for automated deployment + +This stack is newer than most online resources, so documented patterns are limited. + +### Critical: renv snapshot configuration + +**Problem**: Default `renv::snapshot()` only captures packages used in `R/` code, missing: +- DESCRIPTION Suggests field (pkgdown, quarto, devtools, roxygen2) +- Packages used only in vignettes (dplyr, stringr, lubridate) + +**Solution**: Configure renv to capture ALL dependencies + +```r +# Set snapshot type to "all" (persists in project settings) +renv::settings$snapshot.type("all") + +# Snapshot with all DESCRIPTION dependencies +renv::snapshot() +``` + +**Result**: renv.lock now contains ~124 packages instead of just renv itself. + +### Simplified GitHub Actions workflow + +With complete renv.lock, the workflow is straightforward: + +```yaml +- name: Install renv + run: Rscript -e "install.packages('renv')" + +- name: Restore R packages with renv + run: Rscript -e "renv::restore(prompt = FALSE)" + +- name: Build and install MockData package + run: | + Rscript -e "roxygen2::roxygenize()" + R CMD INSTALL . + +- name: Build pkgdown site + run: Rscript -e 'pkgdown::build_site(new_process = FALSE)' +``` + +**No manual package installations needed.** +**No R_LIBS_USER path manipulation needed.** + +### When to update renv.lock + +```r +# After adding packages to DESCRIPTION +renv::snapshot() + +# After removing packages from DESCRIPTION +renv::snapshot() + +# To check what changed +renv::status() +``` + +### Known issues with pkgdown + Quarto + +From official pkgdown documentation (as of 2025): +- Callouts not currently supported in Quarto vignettes +- Only HTML vignettes work (requires `minimal: true` in Quarto format) +- External files in vignettes/ may not be copied during rendering +- Mermaid diagrams require custom CSS instead of quarto themes + +### Debugging tips + +If vignettes fail to render: +```r +# Enable Quarto debugging +options(quarto.log.debug = TRUE) +pkgdown::build_site() +``` + +Check that all vignette dependencies are in DESCRIPTION Suggests and renv.lock. + +### Debugging GitHub Actions failures: Lessons learned (2025-01-07) + +**Context**: 10+ hour debugging session to fix "System command 'quarto' failed" error in GitHub Actions. + +#### Start with minimal examples and successful patterns + +**DON'T**: Try to debug complex failures in GitHub Actions directly +**DO**: Build from working examples (chmsflow, popcorn-data) and test locally first + +**Minimal working workflow pattern**: + +```yaml +name: pkgdown + +on: + push: + branches: [main] # Don't include feature branches - causes duplicate runs with PRs + pull_request: + branches: [main] + workflow_dispatch: + +permissions: + contents: write + +jobs: + pkgdown: + runs-on: ubuntu-latest + env: + GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} + + steps: + - uses: actions/checkout@v4 + - uses: r-lib/actions/setup-pandoc@v2 + - uses: r-lib/actions/setup-r@v2 + with: + use-public-rspm: true + + - name: Install Quarto + uses: quarto-dev/quarto-actions/setup@v2 + + - name: Install roxygen2 + run: Rscript -e "install.packages('roxygen2')" + + - name: Generate documentation + run: Rscript -e "roxygen2::roxygenize()" + + - uses: r-lib/actions/setup-r-dependencies@v2 + with: + extra-packages: any::pkgdown, local::. + needs: website + + # Debug step - render single vignette to isolate failures + - name: Test render single vignette + run: quarto render vignettes/getting-started.qmd --to html + continue-on-error: true + + - name: Build pkgdown site + run: | + options(rlib_message_verbosity = "verbose") + pkgdown::build_site_github_pages(new_process = FALSE, install = FALSE, quiet = FALSE) + shell: Rscript {0} + + - name: Deploy to GitHub Pages + if: github.event_name != 'pull_request' + uses: JamesIves/github-pages-deploy-action@v4 + with: + folder: docs + branch: gh-pages + target-folder: . + clean: false +``` + +#### Critical debugging principles + +1. **Make errors visible** + - Set `quiet = FALSE` in `build_site_github_pages()` + - Add `continue-on-error: true` test steps to see actual failures + - Use `options(rlib_message_verbosity = "verbose")` + +2. **Test incrementally** + - Render one vignette at a time to isolate failures + - Test locally first: `quarto render vignettes/example.qmd --to html` + - Compare with working repos (chmsflow, popcorn-data) + +3. **Environment differences matter** + - **Locales**: `en_CA` works on macOS but NOT on Ubuntu GitHub Actions + - **Solution**: Use `en_US.UTF-8` for cross-platform compatibility + - **Example**: `lubridate::parse_date_time(..., locale = "en_US.UTF-8")` + +4. **Avoid duplicate workflow runs** + - **DON'T**: `push: branches: [main, feature-branch]` + - **DO**: `push: branches: [main]` + - **Why**: PRs already trigger on `pull_request` event + +5. **Use r-lib actions for dependency management** + - Prefer `r-lib/actions/setup-r-dependencies@v2` over manual renv + - Let `setup-r-dependencies` handle dependency installation + - **Always generate documentation first** with `roxygen2::roxygenize()` + +#### Common pitfalls + +1. **Generic error messages**: "System command 'quarto' failed" tells you nothing + - **Fix**: Add `quiet = FALSE` to see actual errors + +2. **Locale issues**: Hardcoded locales fail in CI/CD + - **Fix**: Use `en_US.UTF-8` instead of `en_CA` + +3. **Missing documentation**: pkgdown can't find topics if man/ files don't exist + - **Fix**: Run `roxygen2::roxygenize()` before building site + +4. **Vignette dependencies**: Packages used only in vignettes must be in DESCRIPTION + - **Fix**: Add to Suggests field, then `renv::snapshot()` + +#### Quick diagnostic checklist + +When GitHub Actions fails: + +- [ ] Test locally: `pkgdown::build_site()` +- [ ] Render vignettes individually: `quarto render vignettes/example.qmd --to html` +- [ ] Check for hardcoded locales (use `en_US.UTF-8`) +- [ ] Verify all vignette packages in DESCRIPTION Suggests +- [ ] Add `quiet = FALSE` to see actual error messages +- [ ] Compare workflow with working repos (chmsflow) +- [ ] Check for duplicate triggers (push + pull_request) + +#### GitHub Pages deployment tips + +**Start early**: Set up GitHub Pages deployment from the beginning, not as an afterthought. + +**Multi-branch deployment pattern**: + +```yaml +- name: Determine deployment path + id: deploy-path + run: | + if [[ "${{ github.ref }}" == "refs/heads/main" ]]; then + echo "target_path=." >> $GITHUB_OUTPUT + elif [[ "${{ github.ref }}" == "refs/heads/dev" ]]; then + echo "target_path=dev" >> $GITHUB_OUTPUT + else + echo "target_path=preview/${{ github.ref_name }}" >> $GITHUB_OUTPUT + fi + +- name: Deploy to GitHub Pages + uses: JamesIves/github-pages-deploy-action@v4 + with: + folder: docs + branch: gh-pages + target-folder: ${{ steps.deploy-path.outputs.target_path }} + clean: false +``` + +**Result**: +- `main` β†’ https://yoursite.github.io/repo/ +- `dev` β†’ https://yoursite.github.io/repo/dev/ +- Other branches β†’ https://yoursite.github.io/repo/preview/branch-name/ + +### References + +- [pkgdown Quarto vignettes documentation](https://pkgdown.r-lib.org/articles/quarto.html) +- [renv CI/CD guide](https://rstudio.github.io/renv/articles/ci.html) +- [Quarto with renv discussion](https://github.com/quarto-dev/quarto-cli/discussions/9150) +- [r-lib/actions GitHub repository](https://github.com/r-lib/actions) diff --git a/.github/workflows/deploy-manual.yaml b/.github/workflows/deploy-manual.yaml new file mode 100644 index 0000000..8c8ca50 --- /dev/null +++ b/.github/workflows/deploy-manual.yaml @@ -0,0 +1,88 @@ +on: + workflow_dispatch: + inputs: + branch: + description: 'Branch to deploy' + required: true + default: 'v030-refactor' + type: choice + options: + - main + - v030-refactor + target: + description: 'Deployment target (root, dev, or custom path)' + required: true + default: 'dev' + type: string + +name: Manual Deploy + +permissions: + contents: write + +jobs: + deploy: + runs-on: ubuntu-latest + env: + GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} + + steps: + - uses: actions/checkout@v4 + with: + ref: ${{ inputs.branch }} + + - uses: r-lib/actions/setup-pandoc@v2 + + - uses: r-lib/actions/setup-r@v2 + with: + use-public-rspm: true + + - name: Install Quarto + uses: quarto-dev/quarto-actions/setup@v2 + + - name: Install roxygen2 + run: Rscript -e "install.packages('roxygen2')" + + - name: Generate documentation + run: Rscript -e "roxygen2::roxygenize()" + + - uses: r-lib/actions/setup-r-dependencies@v2 + with: + extra-packages: any::pkgdown, local::. + needs: website + + - name: Build pkgdown site + run: | + options(rlib_message_verbosity = "verbose") + pkgdown::build_site_github_pages(new_process = FALSE, install = FALSE, quiet = FALSE) + shell: Rscript {0} + + - name: Deploy to GitHub Pages + uses: JamesIves/github-pages-deploy-action@v4 + with: + folder: docs + branch: gh-pages + target-folder: ${{ inputs.target }} + clean: false + + - name: Deployment Summary + run: | + if [ "${{ inputs.target }}" = "." ]; then + TARGET_PATH="" + TARGET_DESC="root" + else + TARGET_PATH="${{ inputs.target }}/" + TARGET_DESC="${{ inputs.target }}" + fi + + echo "## πŸš€ Deployment Complete" >> $GITHUB_STEP_SUMMARY + echo "" >> $GITHUB_STEP_SUMMARY + echo "| Setting | Value |" >> $GITHUB_STEP_SUMMARY + echo "|---------|-------|" >> $GITHUB_STEP_SUMMARY + echo "| **Branch** | \`${{ inputs.branch }}\` |" >> $GITHUB_STEP_SUMMARY + echo "| **Target** | \`${TARGET_DESC}\` |" >> $GITHUB_STEP_SUMMARY + echo "| **URL** | https://big-life-lab.github.io/MockData/${TARGET_PATH} |" >> $GITHUB_STEP_SUMMARY + echo "" >> $GITHUB_STEP_SUMMARY + echo "### ℹ️ Target options" >> $GITHUB_STEP_SUMMARY + echo "- Use \`.\` to deploy to the site root" >> $GITHUB_STEP_SUMMARY + echo "- Use \`dev\` or other path for subfolder deployment" >> $GITHUB_STEP_SUMMARY diff --git a/.github/workflows/pkgdown.yaml b/.github/workflows/pkgdown.yaml new file mode 100644 index 0000000..8d51ed8 --- /dev/null +++ b/.github/workflows/pkgdown.yaml @@ -0,0 +1,75 @@ +on: + push: + branches: [main] + pull_request: + branches: [main] + release: + types: [published] + workflow_dispatch: + +name: pkgdown + +permissions: + contents: write + +jobs: + pkgdown: + runs-on: ubuntu-latest + env: + GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} + + steps: + - uses: actions/checkout@v4 + + - uses: r-lib/actions/setup-pandoc@v2 + + - uses: r-lib/actions/setup-r@v2 + with: + use-public-rspm: true + + - name: Install Quarto + uses: quarto-dev/quarto-actions/setup@v2 + + - name: Install roxygen2 + run: Rscript -e "install.packages('roxygen2')" + + - name: Generate documentation + run: Rscript -e "roxygen2::roxygenize()" + + - uses: r-lib/actions/setup-r-dependencies@v2 + with: + extra-packages: any::pkgdown, local::. + needs: website + + - name: Test render single vignette + run: quarto render vignettes/getting-started.qmd --to html + continue-on-error: true + + - name: Build pkgdown site + run: | + options(rlib_message_verbosity = "verbose") + pkgdown::build_site_github_pages(new_process = FALSE, install = FALSE, quiet = FALSE) + shell: Rscript {0} + + - name: Determine deployment path + id: deploy-path + run: | + if [[ "${{ github.ref }}" == "refs/heads/main" ]]; then + echo "target_path=." >> $GITHUB_OUTPUT + echo "Deploying to root (main branch)" + elif [[ "${{ github.ref }}" == "refs/heads/create-date-var" ]]; then + echo "target_path=dev" >> $GITHUB_OUTPUT + echo "Deploying to /dev (create-date-var branch)" + else + echo "target_path=preview/${{ github.ref_name }}" >> $GITHUB_OUTPUT + echo "Deploying to /preview/${{ github.ref_name }}" + fi + + - name: Deploy to GitHub Pages + if: github.event_name != 'pull_request' + uses: JamesIves/github-pages-deploy-action@v4 + with: + folder: docs + branch: gh-pages + target-folder: ${{ steps.deploy-path.outputs.target_path }} + clean: false diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..3c31a9d --- /dev/null +++ b/.gitignore @@ -0,0 +1,22 @@ +# R build artifacts +*.tar.gz +*.Rcheck/ +.Rproj.user/ +.Rhistory +.RData +.Ruserdata +.Renviron + +# Temporary files and development artifacts +.tmp/ + +# macOS +.DS_Store + +# Generated documentation +man/*.Rd +docs/ + +# Quarto/HTML output +Generate_mock_data.html +Generate_mock_data_files/ diff --git a/CODE_OF_CONDUCT.md b/CODE_OF_CONDUCT.md new file mode 100644 index 0000000..e71b246 --- /dev/null +++ b/CODE_OF_CONDUCT.md @@ -0,0 +1,27 @@ +# Code of Conduct + +## Be Nice + +We're all here to build better tools for health research. Let's make this a welcoming place for everyone. + +## Our Standards + +**Do:** +* Be kind and respectful +* Give constructive feedback +* Focus on what's best for the project and community +* Help others learn and grow +* Credit people for their contributions + +**Don't:** +* Be mean, insulting, or harassing +* Make it personal when discussing technical issues +* Share others' private information without permission + +## That's It + +If you see behaviour that makes this community less welcoming, please reach out to the project maintainers. We'll handle issues with care and discretion. + +--- + +**Attribution**: Inspired by the [Contributor Covenant](https://www.contributor-covenant.org/) and [Mozilla's code of conduct](https://github.com/mozilla/diversity). diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md new file mode 100644 index 0000000..32805d0 --- /dev/null +++ b/CONTRIBUTING.md @@ -0,0 +1,250 @@ +# Contributing to MockData + +Thank you for considering contributing to MockData! This package is part of the recodeflow ecosystem and benefits from community input. + +## Getting Started + +### Prerequisites + +- R (>= 4.2.0) +- RStudio or another R IDE (recommended) +- Git +- Package development tools: `install.packages(c("devtools", "testthat", "roxygen2"))` + +### Setting Up Development Environment + +1. Fork and clone the repository: +```bash +git clone https://github.com/your-username/MockData.git +cd MockData +``` + +2. Open in RStudio: + - Double-click `MockData.Rproj` + - Or: File β†’ Open Project β†’ Select MockData.Rproj + +3. Install development dependencies: +```r +devtools::install_dev_deps() +``` + +4. Load the package: +```r +devtools::load_all() +``` + +## Development Workflow + +### Making Changes + +1. **Create a new branch** for your work: +```bash +git checkout -b feature/your-feature-name +``` + +2. **Make your changes** following the coding standards below + +3. **Document your changes**: + - Update function documentation (roxygen2 comments) + - Add examples where appropriate + - Update NEWS.md with your changes + +4. **Write tests** for new functionality: + - Add tests to `tests/testthat/test-mockdata.R` + - Ensure all tests pass: `devtools::test()` + +5. **Run checks**: +```r +devtools::check() +``` + +6. **Commit your changes** following commit message guidelines + +7. **Push and create a pull request** + +### Coding Standards + +#### R Code Style + +- Use 2 spaces for indentation (not tabs) +- Line length: aim for < 80 characters, max 100 +- Use `<-` for assignment, not `=` +- Function names: `snake_case` +- Variable names: `snake_case` +- Constants: `SCREAMING_SNAKE_CASE` + +#### Documentation + +- All exported functions must have roxygen2 documentation +- Include `@param`, `@return`, `@examples`, `@export` tags +- Examples should be runnable (use `\dontrun{}` sparingly) +- Use Canadian spelling (behaviour, colour, centre) + +#### Commit Messages + +Follow Canadian Government Digital Standards: +- **Format**: `type: brief description` +- **Types**: + - `feat`: New feature + - `fix`: Bug fix + - `docs`: Documentation changes + - `test`: Adding or updating tests + - `refactor`: Code refactoring + - `style`: Code style changes (formatting, etc.) + - `chore`: Maintenance tasks + +**Examples**: +``` +feat: add support for date variable generation +fix: handle missing NA codes in categorical variables +docs: update README with CHMS example +test: add tests for parse_range_notation edge cases +``` + +**Do not credit AI tools in commit messages** (as per project guidelines). + +### Testing + +#### Running Tests + +```r +# Run all tests +devtools::test() + +# Run specific test file +testthat::test_file("tests/testthat/test-mockdata.R") + +# Run with coverage +covr::package_coverage() +``` + +#### Writing Tests + +- Place tests in `tests/testthat/test-mockdata.R` +- Use descriptive test names: `test_that("parse_range_notation handles closed intervals", { ... })` +- Test edge cases and error conditions +- Aim for high code coverage + +#### Test Data + +- Use existing metadata in `inst/extdata/` for tests +- If adding new test data, document its purpose +- Keep test data small and focused + +### Building Documentation + +#### Prerequisites for documentation builds + +1. **Install Quarto**: Download from https://quarto.org/docs/get-started/ or use Homebrew: +```bash +brew install quarto +``` + +2. **Ensure pkgdown and roxygen2 are available**: +```r +# These are in Suggests, install if needed +renv::install(c("pkgdown", "roxygen2")) +``` + +3. **Configure PATH for IDE users** (Positron/RStudio): + +If you encounter "System command 'quarto' failed" errors, add Quarto to your PATH in `~/.Renviron`: +``` +PATH="/usr/local/bin:/opt/homebrew/bin:/usr/bin:/bin:/usr/sbin:/sbin:${PATH}" +``` + +Then restart your R session. + +#### Building the pkgdown site + +```r +# 1. Regenerate .Rd files from roxygen comments (after editing R documentation) +roxygen2::roxygenize() + +# 2. Build the pkgdown site +pkgdown::build_site() + +# 3. Preview locally +browseURL("docs/index.html") +``` + +**Important**: Always run `roxygen2::roxygenize()` before `pkgdown::build_site()` if you've modified roxygen documentation in R files. + +#### Rendering individual vignettes + +```bash +# From project root +quarto render vignettes/getting-started.qmd --to html +``` + +### Validation Tools + +Before submitting, run the validation tools: + +```bash +# Validate metadata quality +Rscript mockdata-tools/validate-metadata.R + +# Test coverage across cycles +Rscript mockdata-tools/test-all-cycles.R +``` + +## Areas for Contribution + +### High Priority + +- **Date variable support**: Implement `create_date_var()` for linkage testing +- **Data quality injection**: Add functions to inject realistic data quality issues +- **Performance optimization**: Improve generation speed for large datasets +- **Additional vignettes**: Real-world use cases and workflows + +### Medium Priority + +- **More survey examples**: Add metadata from other recodeflow projects +- **Validation improvements**: Enhance metadata quality checks +- **Documentation**: Expand README, add pkgdown site + +### Low Priority + +- **Distribution options**: Add more probability distributions for continuous variables +- **Correlation structure**: Generate correlated variables +- **Time series**: Support for longitudinal data + +## Recodeflow Schema Compliance + +When adding or modifying parsers: + +1. **Check the schema**: See `inst/metadata/schemas/` for authoritative definitions +2. **Test with real metadata**: Use CCHS, CHMS, or DemPoRT examples +3. **Document notation support**: Update README if adding new notation patterns +4. **Coordinate with cchsflow/chmsflow**: Major schema changes should be discussed + +## Questions or Issues? + +- **Package questions**: Contact Juan Li (juan.li@oahpp.ca) or Doug Manuel (dmanuel@ohri.ca) +- **Bug reports**: Open a GitHub issue +- **Feature requests**: Open a GitHub issue with the "enhancement" label +- **Security issues**: Email maintainers directly (do not open public issue) + +## Code of Conduct + +### Our Standards + +- Be respectful and inclusive +- Focus on constructive feedback +- Prioritize technical accuracy over personal preferences +- Give credit where credit is due + +### Unacceptable Behaviour + +- Harassment or discriminatory language +- Personal attacks or trolling +- Sharing private information without permission + +## License + +By contributing to MockData, you agree that your contributions will be licensed under the MIT License. + +--- + +**Thank you for contributing to MockData and the recodeflow ecosystem!** diff --git a/DESCRIPTION b/DESCRIPTION new file mode 100644 index 0000000..24c6f98 --- /dev/null +++ b/DESCRIPTION @@ -0,0 +1,36 @@ +Package: MockData +Title: Generate Mock Data from Recodeflow Metadata +Version: 0.3.0 +Authors@R: c( + person("Juan", "Li", role = c("aut", "cre"), email = "juli@ohri.ca"), + person("recodeflow contributors", role = "ctb") + ) +Author: Juan Li [aut, cre], + recodeflow contributors [ctb] +Maintainer: Juan Li +Description: Generates mock testing data from recodeflow metadata (variables.csv + and variable-details.csv). Supports categorical and continuous variables + with metadata-driven specifications. Designed for testing harmonization workflows + across CHMS, CCHS, and other recodeflow projects. Uses recodeflow-standard + notation for parsing variable specifications and range notation. +License: MIT + file LICENSE +URL: https://big-life-lab.github.io/MockData/, https://github.com/Big-Life-Lab/MockData +BugReports: https://github.com/Big-Life-Lab/MockData/issues +Encoding: UTF-8 +Roxygen: list(markdown = TRUE) +RoxygenNote: 7.3.3 +VignetteBuilder: quarto +Depends: + R (>= 4.2.0) +Imports: + stats +Suggests: + testthat (>= 3.0.0), + readr, + dplyr, + stringr, + lubridate, + quarto, + devtools, + pkgdown, + roxygen2 diff --git a/DOCUMENTATION_FINAL_REVIEW.md b/DOCUMENTATION_FINAL_REVIEW.md new file mode 100644 index 0000000..5cca31d --- /dev/null +++ b/DOCUMENTATION_FINAL_REVIEW.md @@ -0,0 +1,168 @@ +# Documentation Final Review - Session Notes + +**Date:** 2025-11-05 +**Status:** Ready for pkgdown rebuild and final review + +## Completed in this session + +### 1. Vignette standardization (Phases 1-4) + +βœ… **Phase 1:** Added "About this vignette" callouts to all 7 vignettes that were missing them +- getting-started.qmd +- tutorial-config-files.qmd +- tutorial-dates.qmd +- dates.qmd +- advanced-topics.qmd +- reference-config.qmd +- missing-data-tutorial-outline.qmd + +βœ… **Phase 2:** Standardized "Next steps" section formatting +- dates.qmd: Changed "## See also" β†’ "## Next steps" +- cchs-example.qmd: Changed bold text β†’ level 2 heading +- chms-example.qmd: Changed bold text β†’ level 2 heading + +βœ… **Phase 3:** Fixed terminology consistency +- demport-example.qmd: Fixed CCHS acronym pattern to "Canadian Community Health Survey (CCHS)" + +βœ… **Phase 4:** Added "What you learned" section +- tutorial-dates.qmd: Added comprehensive 6-point summary + +βœ… **Phase 5:** Blank lines before lists (already complete - no changes needed) + +### 2. README enhancements + +βœ… Added "The recodeflow universe" section explaining: +- Metadata-driven philosophy +- Design principles +- Related packages (cchsflow, chmsflow, recodeflow) + +βœ… Added "Data sources and acknowledgements" section: +- Statistics Canada credit +- Open License reference +- Clarification that package generates mock data only + +### 3. Author attribution updates + +βœ… **All vignettes:** Updated author field to "Juan Li and the recodeflow contributors" + +βœ… **DESCRIPTION file:** Modified Authors@R to show: +- Juan Li (aut, cre) +- recodeflow contributors (ctb) +- Removed Doug Manuel per request + +### 4. Function documentation improvements + +βœ… Expanded 5 short function titles from 3-8 words to 13-15 words: + +| Function | Old title (words) | New title (words) | +|----------|-------------------|-------------------| +| `read_mock_data_config()` | 4 | 14 | +| `validate_mock_data_config()` | 3 | 13 | +| `read_mock_data_config_details()` | 5 | 14 | +| `validate_mock_data_config_details()` | 4 | 14 | +| `import_from_recodeflow()` | 8 | 15 | + +**Files modified:** +- R/read_mock_data_config.R (2 @title tags) +- R/read_mock_data_config_details.R (2 @title tags) +- R/import_from_recodeflow.R (1 @title tag) + +## Next steps on the other computer + +### 1. Rebuild pkgdown site + +```r +# In R console +pkgdown::build_site() +``` + +**Check these items:** +- Footer shows "Developed by Juan Li and recodeflow contributors" +- Reference page shows expanded function descriptions (13-15 words each) +- All vignettes have "About this vignette" callouts +- README shows recodeflow universe and Statistics Canada sections + +### 2. Final review checklist + +- [ ] All vignettes render correctly +- [ ] Footer attribution correct on all pages +- [ ] Reference page function descriptions are clear +- [ ] README sections display properly +- [ ] All links work correctly +- [ ] No regressions in code examples + +### 3. Files changed in this session + +**Documentation:** +- README.md +- vignettes/getting-started.qmd +- vignettes/tutorial-config-files.qmd +- vignettes/tutorial-dates.qmd +- vignettes/dates.qmd +- vignettes/advanced-topics.qmd +- vignettes/reference-config.qmd +- vignettes/missing-data-tutorial-outline.qmd +- vignettes/cchs-example.qmd +- vignettes/chms-example.qmd +- vignettes/demport-example.qmd (already had callout, just fixed CCHS acronym) + +**Package metadata:** +- DESCRIPTION (Authors@R field) + +**R documentation:** +- R/read_mock_data_config.R +- R/read_mock_data_config_details.R +- R/import_from_recodeflow.R + +### 4. Verification commands + +```bash +# Verify all vignettes render +for file in vignettes/*.qmd; do + echo "=== Rendering $file ===" + quarto render "$file" --to html +done + +# Check for any broken links +# (After pkgdown build) +``` + +## Notes for review + +### Style guide compliance +- All level 2+ headings use sentence case βœ… +- Canadian spelling throughout βœ… +- Consistent "About this vignette" callout structure βœ… +- Consistent "Next steps" section formatting βœ… + +### No regressions introduced +- No cat(), print(), or echo statements added βœ… +- All code examples remain executable βœ… +- No changes to core generation functions βœ… +- Only additive changes (callouts, sections) and formatting (headings) βœ… + +### Outstanding items +None - documentation is ready for final review and deployment. + +## Commits made in this session + +### Commit 1: `9186757` - Standardize documentation and finalize vignette improvements +**34 files changed, 2624 insertions(+), 178 deletions(-)** + +Main changes: +- All vignette updates (11 files) +- README.md enhancements (recodeflow universe, StatsCan acknowledgements) +- DESCRIPTION author updates (Juan Li + recodeflow contributors) +- Function documentation expansions (5 @title tags in 3 R files) +- DOCUMENTATION_FINAL_REVIEW.md (this file) + +### Commit 2: `f13c91c` - Improve pkgdown reference page section descriptions +**2 files changed, 20 insertions(+), 11 deletions(-)** + +Main changes: +- _pkgdown.yml: Expanded all section descriptions to full sentences +- .Rbuildignore: Cleaned up to exclude PR review notes and session docs + +**Both commits pushed to `origin/create-date-var`** + +All documentation work is now complete and ready for pkgdown rebuild on the other computer. diff --git a/Generate_mock_data.qmd b/Generate_mock_data.qmd deleted file mode 100644 index 58db3aa..0000000 --- a/Generate_mock_data.qmd +++ /dev/null @@ -1,158 +0,0 @@ ---- -title: "Excample of generating mock data using PHIAT-YLL files based on variable and variable-details sheets" -author: "Juan Li" -date: 2025-07-02 -format: - html: - toc: true - html-math-method: katex - css: styles.css -editor: visual ---- - -Some resources: - - - -```{r} -#| warning: false -#| message: false -#| output: false - -library(dplyr) # Data manipulation -library(stringr) # Working with strings -#library(simstudy) # Generate simulated data sets: https://cran.r-project.org/web/packages/simstudy/vignettes/simstudy.html - -# source helper functions -source("R/create_cat_var.R") -source("R/create_con_var.R") -source("R/util.R") -``` - -## Read in variable and variable_details sheet - -```{r} -# PHIAT-YLL variables -variables <- read.csv("Worksheets/phiatyll_variables.csv", header = T, check.names=FALSE, na.strings=c("","NA","N/A")) # PHIAT-YLL variables -# CCHS variable details -variable_details_c <- read.csv("Worksheets/cchsflow-variable-details.csv", header = T, check.names=FALSE, na.strings=c("","NA","N/A")) -# additional PHIAT-YLL variable details -variable_details_p <- read.csv("Worksheets/phiatyll_variables_details.csv", header = T, check.names=FALSE, na.strings=c("","NA","N/A")) - -variable_details <- bind_rows(variable_details_c, variable_details_p) %>% - filter(variable %in% variables$variable) -``` - -## Get required cycles - -```{r} -cycles <- sort(unique(unlist(str_split(paste(variables$databaseStart, collapse = ","), ",")))) -(cycles <- str_trim(cycles[str_detect(cycles, "cchs")])) -``` - -## Get variable names of each type - -```{r} -# --- derived variables --- -var_derived <- unique(variable_details[str_detect(variable_details$variableStart, "DerivedVar::") | - str_detect(variable_details$variable, "_der"), "variable"]) -print("--- Derived variables: ---") -print(var_derived) - -# --- original variables --- -# categorical variables -var_cat <- unique(variables[variables$variableType == "Categorical", "variable"]) -var_cat <- var_cat[!(var_cat %in% var_derived)] # remove derived variable -print("--- Categorical variables: ---") -print(var_cat) - -# continuous variables -var_con <- unique(variables[variables$variableType == "Continuous", "variable"]) -var_con <- var_con[!(var_con %in% var_derived)] # remove derived variable -print("--- Continuous variables: ---") -print(var_con) - -# check -nrow(variables) == length(var_derived) + length(var_cat) + length(var_con) -``` - -## 1. Generate mock data of original variables - -### Categorical variables - -```{r} -length <- 5 - -df_cat <- data.frame() -for (cycle in cycles) { - df_i <- data.frame(cycle = rep(cycle, length)) - for (var in var_cat) { - col <- create_cat_var(var, cycle, variable_details, length, df_i) - df_i <- bind_cols(df_i, col) - } - df_cat <- bind_rows(df_cat, df_i) -} -``` - -### Continuous variables - -```{r} -df_con <- data.frame() -for (cycle in cycles) { - df_i <- data.frame(cycle = rep(cycle, length)) - for (var in var_con) { - col <- create_con_var(var, cycle, variable_details, length, df_i, type = "uniform") - df_i <- bind_cols(df_i, col) - } - df_con <- bind_rows(df_con, df_i) -} -``` - -### combine - -```{r} -df <- bind_cols(df_cat, df_con[, !(names(df_con) %in% names(df_cat))]) -``` - -```{r} -# check -df_2003 <- df %>% filter(cycle == cycles[1]) -nNA <- colSums(is.na(df_2003)) -df_2003[, nNA == 0] -``` - -## 2. Generate mock data of derived variables - -```{r} - -``` - -## 3. Optional: further manipulate data - -### Add missing data - -```{r} - -``` - -### Add spoiled data - -```{r} - -``` - -## 4. Add info from Table 1 - -```{r} - -``` - -## 5. Add info from correlation matrix - -```{r} - -``` - -```{r} - -``` \ No newline at end of file diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..17a1bee --- /dev/null +++ b/LICENSE @@ -0,0 +1,2 @@ +YEAR: 2025 +COPYRIGHT HOLDER: Juan Li, Doug Manuel diff --git a/MockData.Rproj b/MockData.Rproj new file mode 100644 index 0000000..69fafd4 --- /dev/null +++ b/MockData.Rproj @@ -0,0 +1,22 @@ +Version: 1.0 + +RestoreWorkspace: No +SaveWorkspace: No +AlwaysSaveHistory: Default + +EnableCodeIndexing: Yes +UseSpacesForTab: Yes +NumSpacesForTab: 2 +Encoding: UTF-8 + +RnwWeave: Sweave +LaTeX: pdfLaTeX + +AutoAppendNewline: Yes +StripTrailingWhitespace: Yes +LineEndingConversion: Posix + +BuildType: Package +PackageUseDevtools: Yes +PackageInstallArgs: --no-multiarch --with-keep.source +PackageRoxygenize: rd,collate,namespace diff --git a/NAMESPACE b/NAMESPACE new file mode 100644 index 0000000..0d0e39e --- /dev/null +++ b/NAMESPACE @@ -0,0 +1,40 @@ +# Generated by roxygen2: do not edit by hand + +S3method(print,mockdata_validation_result) +export(add_garbage) +export(apply_garbage) +export(apply_missing_codes) +export(apply_rtype_defaults) +export(create_cat_var) +export(create_con_var) +export(create_date_var) +export(create_mock_data) +export(create_wide_survival_data) +export(extract_distribution_params) +export(extract_proportions) +export(generate_garbage_values) +export(get_cycle_variables) +export(get_enabled_variables) +export(get_raw_var_dependencies) +export(get_raw_variables) +export(get_variable_details) +export(get_variables_by_role) +export(has_garbage) +export(identify_derived_vars) +export(import_from_recodeflow) +export(make_garbage) +export(parse_range_notation) +export(parse_variable_start) +export(read_mock_data_config) +export(read_mock_data_config_details) +export(sample_with_proportions) +export(validate_mock_data_config) +export(validate_mock_data_config_details) +export(validate_mockdata_metadata) +importFrom(stats,rexp) +importFrom(stats,rnorm) +importFrom(stats,runif) +importFrom(stats,setNames) +importFrom(utils,head) +importFrom(utils,read.csv) +importFrom(utils,write.csv) diff --git a/NEWS.md b/NEWS.md new file mode 100644 index 0000000..b43c9b9 --- /dev/null +++ b/NEWS.md @@ -0,0 +1,239 @@ +# MockData 0.3.0 + +## Breaking changes + +**New function API** - All generator functions now accept full metadata data frames instead of pre-filtered subsets: + +```r +# Before (v0.2.x) +var_row <- variables[variables$variable == "age", ] +details_subset <- variable_details[variable_details$variable == "age", ] +result <- create_con_var(var_row, details_subset, n = 1000) + +# After (v0.3.0) +result <- create_con_var( + var = "age", + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 1000 +) +``` + +**Affected functions:** `create_cat_var()`, `create_con_var()`, `create_date_var()`, `create_wide_survival_data()`, `create_mock_data()` + +**Deprecated:** `prop_garbage` parameter in `create_wide_survival_data()`. Use garbage parameters in metadata instead: + +```r +# Old way (no longer supported) +surv <- create_wide_survival_data(..., prop_garbage = 0.03) + +# New way +vars_with_garbage <- add_garbage(variables, "death_date", + garbage_high_prop = 0.03, garbage_high_range = "[2025-01-01, 2099-12-31]") +surv <- create_wide_survival_data(..., variables = vars_with_garbage) +``` + +## New features + +**Unified garbage generation** across all variable types (categorical, continuous, date, survival): + +- `garbage_low_prop` + `garbage_low_range` for values below valid range +- `garbage_high_prop` + `garbage_high_range` for values above valid range +- New helper function `add_garbage()` for easy garbage specification +- Categorical garbage now supported (treats codes as ordinal to generate out-of-range values) + +```r +# Add garbage to any variable type +vars_with_garbage <- add_garbage(variables, "smoking", + garbage_low_prop = 0.02, garbage_low_range = "[-2, 0]") + +# Pipe-friendly +vars_with_garbage <- variables %>% + add_garbage("age", garbage_high_prop = 0.03, garbage_high_range = "[150, 200]") %>% + add_garbage("smoking", garbage_low_prop = 0.02, garbage_low_range = "[-2, 0]") +``` + +**Derived variable identification:** + +- `identify_derived_vars()` - Identifies derived variables using `DerivedVar::` and `Func::` patterns +- `get_raw_var_dependencies()` - Extracts raw variable dependencies +- Compatible with recodeflow patterns + +## Bug fixes + +- Fixed categorical garbage factor level bug - garbage values were being converted to NA during factor creation +- Fixed `recEnd` column requirement - now optional for simple configurations +- Fixed derived variable generation in `create_mock_data()` - derived variables now correctly excluded + +## Documentation + +**Restructured using Divio framework:** + +- Removed 6 vignettes (cchs-example, chms-example, demport-example, dates, schema-change-dates, tutorial-config-files) +- Added 2 new vignettes (tutorial-categorical-continuous, tutorial-survival-data) +- Massively expanded reference-config (2,028 lines of comprehensive metadata schema documentation) +- All vignettes updated to v0.3.0 API +- All examples now use `inst/extdata/minimal-example/` only + +**Final structure (9 vignettes):** + +- **Tutorials (6):** getting-started, tutorial-categorical-continuous, tutorial-dates, tutorial-survival-data, tutorial-missing-data, tutorial-garbage-data +- **How-to guides (1):** for-recodeflow-users +- **Explanation (1):** advanced-topics +- **Reference (1):** reference-config + +**Metadata simplification:** + +- Removed `inst/extdata/cchs/`, `inst/extdata/chms/`, `inst/extdata/demport/` +- Only `inst/extdata/minimal-example/` remains as canonical reference + +## Migration guide + +**Update function calls:** + +1. Pass variable name as string (not pre-filtered row) +2. Pass full metadata data frames (not subsets) +3. Add `databaseStart` parameter +4. Remove manual filtering + +**Update garbage specification:** + +1. Remove `prop_garbage` from `create_wide_survival_data()` calls +2. Add garbage to metadata using `add_garbage()` helper + +--- + +# MockData 0.2.0 + +## Major changes + +### New configuration format (v0.2) + +- **Breaking change**: New configuration schema with `uid`/`uid_detail` system +- Replaces v0.1 `cat`/`catLabel` columns with unified metadata structure +- Adds `rType` field for explicit R type coercion (factor, integer, double, Date) +- Adds `proportion` field for direct distribution control +- Adds date-specific fields: `date_start`, `date_end`, `distribution` + +**Backward compatibility**: v0.1 format still supported via dual interface. Both formats work side-by-side. + +### Date variable generation + +- New `create_date_var()` function for date variables +- Multiple distribution options: uniform, gompertz, exponential +- Support for survival analysis patterns +- SAS date format parsing +- Three source formats: analysis (R Date), csv (ISO strings), sas (numeric) + +### Survival analysis support + +- New `create_wide_survival_data()` function for cohort studies +- Generates paired entry and event dates with guaranteed temporal ordering +- Supports censoring and multiple event distributions +- **Note**: Must be called manually (not compatible with `create_mock_data()` batch generation) + +### Data quality testing (garbage data) + +- New `prop_invalid` parameter across all generators +- Generates intentionally invalid data for testing validation pipelines +- Supports garbage types: `corrupt_future`, `corrupt_past`, `corrupt_range` +- Critical for testing data cleaning workflows + +### Batch generation + +- New `create_mock_data()` function for batch generation from CSV configuration +- New `read_mock_data_config()` and `read_mock_data_config_details()` readers +- Processes multiple variables in single call +- Fallback mode when details not provided + +### Type coercion + +- Explicit `rType` field controls R type conversion +- Proper factor handling with levels +- Integer vs double distinction for age/count variables +- Makes generated data match real survey data types + +## New functions + +- `create_date_var()` - Date variable generation +- `create_wide_survival_data()` - Paired survival dates with temporal ordering +- `create_mock_data()` - Batch generation orchestrator +- `read_mock_data_config()` - Configuration file reader +- `read_mock_data_config_details()` - Details file reader +- `determine_proportions()` - Unified proportion determination +- `import_from_recodeflow()` - Helper to adapt recodeflow metadata + +## Function updates + +- `create_cat_var()`: Add rType support, proportion parameter, uid-based filtering +- `create_con_var()`: Add rType support, proportion parameter for missing codes +- Consolidate helpers in `mockdata_helpers.R`, `config_helpers.R`, `scalar_helpers.R` + +## Documentation + +### New vignettes + +- `getting-started.qmd` - Comprehensive introduction +- `tutorial-dates.qmd` - Date configuration patterns +- `tutorial-config-files.qmd` - Batch generation workflow +- `reference-config.qmd` - Complete v0.2 schema documentation +- `advanced-topics.qmd` - Technical implementation details + +### Updated vignettes + +- `cchs-example.qmd` - Modernized to v0.2 with inline R +- `chms-example.qmd` - Modernized to v0.2 with inline R +- `demport-example.qmd` - Modernized to v0.2 with inline R +- `dates.qmd` - Aligned with v0.2 date configuration +- All vignettes use modern inline R approach + +### Metadata updates + +- `mock_data_schema.yaml` - LinkML-style schema documentation (1,222 lines) +- `metadata_registry.yaml` - Document v0.2 format +- Renamed CCHS/CHMS sample files for consistency +- Updated DemPoRT metadata with v0.2 format +- Removed deprecated ICES metadata (moved to recodeflow) + +## Package infrastructure + +- Added `_pkgdown.yml` for documentation website +- Updated NAMESPACE with new imports (stats::rexp, utils::read.csv, etc.) +- Updated DESCRIPTION with new dependencies + +## Breaking changes + +**Configuration format changes:** + +- Variable details now require `uid` and `uid_detail` columns +- `rType` field required for proper type coercion +- New date fields: `date_start`, `date_end`, `distribution` + +**Migration path:** + +- v0.1 format still works (backward compatibility maintained) +- Dual interface auto-detects format based on parameters +- v0.2 recommended for new projects + +**File changes:** + +- Renamed `R/mockdata-helpers.R` β†’ `R/mockdata_helpers.R` +- ICES metadata removed (maintained in recodeflow package) + +## Bug fixes + +- Fixed 'else' handling in `recEnd` rules (issue #5) +- Fixed create_wide_survival_data() compatibility with create_mock_data() +- Fixed Roxygen documentation link syntax errors + +## Known issues + +- Survival variable type must be generated manually with `create_wide_survival_data()` +- Cannot be used in `create_mock_data()` batch generation (requires paired variables) + +--- + +# MockData 0.1.0 + +Initial release with basic categorical and continuous variable generation. diff --git a/Note- cchsflow.docx b/Note- cchsflow.docx deleted file mode 100644 index 5d3e7ed..0000000 Binary files a/Note- cchsflow.docx and /dev/null differ diff --git a/R/MockData-package.R b/R/MockData-package.R new file mode 100644 index 0000000..3ca221e --- /dev/null +++ b/R/MockData-package.R @@ -0,0 +1,8 @@ +#' @keywords internal +"_PACKAGE" + +## usethis namespace: start +#' @importFrom stats rnorm runif rexp setNames +#' @importFrom utils head read.csv write.csv +## usethis namespace: end +NULL diff --git a/R/add_garbage.R b/R/add_garbage.R new file mode 100644 index 0000000..93289ca --- /dev/null +++ b/R/add_garbage.R @@ -0,0 +1,199 @@ +#' Add garbage specifications to variables data frame +#' +#' @description +#' Helper function to add garbage data specifications to a variables data frame. +#' This provides a convenient way to specify invalid/garbage values for quality +#' assurance testing. Works consistently across all variable types (categorical, +#' continuous, date). +#' +#' @param variables Data frame with variable metadata (typically read from +#' variables.csv) +#' @param var Character. Variable name to add garbage specifications to. Must +#' exist in `variables$variable`. +#' @param garbage_low_prop Numeric. Proportion of observations to generate as +#' low-range garbage (0-1). If NULL, no low-range garbage is added. +#' @param garbage_low_range Character. Interval notation specifying the range for +#' low-range garbage values (e.g., "[-2, 0]" for categorical, "[0, 1.4)" for +#' continuous, "[1900-01-01, 1950-12-31]" for dates). If NULL, no low-range +#' garbage is added. +#' @param garbage_high_prop Numeric. Proportion of observations to generate as +#' high-range garbage (0-1). If NULL, no high-range garbage is added. +#' @param garbage_high_range Character. Interval notation specifying the range for +#' high-range garbage values (e.g., "[10, 15]" for categorical, "[60, 150]" +#' for continuous, "[2025-01-01, 2099-12-31]" for dates). If NULL, no +#' high-range garbage is added. +#' +#' @return Modified variables data frame with garbage specifications added. +#' If the garbage columns don't exist, they are created and initialized with +#' NA for all other variables. +#' +#' @details +#' ## Unified garbage API +#' +#' All variable types use the same garbage specification pattern: +#' - `garbage_low_prop` + `garbage_low_range` for values below valid range +#' - `garbage_high_prop` + `garbage_high_range` for values above valid range +#' +#' ## Variable type examples +#' +#' **Categorical (ordinal treatment):** +#' ```r +#' # Valid codes: 1, 2, 3, 7 +#' # Generate codes -2, -1, 0 below valid range +#' vars <- add_garbage(vars, "smoking", +#' garbage_low_prop = 0.02, garbage_low_range = "[-2, 0]") +#' ``` +#' +#' **Continuous:** +#' ```r +#' # Valid range: [18, 100] +#' # Generate extreme ages above valid range +#' vars <- add_garbage(vars, "age", +#' garbage_high_prop = 0.03, garbage_high_range = "[150, 200]") +#' ``` +#' +#' **Date:** +#' ```r +#' # Valid range: [2000-01-01, 2020-12-31] +#' # Generate future dates for QA testing +#' vars <- add_garbage(vars, "death_date", +#' garbage_high_prop = 0.03, garbage_high_range = "[2025-01-01, 2099-12-31]") +#' ``` +#' +#' ## Pipe-friendly usage +#' +#' This function returns the modified variables data frame, making it +#' pipe-friendly: +#' +#' ```r +#' vars_with_garbage <- variables %>% +#' add_garbage("age", garbage_high_prop = 0.03, garbage_high_range = "[150, 200]") %>% +#' add_garbage("smoking", garbage_low_prop = 0.02, garbage_low_range = "[-2, 0]") %>% +#' add_garbage("death_date", garbage_high_prop = 0.03, +#' garbage_high_range = "[2025-01-01, 2099-12-31]") +#' ``` +#' +#' @seealso +#' - [create_cat_var()] for categorical variable generation +#' - [create_con_var()] for continuous variable generation +#' - [create_date_var()] for date variable generation +#' - [create_mock_data()] for batch generation of all variables +#' +#' @export +#' +#' @examples +#' \dontrun{ +#' # Load metadata +#' variables <- read.csv( +#' system.file("extdata/minimal-example/variables.csv", +#' package = "MockData"), +#' stringsAsFactors = FALSE, check.names = FALSE +#' ) +#' +#' # Add garbage to age (high-range only) +#' vars <- add_garbage(variables, "age", +#' garbage_high_prop = 0.03, garbage_high_range = "[150, 200]") +#' +#' # Add garbage to smoking (low-range only) +#' vars <- add_garbage(vars, "smoking", +#' garbage_low_prop = 0.02, garbage_low_range = "[-2, 0]") +#' +#' # Add garbage to BMI (two-sided contamination) +#' vars <- add_garbage(vars, "BMI", +#' garbage_low_prop = 0.02, garbage_low_range = "[-10, 15)", +#' garbage_high_prop = 0.01, garbage_high_range = "[60, 150]") +#' +#' # Generate data with garbage +#' mock_data <- create_mock_data( +#' databaseStart = "minimal-example", +#' variables = vars, +#' variable_details = variable_details, +#' n = 1000, +#' seed = 123 +#' ) +#' } +add_garbage <- function(variables, var, + garbage_low_prop = NULL, garbage_low_range = NULL, + garbage_high_prop = NULL, garbage_high_range = NULL) { + # Validate inputs + if (!is.data.frame(variables)) { + stop("'variables' must be a data frame") + } + + if (!("variable" %in% names(variables))) { + stop("'variables' data frame must contain a 'variable' column") + } + + if (!is.character(var) || length(var) != 1) { + stop("'var' must be a single character string") + } + + # Find the variable + idx <- variables$variable == var + + if (!any(idx)) { + stop("Variable '", var, "' not found in variables data frame") + } + + # Validate proportions + if (!is.null(garbage_low_prop)) { + if (!is.numeric(garbage_low_prop) || length(garbage_low_prop) != 1 || + garbage_low_prop < 0 || garbage_low_prop > 1) { + stop("'garbage_low_prop' must be a single numeric value between 0 and 1") + } + } + + if (!is.null(garbage_high_prop)) { + if (!is.numeric(garbage_high_prop) || length(garbage_high_prop) != 1 || + garbage_high_prop < 0 || garbage_high_prop > 1) { + stop("'garbage_high_prop' must be a single numeric value between 0 and 1") + } + } + + # Validate ranges + if (!is.null(garbage_low_range)) { + if (!is.character(garbage_low_range) || length(garbage_low_range) != 1) { + stop("'garbage_low_range' must be a single character string in interval notation") + } + } + + if (!is.null(garbage_high_range)) { + if (!is.character(garbage_high_range) || length(garbage_high_range) != 1) { + stop("'garbage_high_range' must be a single character string in interval notation") + } + } + + # Add garbage_low_prop if specified + if (!is.null(garbage_low_prop)) { + if (!("garbage_low_prop" %in% names(variables))) { + variables$garbage_low_prop <- NA_real_ + } + variables$garbage_low_prop[idx] <- garbage_low_prop + } + + # Add garbage_low_range if specified + if (!is.null(garbage_low_range)) { + if (!("garbage_low_range" %in% names(variables))) { + variables$garbage_low_range <- NA_character_ + } + variables$garbage_low_range[idx] <- garbage_low_range + } + + # Add garbage_high_prop if specified + if (!is.null(garbage_high_prop)) { + if (!("garbage_high_prop" %in% names(variables))) { + variables$garbage_high_prop <- NA_real_ + } + variables$garbage_high_prop[idx] <- garbage_high_prop + } + + # Add garbage_high_range if specified + if (!is.null(garbage_high_range)) { + if (!("garbage_high_range" %in% names(variables))) { + variables$garbage_high_range <- NA_character_ + } + variables$garbage_high_range[idx] <- garbage_high_range + } + + variables +} diff --git a/R/config_helpers.R b/R/config_helpers.R new file mode 100644 index 0000000..58a4fed --- /dev/null +++ b/R/config_helpers.R @@ -0,0 +1,160 @@ +#' Get variables by role +#' +#' @description +#' Filters a MockData configuration to return only variables matching one or more roles. +#' The role column can contain comma-separated values (e.g., "predictor, outcome"), +#' so this function uses pattern matching to find all matching variables. +#' +#' @param config Data frame. Configuration from read_mock_data_config(). +#' @param roles Character vector. Role(s) to filter for (e.g., c("enabled", "predictor")). +#' +#' @return Data frame with subset of config rows matching any of the specified roles. +#' +#' @details +#' This function handles comma-separated role values by using grepl() pattern matching. +#' A variable matches if its role column contains any of the specified role values. +#' +#' Common role values: +#' - enabled: Variables to generate in mock data +#' - predictor: Predictor variables for analysis +#' - outcome: Outcome variables +#' - confounder: Confounding variables +#' - exposure: Exposure variables +#' - intermediate: Intermediate/derived variables +#' - table1_master, table1_sub: Table 1 display variables +#' - metadata: Study metadata (dates, identifiers) +#' +#' @examples +#' \dontrun{ +#' # Load configuration +#' config <- read_mock_data_config("inst/extdata/mock_data_config.csv") +#' +#' # Get all predictor variables +#' predictors <- get_variables_by_role(config, "predictor") +#' +#' # Get variables with multiple roles +#' outcomes <- get_variables_by_role(config, c("outcome", "exposure")) +#' +#' # Get Table 1 variables +#' table1_vars <- get_variables_by_role(config, c("table1_master", "table1_sub")) +#' } +#' +#' @family configuration +#' @export +get_variables_by_role <- function(config, roles) { + + # Input validation + if (!is.data.frame(config)) { + stop("config must be a data frame") + } + + if (!"role" %in% names(config)) { + stop("config must have a 'role' column") + } + + if (!is.character(roles) || length(roles) == 0) { + stop("roles must be a non-empty character vector") + } + + # Build pattern to match any of the specified roles + # Use word boundaries to avoid partial matches (e.g., "table1" shouldn't match "table1_master") + pattern <- paste0("\\b(", paste(roles, collapse = "|"), ")\\b") + + # Filter using grepl (handles comma-separated role values) + matches <- grepl(pattern, config$role, ignore.case = FALSE) + + result <- config[matches, ] + + # Return empty data frame with same structure if no matches + if (nrow(result) == 0) { + warning("No variables found with role(s): ", paste(roles, collapse = ", ")) + } + + return(result) +} + + +#' Get enabled variables +#' +#' @description +#' Convenience function to get all variables marked with role "enabled", +#' excluding derived variables by default. Derived variables should be +#' calculated after generating raw mock data, not generated directly. +#' +#' @param config Data frame. Configuration from read_mock_data_config(). +#' @param exclude_derived Logical. If TRUE (default), exclude derived variables +#' identified by recodeflow patterns (DerivedVar::, Func::). Derived variables +#' are calculated from raw variables and should not be generated as mock data. +#' @param variable_details Data frame. Required when exclude_derived = TRUE. +#' Detail-level metadata with columns: variable, recStart, recEnd. Contains +#' DerivedVar:: and Func:: patterns that identify derived variables. +#' +#' @return Data frame with subset of config rows where role contains "enabled" +#' and not identified as derived (unless exclude_derived = FALSE). +#' +#' @details +#' The "enabled" role indicates variables that should be included when generating +#' mock data. However, derived variables are calculated from other variables and +#' should NOT be generated directly. +#' +#' **Derived variables**: Variables calculated from raw data (e.g., BMI from +#' height and weight, pack-years from smoking variables). These are identified +#' by recodeflow patterns in variable_details: +#' - `DerivedVar::[VAR1, VAR2, ...]` in variable_details.recStart +#' - `Func::function_name` in variable_details.recEnd +#' +#' **Default behavior**: Excludes derived variables to prevent generating +#' variables that should be calculated from raw data. +#' +#' **Note**: This function uses pattern-based detection (recodeflow approach), +#' NOT role column flags. The role column is NOT checked for "derived" status. +#' +#' @examples +#' \dontrun{ +#' # Load configuration +#' config <- read_mock_data_config("inst/extdata/mock_data_config.csv") +#' variable_details <- read.csv("inst/extdata/variable_details.csv") +#' +#' # Get only enabled RAW variables (excludes derived, default) +#' enabled_vars <- get_enabled_variables(config, variable_details = variable_details) +#' +#' # Include derived variables (not recommended) +#' all_enabled <- get_enabled_variables(config, exclude_derived = FALSE) +#' +#' # View enabled variable names +#' enabled_vars$variable +#' } +#' +#' @family configuration +#' @export +get_enabled_variables <- function(config, exclude_derived = TRUE, variable_details = NULL) { + # Get all enabled variables + enabled_vars <- get_variables_by_role(config, "enabled") + + # Exclude derived variables if requested (default) + if (exclude_derived) { + # Require variable_details for pattern-based detection + if (is.null(variable_details)) { + stop("variable_details is required when exclude_derived = TRUE. ", + "Derived variables are identified by DerivedVar:: and Func:: patterns ", + "in variable_details, not by role column. ", + "Pass variable_details parameter or set exclude_derived = FALSE.") + } + + # Use pattern-based detection (recodeflow approach) + derived_vars <- identify_derived_vars(enabled_vars, variable_details) + + # Filter out derived variables + if (length(derived_vars) > 0) { + enabled_vars <- enabled_vars[!enabled_vars$variable %in% derived_vars, ] + } + + # Return empty data frame with same structure if no matches + if (nrow(enabled_vars) == 0) { + warning("No enabled non-derived variables found. ", + "All enabled variables are derived variables.") + } + } + + return(enabled_vars) +} diff --git a/R/create_cat_var.R b/R/create_cat_var.R index bc11edd..936e0d2 100644 --- a/R/create_cat_var.R +++ b/R/create_cat_var.R @@ -1,69 +1,322 @@ -#' @description This function creates categorical variables based on specifications from `variable` and `variable-details` sheets. +#' Create categorical variable for MockData +#' +#' Generates a categorical mock variable based on specifications from metadata. +#' +#' @param var character. Variable name to generate (column name in output) +#' @param databaseStart character. Database/cycle identifier for filtering metadata +#' (e.g., "cchs2001_p", "minimal-example"). Used to filter variables and +#' variable_details to the specified database. +#' @param variables data.frame or character. Variable-level metadata containing: +#' \itemize{ +#' \item \code{variable}: Variable names +#' \item \code{database}: Database identifier (optional, for filtering) +#' \item \code{rType}: R output type (factor/character/integer/logical) +#' \item \code{garbage_low_prop}, \code{garbage_high_prop}: Garbage data parameters +#' } +#' Can also be a file path (character) to variables.csv. +#' @param variable_details data.frame or character. Detail-level metadata containing: +#' \itemize{ +#' \item \code{variable}: Variable name (for joining) +#' \item \code{recStart}: Category code or range +#' \item \code{recEnd}: Classification (numeric code, "NA::a", "NA::b") +#' \item \code{proportion}: Category proportion (0-1, must sum to 1) +#' \item \code{catLabel}: Category label/description +#' } +#' Can also be a file path (character) to variable_details.csv. +#' @param df_mock data.frame. Optional. Existing mock data (to check if variable already exists). +#' @param prop_missing numeric. Proportion of missing values (0-1). Default 0 (no missing). +#' If > 0, function looks for rows with recEnd containing "NA::" in variable_details. +#' @param n integer. Number of observations to generate. +#' @param seed integer. Optional. Random seed for reproducibility. +#' +#' @return data.frame with one column (the generated categorical variable), or NULL if: +#' \itemize{ +#' \item Variable not found in metadata +#' \item Variable already exists in df_mock +#' \item No valid categories found in variable_details +#' } +#' +#' @details +#' **v0.3.0 API**: This function now accepts full metadata data frames and filters +#' internally for the specified variable and database. This is the "recodeflow pattern" +#' where filtering is handled inside the function. +#' +#' **Generation process**: +#' \enumerate{ +#' \item Filter metadata: Extract rows for specified var + database +#' \item Extract proportions: Read from variable_details (proportion column) +#' \item Generate population: Sample categories based on proportions +#' \item Apply missing codes: If prop_missing > 0 or proportions in metadata +#' \item Apply garbage: Read garbage parameters from variables.csv +#' \item Apply rType: Coerce to specified R type (factor/character/integer/logical) +#' } +#' +#' **Type coercion (rType)**: +#' The rType column in variables.csv controls output data type: +#' \itemize{ +#' \item \code{"factor"}: Factor with levels from category codes (default for categorical) +#' \item \code{"character"}: Character vector +#' \item \code{"integer"}: Integer (for numeric category codes) +#' \item \code{"logical"}: Logical (for TRUE/FALSE categories) +#' } +#' +#' **Missing data**: +#' Missing codes are identified by \code{recEnd} containing "NA::": +#' \itemize{ +#' \item \code{NA::a}: Skip codes (not applicable) +#' \item \code{NA::b}: Missing codes (don't know, refusal, not stated) +#' } +#' Proportions for missing codes are read from the proportion column in variable_details. +#' +#' **Garbage data**: +#' Garbage parameters are read from variables.csv: +#' \itemize{ +#' \item \code{garbage_low_prop}, \code{garbage_low_range}: Below-range invalid values +#' \item \code{garbage_high_prop}, \code{garbage_high_range}: Above-range invalid values +#' } #' -#' @param var string. The variable name to be created. -#' @param cycle string. The cycle to which the variable belongs (e.g., "CCHS2001"). -#' @param variable_details data.frame. A data frame containing variable details, typically loaded from a "variable-details" sheet. -#' @param length integer. The desired length of the categorical variable vector. -#' @param df_mock data frame, the current generated mock data, to check if the raw variable has already been created. -#' @param prop_NA numeric. Optional. The proportion of NA values to be introduced. If NULL, no NA values are introduced. -#' @param seed integer. Optional. Seed for reproducibility. Default is 100. -#' @return A data frame with one column representing the newly created categorical variable. #' @examples -#' # Assuming 'variable_details' is loaded -#' # create_cat_var("gender", "HC1", variable_details, 100) -#' # create_cat_var("race", "HC1", variable_details, 100, prop_NA = 0.1) - -create_cat_var <- function(var, cycle, variable_details, length, df_mock, prop_NA = NULL, seed = 100) { - # related rows in variable_details - var_details <- variable_details[variable_details$variable == var & str_detect(variable_details$variableStart, cycle),] - - if (nrow(var_details) > 0) { - # extract the row variable name in the corresponding cycle - temp <- unlist(str_split(var_details$variableStart[1],",")) - var_raw <- unlist(str_split(temp[str_detect(temp, cycle)],"::"))[2] - - if (!(var_raw %in% names(df_mock))) { - # extract categories from `recStart` column - # real levels - labels <- var_details$recStart[!(str_detect(var_details$recEnd, "NA"))] - if (any(str_detect(labels, ","))) { # unpack the ranges - temp <- labels[!str_detect(labels, ",")] - ranges <- labels[str_detect(labels, ",")] - for (range in ranges) { - temp <- c(temp, unpack_range(range)) - } - labels <- sort(temp) - } - # NA levels - NA_labels <- var_details$recStart[str_detect(var_details$recEnd, "NA")] - if (any(str_detect(NA_labels, ","))) { # unpack the ranges - temp <- NA_labels[!str_detect(NA_labels, ",")] - ranges <- NA_labels[str_detect(NA_labels, ",")] - for (range in ranges) { - temp <- c(temp, unpack_range(range)) - } - NA_labels <- sort(temp) - } - - # create mock variable - if (is.null(prop_NA)) { - set.seed(seed) - col <- data.frame(new = sample(labels, length, replace = T)) - } else { # optional: add NA levels - set.seed(seed) - vec <- sample(labels, length * (1-prop_NA), replace = T) - set.seed(seed) - vec.na <- sample(NA_labels, length * prop_NA, replace = T) - - vec <- sample(c(vec, vec.na)) # combine and randomly sorted - col <- data.frame(new = c(vec, vec.na))[1:length] - } - names(col)[1] <- var_raw - - return(col) +#' \dontrun{ +#' # Basic usage with metadata data frames +#' smoking <- create_cat_var( +#' var = "smoking", +#' databaseStart = "cchs2001_p", +#' variables = variables, +#' variable_details = variable_details, +#' n = 1000, +#' seed = 123 +#' ) +#' +#' # Expected output: data.frame with 1000 rows, 1 column ("smoking") +#' # Values: Factor with levels from metadata (e.g., "1", "2", "3", "7") +#' # Distribution: Based on proportions in variable_details +#' # Example: +#' # smoking +#' # 1 1 +#' # 2 3 +#' # 3 2 +#' # 4 1 +#' # 5 7 +#' # ... +#' +#' # With missing data (uses proportions from metadata) +#' smoking <- create_cat_var( +#' var = "smoking", +#' databaseStart = "cchs2001_p", +#' variables = variables, +#' variable_details = variable_details, +#' n = 1000 +#' ) +#' # Missing codes (recEnd = "NA::b") automatically included based on proportions +#' +#' # With file paths instead of data frames +#' result <- create_cat_var( +#' var = "smoking", +#' databaseStart = "cchs2001_p", +#' variables = "path/to/variables.csv", +#' variable_details = "path/to/variable_details.csv", +#' n = 1000 +#' ) +#' } +#' +#' @family generators +#' @export +create_cat_var <- function(var, + databaseStart, + variables, + variable_details, + df_mock = NULL, + prop_missing = 0, + n, + seed = NULL) { + + # ========== PARAMETER VALIDATION ========== + + # Load metadata from file paths if needed + if (is.character(variables) && length(variables) == 1) { + variables <- read.csv(variables, stringsAsFactors = FALSE, check.names = FALSE) + } + if (is.character(variable_details) && length(variable_details) == 1) { + variable_details <- read.csv(variable_details, stringsAsFactors = FALSE, check.names = FALSE) + } + + # ========== INTERNAL FILTERING (recodeflow pattern) ========== + + # Filter variables for this var + var_row <- variables[variables$variable == var, ] + + if (nrow(var_row) == 0) { + warning(paste0("Variable '", var, "' not found in variables metadata")) + return(NULL) + } + + # Take first row if multiple matches + if (nrow(var_row) > 1) { + var_row <- var_row[1, ] + } + + # Filter variable_details for this var AND database (using databaseStart) + # databaseStart is a recodeflow core column containing comma-separated database identifiers + if ("databaseStart" %in% names(variable_details)) { + details_subset <- variable_details[ + variable_details$variable == var & + (is.na(variable_details$databaseStart) | + variable_details$databaseStart == "" | + grepl(databaseStart, variable_details$databaseStart, fixed = TRUE)), + ] + } else { + # Fallback: no databaseStart filtering (for simple configs) + details_subset <- variable_details[variable_details$variable == var, ] + } + + # ========== CHECK IF VARIABLE ALREADY EXISTS ========== + + if (!is.null(df_mock) && var %in% names(df_mock)) { + return(NULL) + } + + # ========== SET SEED ========== + + if (!is.null(seed)) set.seed(seed) + + # ========== FALLBACK MODE: Simple generation if no details ========== + + if (nrow(details_subset) == 0) { + # Generate simple 2-category variable with uniform distribution + values <- sample(c("1", "2"), size = n, replace = TRUE) + + col <- data.frame( + new = values, + stringsAsFactors = FALSE + ) + names(col)[1] <- var + return(col) + } + + # ========== EXTRACT PROPORTIONS ========== + + props <- extract_proportions(details_subset, variable_name = var) + + # Check if we have valid categories + if (length(props$categories) == 0) { + warning(paste0("No valid categories found for ", var)) + return(NULL) + } + + # ========== STEP 1: Generate population (valid values only) ========== + + # Calculate number of valid observations (excluding missing) + n_valid <- floor(n * props$valid) + + # Generate category assignments based on category-specific proportions + valid_assignments <- sample_with_proportions( + categories = props$categories, + proportions = props$category_proportions, + n = n_valid, + seed = NULL # Already set globally if needed + ) + + # ========== STEP 2: Apply missing codes ========== + + # Calculate number of each missing type + n_missing <- n - n_valid + + if (n_missing > 0 && length(props$missing) > 0) { + # Generate missing assignments + missing_assignments <- sample( + names(props$missing), + size = n_missing, + replace = TRUE, + prob = unlist(props$missing) + ) + + # Combine valid and missing assignments + all_assignments <- c(valid_assignments, missing_assignments) + + # Create map of missing categories to their codes + missing_map <- list() + for (miss_cat in names(props$missing)) { + miss_row <- details_subset[details_subset$recStart == miss_cat, ] + if (nrow(miss_row) > 0) { + # Use recStart itself if value is NA or not present + code_value <- if ("value" %in% names(miss_row) && !is.na(miss_row$value[1])) { + miss_row$value[1] + } else { + miss_cat # Use recStart (e.g., "7" or "[7,9]") as the value } - } -} + missing_map[[miss_cat]] <- code_value + } + } + + # Apply missing codes (replaces missing category names with actual codes) + values <- apply_missing_codes( + values = all_assignments, + category_assignments = all_assignments, + missing_code_map = missing_map + ) + } else { + # No missing codes needed + values <- valid_assignments + } + + # ========== STEP 3: Apply garbage data if specified in variables.csv ========== + + # Extract missing codes from missing_map (metadata-based) + missing_codes_vec <- NULL + if (exists("missing_map") && length(missing_map) > 0) { + # Flatten missing_map to get all numeric codes + missing_codes_vec <- unique(unlist(missing_map)) + } + values <- apply_garbage( + values = values, + var_row = var_row, + variable_type = "categorical", + missing_codes = missing_codes_vec, # Pass metadata-based missing codes + seed = NULL # Already set globally if needed + ) + # ========== STEP 4: Apply rType coercion if specified ========== + # Read rType from var_row (variables.csv) + if ("rType" %in% names(var_row)) { + r_type <- var_row$rType + if (!is.null(r_type) && !is.na(r_type) && r_type != "") { + values <- switch(r_type, + "factor" = { + # Extract category levels from details_subset + categories <- unique(details_subset$recStart[!is.na(details_subset$recStart)]) + + # If garbage was applied, include garbage values in factor levels + # This ensures garbage codes don't get converted to NA + all_values <- unique(values[!is.na(values)]) + if (any(!all_values %in% categories)) { + # Garbage values present - use all observed values as levels + # Sort to put valid codes first, then garbage codes + valid_levels <- categories[categories %in% all_values] + garbage_levels <- all_values[!all_values %in% categories] + combined_levels <- c(valid_levels, sort(garbage_levels)) + factor(values, levels = combined_levels) + } else { + # No garbage - use only metadata-defined levels + factor(values, levels = categories) + } + }, + "character" = as.character(values), + "integer" = as.integer(values), + "logical" = as.logical(values), + values # No coercion for other types + ) + } + } + + # ========== RETURN AS DATA FRAME ========== + + col <- data.frame( + new = values, + stringsAsFactors = FALSE + ) + names(col)[1] <- var + + return(col) +} diff --git a/R/create_con_var.R b/R/create_con_var.R index 1a9b71c..f688663 100644 --- a/R/create_con_var.R +++ b/R/create_con_var.R @@ -1,75 +1,364 @@ -#' @description This function creates continuous variables based on specifications from `variable` and `variable-details` sheets. +#' Create continuous variable for MockData #' -#' @param var A string representing the variable name. -#' @param cycle A string indicating the cycle (e.g., "CCHS2001"). -#' @param variable_details A data frame containing details about variables, including ranges and NA specifications. -#' @param length An integer specifying the desired length of the generated variable. -#' @param df_mock data frame, the current generated mock data, to check if the raw variable has already been created. -#' @param type A string indicating the distribution type for the continuous variable. Can be "normal" or "uniform". Default is "normal". -#' @param prop_NA A numeric value between 0 and 1, representing the proportion of NAs to introduce. If NULL, no NAs are introduced. Default is NULL. -#' @param seed An integer for setting the random seed to ensure reproducibility. Default is 100. +#' Generates a continuous mock variable based on specifications from metadata. +#' +#' @param var character. Variable name to generate (column name in output) +#' @param databaseStart character. Database/cycle identifier for filtering metadata +#' (e.g., "cchs2001_p", "minimal-example"). Used to filter variables and +#' variable_details to the specified database. +#' @param variables data.frame or character. Variable-level metadata containing: +#' \itemize{ +#' \item \code{variable}: Variable names +#' \item \code{database}: Database identifier (optional, for filtering) +#' \item \code{rType}: R output type (integer/double) +#' \item \code{distribution}: Distribution type (uniform/normal/exponential) +#' \item \code{mean}, \code{sd}: Normal distribution parameters +#' \item \code{rate}, \code{shape}: Exponential/Gompertz parameters +#' \item \code{garbage_low_prop}, \code{garbage_high_prop}: Garbage data parameters +#' } +#' Can also be a file path (character) to variables.csv. +#' @param variable_details data.frame or character. Detail-level metadata containing: +#' \itemize{ +#' \item \code{variable}: Variable name (for joining) +#' \item \code{recStart}: Valid range in interval notation (e.g., [18,100]) +#' \item \code{recEnd}: Classification (copy, NA::a, NA::b) +#' \item \code{proportion}: Category proportion for missing codes +#' } +#' Can also be a file path (character) to variable_details.csv. +#' @param df_mock data.frame. Optional. Existing mock data (to check if variable already exists). +#' @param prop_missing numeric. Proportion of missing values (0-1). Default 0 (no missing). +#' @param n integer. Number of observations to generate. +#' @param seed integer. Optional. Random seed for reproducibility. +#' +#' @return data.frame with one column (the generated continuous variable), or NULL if: +#' \itemize{ +#' \item Variable not found in metadata +#' \item Variable already exists in df_mock +#' \item No valid range found in variable_details +#' } +#' +#' @details +#' **v0.3.0 API**: This function now accepts full metadata data frames and filters +#' internally for the specified variable and database. This is the "recodeflow pattern" +#' where filtering is handled inside the function. +#' +#' **Generation process**: +#' \enumerate{ +#' \item Filter metadata: Extract rows for specified var + database +#' \item Extract distribution parameters: Read from variables.csv +#' \item Extract valid range: Parse from variable_details recStart column +#' \item Generate population: Based on distribution type (uniform/normal/exponential) +#' \item Apply missing codes: If proportions specified in metadata +#' \item Apply garbage: Read garbage parameters from variables.csv +#' \item Apply rType: Coerce to specified R type (integer/double) +#' } +#' +#' **Type coercion (rType)**: +#' The rType column in variables.csv controls output data type: +#' \itemize{ +#' \item \code{\"integer\"}: Rounds and converts to integer (for age, counts) +#' \item \code{\"double\"}: Double precision (default for continuous) +#' } +#' +#' **Distribution types**: +#' \itemize{ +#' \item \code{\"uniform\"}: Uniform distribution over [min, max] from recStart +#' \item \code{\"normal\"}: Normal distribution (requires mean, sd in variables.csv) +#' \item \code{\"exponential\"}: Exponential distribution (requires rate in variables.csv) +#' } +#' +#' **Missing data**: +#' Missing codes are identified by recEnd containing "NA::": +#' \itemize{ +#' \item \code{NA::a}: Skip codes (not applicable) +#' \item \code{NA::b}: Missing codes (don't know, refusal, not stated) +#' } +#' +#' **Garbage data**: +#' Garbage parameters are read from variables.csv: +#' \itemize{ +#' \item \code{garbage_low_prop}, \code{garbage_low_range}: Below-range invalid values +#' \item \code{garbage_high_prop}, \code{garbage_high_range}: Above-range invalid values +#' } #' -#' @return A data frame with one column, representing the newly created continuous variable. The column name will be the raw variable name extracted from `variable_details`. #' @examples -#' # Assuming 'variable_details' is a pre-loaded data frame with variable specifications -#' # create_con_var("age", "cycle1", variable_details, 1000, type = "normal") -#' # create_con_var("income", "cycle2", variable_details, 500, type = "uniform", prop_NA = 0.1) +#' \dontrun{ +#' # Basic usage with metadata data frames +#' age <- create_con_var( +#' var = "age", +#' databaseStart = "cchs2001_p", +#' variables = variables, +#' variable_details = variable_details, +#' n = 1000, +#' seed = 123 +#' ) +#' +#' # Expected output: data.frame with 1000 rows, 1 column ("age") +#' # Values: Numeric based on distribution in metadata +#' # Example for age with normal(50, 15): +#' # age +#' # 1 45 +#' # 2 52 +#' # 3 48 +#' # 4 61 +#' # 5 39 +#' # ... +#' # Distribution: Normal(mean=50, sd=15), clipped to [18,100] +#' # Type: Integer (if rType="integer" in metadata) #' +#' # With file paths instead of data frames +#' result <- create_con_var( +#' var = "BMI", +#' databaseStart = "minimal-example", +#' variables = "path/to/variables.csv", +#' variable_details = "path/to/variable_details.csv", +#' n = 1000 +#' ) +#' } +#' +#' @family generators +#' @export +create_con_var <- function(var, + databaseStart, + variables, + variable_details, + df_mock = NULL, + prop_missing = 0, + n, + seed = NULL) { -create_con_var <- function(var, cycle, variable_details, length, df_mock, - type = "normal", prop_NA = NULL, seed = 100) { - # related rows in variable_details - var_details <- variable_details[variable_details$variable == var & str_detect(variable_details$variableStart, cycle),] - - if (nrow(var_details) > 0) { - # extract the row variable name in the corresponding cycle - temp <- unlist(str_split(var_details$variableStart[1],",")) - var_raw <- unlist(str_split(temp[str_detect(temp, cycle)],"::"))[2] - - if (!(var_raw %in% names(df_mock))) { - # extract values from `recStart` column - # real levels - rng <- var_details$recStart[!(str_detect(var_details$recEnd, "NA"))] - rng <- as.numeric(unlist(str_extract_all(rng, "\\d+\\.?\\d*"))) # extract integers or float - - # NA levels - NA_labels <- var_details$recStart[str_detect(var_details$recEnd, "NA")] - if (any(str_detect(NA_labels, ","))) { # unpack the ranges - temp <- NA_labels[!str_detect(NA_labels, ",")] - ranges <- NA_labels[str_detect(NA_labels, ",")] - for (range in ranges) { - temp <- c(temp, unpack_range(range)) - } - NA_labels <- sort(temp) + # ========== PARAMETER VALIDATION ========== + + # Load metadata from file paths if needed + if (is.character(variables) && length(variables) == 1) { + variables <- read.csv(variables, stringsAsFactors = FALSE, check.names = FALSE) + } + if (is.character(variable_details) && length(variable_details) == 1) { + variable_details <- read.csv(variable_details, stringsAsFactors = FALSE, check.names = FALSE) + } + + # ========== INTERNAL FILTERING (recodeflow pattern) ========== + + # Filter variables for this var + var_row <- variables[variables$variable == var, ] + + if (nrow(var_row) == 0) { + warning(paste0("Variable '", var, "' not found in variables metadata")) + return(NULL) + } + + # Take first row if multiple matches + if (nrow(var_row) > 1) { + var_row <- var_row[1, ] + } + + # Filter variable_details for this var AND database (using databaseStart) + # databaseStart is a recodeflow core column containing comma-separated database identifiers + if ("databaseStart" %in% names(variable_details)) { + details_subset <- variable_details[ + variable_details$variable == var & + (is.na(variable_details$databaseStart) | + variable_details$databaseStart == "" | + grepl(databaseStart, variable_details$databaseStart, fixed = TRUE)), + ] + } else { + # Fallback: no databaseStart filtering (for simple configs) + details_subset <- variable_details[variable_details$variable == var, ] + } + + # ========== CHECK IF VARIABLE ALREADY EXISTS ========== + + if (!is.null(df_mock) && var %in% names(df_mock)) { + return(NULL) + } + + # ========== SET SEED ========== + + if (!is.null(seed)) set.seed(seed) + + # ========== FALLBACK MODE: Uniform [0, 100] if no details ========== + + if (nrow(details_subset) == 0) { + values <- runif(n, min = 0, max = 100) + + col <- data.frame( + new = values, + stringsAsFactors = FALSE + ) + names(col)[1] <- var + return(col) + } + + # ========== EXTRACT DISTRIBUTION PARAMETERS ========== + + # Extract distribution parameters from var_row (v0.3.0 schema) + distribution_type <- if ("distribution" %in% names(var_row) && !is.na(var_row$distribution)) { + var_row$distribution + } else { + "uniform" # default + } + + mean_val <- if ("mean" %in% names(var_row)) as.numeric(var_row$mean) else NULL + sd_val <- if ("sd" %in% names(var_row)) as.numeric(var_row$sd) else NULL + rate_val <- if ("rate" %in% names(var_row)) as.numeric(var_row$rate) else NULL + shape_val <- if ("shape" %in% names(var_row)) as.numeric(var_row$shape) else NULL + + # Extract range from details_subset recStart (interval notation like [18,100]) + range_min <- NULL + range_max <- NULL + if (nrow(details_subset) > 0 && "recStart" %in% names(details_subset)) { + # Parse first recStart that looks like interval notation + for (i in seq_len(nrow(details_subset))) { + rec_val <- details_subset$recStart[i] + if (!is.na(rec_val) && grepl("^\\[.*,.*\\]$", rec_val)) { + parsed <- parse_range_notation(rec_val) + if (!is.null(parsed) && !is.null(parsed$min) && !is.null(parsed$max)) { + range_min <- parsed$min + range_max <- parsed$max + break + } } + } + } + + # ========== STEP 1: Generate population (valid values only) ========== + + # Extract proportions to determine valid vs missing + props <- extract_proportions(details_subset, variable_name = var) + n_valid <- floor(n * props$valid) + + # Generate based on distribution type + if (distribution_type == "normal" && !is.na(mean_val) && !is.na(sd_val)) { + # Normal distribution + values <- rnorm(n_valid, mean = mean_val, sd = sd_val) + + # Clip to range if specified + if (!is.null(range_min) && !is.null(range_max)) { + values <- pmax(range_min, pmin(range_max, values)) + } + + } else if (distribution_type == "exponential" && !is.na(rate_val)) { + # Exponential distribution + values <- rexp(n_valid, rate = rate_val) + + # Clip to range if specified + if (!is.null(range_max)) { + values <- pmin(range_max, values) + } + + } else { + # Uniform distribution (default) + if (is.null(range_min)) range_min <- 0 + if (is.null(range_max)) range_max <- 100 + + values <- runif(n_valid, min = range_min, max = range_max) + } + + # ========== STEP 2: Apply missing codes ========== + + n_missing <- n - n_valid - # create mock variable - if (is.null(prop_NA)) { - col <- data.frame(new = create_vec(length, rng, type, seed)) - } else { # optional: add NA levels - vec <- create_vec(length * (1-prop_NA), rng, type, seed) - set.seed(seed) - vec.na <- sample(NA_labels, length * prop_NA, replace = T) + if (n_missing > 0 && length(props$missing) > 0) { + # Generate missing assignments + missing_assignments <- sample( + names(props$missing), + size = n_missing, + replace = TRUE, + prob = unlist(props$missing) + ) - vec <- sample(c(vec, vec.na)) # combine and randomly sorted - col <- data.frame(new = c(vec, vec.na))[1:length] + # Create placeholder values for missing (will be replaced) + missing_values <- rep(NA, n_missing) + + # Combine valid and missing + all_values <- c(values, missing_values) + all_assignments <- c(rep("valid", n_valid), missing_assignments) + + # Create map of missing categories to their codes + missing_map <- list() + for (miss_cat in names(props$missing)) { + miss_row <- details_subset[details_subset$recStart == miss_cat, ] + if (nrow(miss_row) > 0) { + # For continuous variables, missing codes should be numeric + # Check if 'value' column exists or use recStart + code_value <- if ("value" %in% names(miss_row) && !is.na(miss_row$value[1])) { + miss_row$value[1] + } else { + NA + } + + if (is.na(code_value) || length(code_value) == 0) { + # Parse recStart to extract numeric codes + # For ranges like "[997,999]", sample from 997, 998, 999 + # For single values like "996", use as-is + parsed <- parse_range_notation(miss_cat) + + if (!is.null(parsed) && parsed$type == "integer" && !is.null(parsed$values)) { + # Integer range - use expanded values (e.g., [997,999] β†’ c(997, 998, 999)) + code_value <- parsed$values + } else if (!is.null(parsed) && parsed$type == "single_value") { + # Single numeric value + code_value <- parsed$value + } else { + # Fallback: try to convert to numeric + code_value <- suppressWarnings(as.numeric(miss_cat)) + if (is.na(code_value)) { + # If all else fails, use the string + code_value <- miss_cat + } + } + } + + missing_map[[miss_cat]] <- code_value } - names(col)[1] <- var_raw - - return(col) } + + # Apply missing codes + values <- apply_missing_codes( + values = all_values, + category_assignments = all_assignments, + missing_code_map = missing_map + ) } -} -# --------------------- -create_vec <- function(length, range, type, seed) { - set.seed(seed) - if (type == "normal") { - vec <- rnorm(length, mean = mean(range), sd = diff(range)/10) # DISCUSSION: sd - vec[vec < range[1]] <- range[1] - vec[vec > range[2]] <- range[2] - } else if (type == "uniform") { - vec <- runif(length, min = range[1], max = range[2]) + # ========== STEP 3: Apply garbage data if specified in variables.csv ========== + + # Extract missing codes from missing_map (metadata-based) + missing_codes_vec <- NULL + if (exists("missing_map") && length(missing_map) > 0) { + # Flatten missing_map to get all numeric codes + missing_codes_vec <- unique(unlist(missing_map)) } - return(vec) + + values <- apply_garbage( + values = values, + var_row = var_row, + variable_type = "continuous", + missing_codes = missing_codes_vec, # Pass metadata-based missing codes + seed = NULL # Already set globally if needed + ) + + # ========== STEP 4: Apply rType coercion if specified ========== + + # Read rType from var_row (variables.csv) + if ("rType" %in% names(var_row)) { + r_type <- var_row$rType + if (!is.null(r_type) && !is.na(r_type) && r_type != "") { + values <- switch(r_type, + "integer" = as.integer(round(values)), + "double" = as.double(values), + values # No coercion for other types + ) + } + } + + # ========== RETURN AS DATA FRAME ========== + + col <- data.frame( + new = values, + stringsAsFactors = FALSE + ) + names(col)[1] <- var + + return(col) } diff --git a/R/create_date_var.R b/R/create_date_var.R new file mode 100644 index 0000000..e94ef72 --- /dev/null +++ b/R/create_date_var.R @@ -0,0 +1,493 @@ +#' Create date variable for MockData +#' +#' Generates a date mock variable based on specifications from metadata. +#' +#' @param var character. Variable name to generate (column name in output) +#' @param databaseStart character. Database/cycle identifier for filtering metadata +#' (e.g., "cchs2001_p", "minimal-example"). Used to filter variables and +#' variable_details to the specified database. +#' @param variables data.frame or character. Variable-level metadata containing: +#' \itemize{ +#' \item \code{variable}: Variable names +#' \item \code{database}: Database identifier (optional, for filtering) +#' \item \code{sourceFormat}: Output format ("analysis"/"csv"/"sas") +#' \item \code{distribution}: Distribution type (uniform/gompertz/exponential) +#' \item \code{followup_min}, \code{followup_max}: Followup period parameters +#' \item \code{event_prop}: Proportion experiencing event +#' \item \code{garbage_high_prop}, \code{garbage_high_range}: Garbage data parameters +#' } +#' Can also be a file path (character) to variables.csv. +#' @param variable_details data.frame or character. Detail-level metadata containing: +#' \itemize{ +#' \item \code{variable}: Variable name (for joining) +#' \item \code{recStart}: Date range (e.g., [01JAN2001,31DEC2020]) or followup period +#' \item \code{recEnd}: Classification (copy, NA::a, NA::b) +#' \item \code{proportion}: Category proportion for missing codes +#' } +#' Can also be a file path (character) to variable_details.csv. +#' @param df_mock data.frame. Optional. Existing mock data (to check if variable already exists). +#' For survival variables, may contain anchor_date column for computing event dates. +#' @param prop_missing numeric. Proportion of missing values (0-1). Default 0 (no missing). +#' @param n integer. Number of observations to generate. +#' @param seed integer. Optional. Random seed for reproducibility. +#' +#' @return data.frame with one column (the generated date variable), or NULL if: +#' \itemize{ +#' \item Variable not found in metadata +#' \item Variable already exists in df_mock +#' \item No valid date range found in variable_details +#' } +#' +#' @details +#' **v0.3.0 API**: This function now accepts full metadata data frames and filters +#' internally for the specified variable and database. This is the "recodeflow pattern" +#' where filtering is handled inside the function. +#' +#' **Generation process**: +#' \enumerate{ +#' \item Filter metadata: Extract rows for specified var + database +#' \item Extract date parameters: Read from variables.csv and variable_details +#' \item Generate population: Based on distribution type (uniform/gompertz/exponential) +#' \item Apply missing codes: If proportions specified in metadata +#' \item Apply garbage: Read garbage parameters from variables.csv +#' \item Apply sourceFormat: Convert to specified format (analysis/csv/sas) +#' } +#' +#' **Output format (sourceFormat)**: +#' The sourceFormat column in variables.csv controls output data type: +#' \itemize{ +#' \item \code{"analysis"}: R Date objects (default) +#' \item \code{"csv"}: Character ISO strings (e.g., "2001-01-15") +#' \item \code{"sas"}: Numeric days since 1960-01-01 +#' } +#' +#' **Distribution types**: +#' \itemize{ +#' \item \code{"uniform"}: Uniform distribution over date range +#' \item \code{"gompertz"}: Gompertz survival distribution (for time-to-event data) +#' \item \code{"exponential"}: Exponential distribution (events concentrated near start) +#' } +#' +#' **Survival data generation**: +#' For variables with followup_min/followup_max/event_prop in variables.csv: +#' \itemize{ +#' \item Requires anchor_date column in df_mock (cohort entry/baseline date) +#' \item Generates event times within followup window +#' \item event_prop controls proportion experiencing event (vs. censored) +#' \item Distribution controls event timing (Gompertz typical for survival) +#' } +#' +#' **Missing data**: +#' Missing codes are identified by recEnd containing "NA::": +#' \itemize{ +#' \item \code{NA::a}: Skip codes (not applicable) +#' \item \code{NA::b}: Missing codes (don't know, refusal, not stated) +#' } +#' +#' **Garbage data**: +#' Garbage parameters are read from variables.csv: +#' \itemize{ +#' \item \code{garbage_high_prop}, \code{garbage_high_range}: Future dates (temporal violations) +#' } +#' +#' @examples +#' \dontrun{ +#' # Basic usage with metadata data frames +#' interview_date <- create_date_var( +#' var = "interview_date", +#' databaseStart = "minimal-example", +#' variables = variables, +#' variable_details = variable_details, +#' n = 1000, +#' seed = 123 +#' ) +#' +#' # Expected output: data.frame with 1000 rows, 1 column ("interview_date") +#' # Values: R Date objects (if sourceFormat="analysis" in metadata) +#' # Distribution: Based on distribution in metadata (uniform/gompertz) +#' +#' # Survival data generation (requires anchor_date in df_mock) +#' death_date <- create_date_var( +#' var = "death_date", +#' databaseStart = "minimal-example", +#' variables = variables, +#' variable_details = variable_details, +#' df_mock = df_mock, # Must contain anchor_date column +#' n = 1000, +#' seed = 456 +#' ) +#' } +#' +#' @family generators +#' @export +create_date_var <- function(var, + databaseStart, + variables, + variable_details, + df_mock = NULL, + prop_missing = 0, + n, + seed = NULL) { + + # ========== PARAMETER VALIDATION ========== + + # Load metadata from file paths if needed + if (is.character(variables) && length(variables) == 1) { + variables <- read.csv(variables, stringsAsFactors = FALSE, check.names = FALSE) + } + if (is.character(variable_details) && length(variable_details) == 1) { + variable_details <- read.csv(variable_details, stringsAsFactors = FALSE, check.names = FALSE) + } + + # ========== INTERNAL FILTERING (recodeflow pattern) ========== + + # Filter variables for this var + var_row <- variables[variables$variable == var, ] + + if (nrow(var_row) == 0) { + warning(paste0("Variable '", var, "' not found in variables metadata")) + return(NULL) + } + + # Take first row if multiple matches + if (nrow(var_row) > 1) { + var_row <- var_row[1, ] + } + + # Filter variable_details for this var AND database (using databaseStart) + # databaseStart is a recodeflow core column containing comma-separated database identifiers + if ("databaseStart" %in% names(variable_details)) { + details_subset <- variable_details[ + variable_details$variable == var & + (is.na(variable_details$databaseStart) | + variable_details$databaseStart == "" | + grepl(databaseStart, variable_details$databaseStart, fixed = TRUE)), + ] + } else { + # Fallback: no databaseStart filtering (for simple configs) + details_subset <- variable_details[variable_details$variable == var, ] + } + + # ========== CHECK IF VARIABLE ALREADY EXISTS ========== + + if (!is.null(df_mock) && var %in% names(df_mock)) { + return(NULL) + } + + # ========== SET SEED ========== + + if (!is.null(seed)) set.seed(seed) + + # ========== EXTRACT PARAMETERS FROM METADATA ========== + + # Extract sourceFormat from variables.csv (controls output type) + source_format <- if ("sourceFormat" %in% names(var_row) && !is.na(var_row$sourceFormat)) { + var_row$sourceFormat + } else { + "analysis" # default: R Date objects + } + + # Extract distribution from variables.csv + distribution_type <- if ("distribution" %in% names(var_row) && !is.na(var_row$distribution)) { + var_row$distribution + } else { + "uniform" # default + } + + # Check if this is a survival variable (has followup parameters) + is_survival <- "followup_min" %in% names(var_row) && + "followup_max" %in% names(var_row) && + "event_prop" %in% names(var_row) && + !is.na(var_row$followup_min) && var_row$followup_min != "" && + !is.na(var_row$followup_max) && var_row$followup_max != "" && + !is.na(var_row$event_prop) && var_row$event_prop != "" + + # ========== FALLBACK MODE: Default date range if no details ========== + + if (nrow(details_subset) == 0) { + # Default range: 2000-01-01 to 2025-12-31 + date_start <- as.Date("2000-01-01") + date_end <- as.Date("2025-12-31") + + values <- sample(seq(date_start, date_end, by = "day"), size = n, replace = TRUE) + + # Apply source format conversion + values <- convert_date_format(values, source_format) + + col <- data.frame( + new = values, + stringsAsFactors = FALSE + ) + names(col)[1] <- var + return(col) + } + + # ========== EXTRACT DATE RANGE FROM variable_details ========== + + # For survival variables, use followup period from variables.csv + # For calendar date variables, parse from variable_details recStart + + if (is_survival) { + # ========== SURVIVAL DATA GENERATION ========== + + # Check for anchor_date in df_mock + if (is.null(df_mock) || !"anchor_date" %in% names(df_mock)) { + warning(paste0( + "Variable '", var, "' is a survival variable (has followup_min/max/event_prop), ", + "but df_mock does not contain 'anchor_date' column. ", + "Cannot generate survival dates without anchor dates." + )) + return(NULL) + } + + if (nrow(df_mock) != n) { + warning(paste0( + "Variable '", var, "': df_mock has ", nrow(df_mock), " rows but n=", n, ". ", + "For survival variables, df_mock row count must match n." + )) + return(NULL) + } + + # Extract followup parameters + followup_min <- as.numeric(var_row$followup_min) # days + followup_max <- as.numeric(var_row$followup_max) # days + event_prop <- as.numeric(var_row$event_prop) # proportion + + if (is.na(followup_min) || is.na(followup_max) || is.na(event_prop)) { + warning(paste0( + "Variable '", var, "': followup_min, followup_max, or event_prop is NA. ", + "Cannot generate survival dates." + )) + return(NULL) + } + + # Extract anchor dates from df_mock + anchor_dates <- as.Date(df_mock$anchor_date) + + if (any(is.na(anchor_dates))) { + warning(paste0( + "Variable '", var, "': Some anchor_date values are NA. ", + "Cannot compute event dates." + )) + return(NULL) + } + + # Generate event times using specified distribution + # Extract proportions to determine events vs. censored + props <- extract_proportions(details_subset, variable_name = var) + n_valid <- floor(n * props$valid) + n_events <- floor(n_valid * event_prop) + n_censored <- n_valid - n_events + + # Create event indicator (TRUE = event occurs, FALSE = censored) + is_event <- c(rep(TRUE, n_events), rep(FALSE, n_censored)) + + # Shuffle event indicator to randomize which observations get events + shuffled_indices <- sample(n_valid) + is_event <- is_event[shuffled_indices] + + # Generate event times only for events (in days from anchor) + if (n_events > 0) { + if (distribution_type == "gompertz") { + # Gompertz distribution: typical for survival/mortality + shape <- if ("shape" %in% names(var_row) && !is.na(var_row$shape)) { + as.numeric(var_row$shape) + } else { + 0.1 # default shape parameter + } + + rate <- if ("rate" %in% names(var_row) && !is.na(var_row$rate)) { + as.numeric(var_row$rate) + } else { + 0.0001 # default rate parameter + } + + # Generate Gompertz-distributed event times + u <- runif(n_events) + event_times_days <- (1/shape) * log(1 - (shape/rate) * log(1 - u)) + event_times_days <- pmax(followup_min, pmin(followup_max, event_times_days)) + + } else if (distribution_type == "exponential") { + # Exponential distribution: constant hazard + rate_exp <- 1 / ((followup_max - followup_min) / 3) + event_times_days <- rexp(n_events, rate = rate_exp) + followup_min + event_times_days <- pmin(event_times_days, followup_max) + + } else { + # Uniform distribution (default) + event_times_days <- runif(n_events, min = followup_min, max = followup_max) + } + } else { + event_times_days <- numeric(0) + } + + # Initialize all dates as NA + event_dates <- rep(as.Date(NA), n_valid) + + # Assign dates only to observations with events + if (n_events > 0) { + anchor_dates_valid <- anchor_dates[seq_len(n_valid)] + event_dates[is_event] <- anchor_dates_valid[is_event] + event_times_days + } + + # Create all_assignments for missing code application + all_assignments <- rep("valid", n) + + } else { + # ========== CALENDAR DATE GENERATION ========== + + # Parse date range from variable_details recStart + # Format: [01JAN2001,31DEC2020] or similar + if ("recEnd" %in% names(details_subset)) { + # Filter out rows where recEnd contains "NA" (missing data codes) + rec_start_values <- details_subset$recStart[ + !grepl("NA", details_subset$recEnd, fixed = TRUE) + ] + } else { + # No recEnd column - use all recStart values (for simple configs) + rec_start_values <- details_subset$recStart + } + + if (length(rec_start_values) == 0) { + warning(paste0("Variable '", var, "': No valid date range found in variable_details")) + return(NULL) + } + + # Use parse_range_notation() to parse date ranges (supports inf for fixed dates) + parsed_range <- parse_range_notation(rec_start_values[1], range_type = "date") + + if (is.null(parsed_range) || parsed_range$type != "date") { + warning(paste0( + "Variable '", var, "': Cannot parse date range from recStart. ", + "Expected format: [01JAN2001,31DEC2020], [2001-01-01,2020-12-31], or [2017-03-31,inf]" + )) + return(NULL) + } + + date_start <- parsed_range$min + date_end <- parsed_range$max + + # Handle infinity case (fixed date): [2017-03-31,inf] means all dates = 2017-03-31 + is_fixed_date <- is.infinite(date_end) + + # Generate dates based on distribution + props <- extract_proportions(details_subset, variable_name = var) + n_valid <- floor(n * props$valid) + + if (is_fixed_date) { + # Fixed date (inf pattern): all dates are the same + event_dates <- rep(date_start, n_valid) + + } else if (distribution_type == "uniform") { + # Uniform distribution over date range + valid_dates <- seq(date_start, date_end, by = "day") + event_dates <- sample(valid_dates, size = n_valid, replace = TRUE) + + } else if (distribution_type == "exponential") { + # Exponential: more dates near start + n_days <- as.numeric(difftime(date_end, date_start, units = "days")) + rate_exp <- 1 / (n_days / 3) + days_from_start <- rexp(n_valid, rate = rate_exp) + days_from_start <- pmin(days_from_start, n_days) + event_dates <- date_start + days_from_start + + } else { + # Gompertz or other: default to uniform for calendar dates + valid_dates <- seq(date_start, date_end, by = "day") + event_dates <- sample(valid_dates, size = n_valid, replace = TRUE) + } + } + + # ========== STEP 2: Apply missing codes ========== + + n_missing <- n - length(event_dates) + + if (n_missing > 0 && length(props$missing) > 0) { + # Generate missing assignments + missing_assignments <- sample( + names(props$missing), + size = n_missing, + replace = TRUE, + prob = unlist(props$missing) + ) + + # For dates, missing codes are typically NA + # Create placeholder values for missing + missing_values <- rep(as.Date(NA), n_missing) + + # Combine valid and missing + all_values <- c(event_dates, missing_values) + all_assignments <- c(rep("valid", length(event_dates)), missing_assignments) + + # Apply missing codes (for dates, this typically sets to NA) + # But we'll use apply_missing_codes for consistency + missing_map <- list() + for (miss_cat in names(props$missing)) { + # For dates, missing codes are R NA + missing_map[[miss_cat]] <- as.Date(NA) + } + + values <- apply_missing_codes( + values = all_values, + category_assignments = all_assignments, + missing_code_map = missing_map + ) + } else { + # No missing codes needed + values <- event_dates + } + + # ========== STEP 3: Apply garbage data if specified in variables.csv ========== + + # Convert to character temporarily for apply_garbage + # (apply_garbage may work with dates, but safer to handle explicitly) + values_char <- as.character(values) + + # Extract missing codes from missing_map (metadata-based) + # For dates, missing codes are typically NA (not numeric codes like 997) + missing_codes_vec <- NULL + if (exists("missing_map") && length(missing_map) > 0) { + # Flatten missing_map - will be NA for dates, but pass it anyway + missing_codes_vec <- unique(as.character(unlist(missing_map))) + } + + values_char <- apply_garbage( + values = values_char, + var_row = var_row, + variable_type = "date", + missing_codes = missing_codes_vec, # Pass metadata-based missing codes + seed = NULL # Already set globally if needed + ) + + # Convert back to Date + values <- as.Date(values_char) + + # ========== STEP 4: Apply sourceFormat conversion ========== + + values <- convert_date_format(values, source_format) + + # ========== RETURN AS DATA FRAME ========== + + col <- data.frame( + new = values, + stringsAsFactors = FALSE + ) + names(col)[1] <- var + + return(col) +} + +# Helper function to convert dates to specified source format +convert_date_format <- function(date_vector, format) { + if (format == "csv") { + # CSV format: character ISO strings (e.g., "2001-01-15") + return(as.character(date_vector)) + } else if (format == "sas") { + # SAS format: numeric days since 1960-01-01 + sas_epoch <- as.Date("1960-01-01") + return(as.numeric(date_vector - sas_epoch)) + } else { + # "analysis" or default: keep as R Date objects + return(date_vector) + } +} diff --git a/R/create_mock_data.R b/R/create_mock_data.R new file mode 100644 index 0000000..893c97c --- /dev/null +++ b/R/create_mock_data.R @@ -0,0 +1,336 @@ +#' Create mock data from configuration files +#' +#' @description +#' Main orchestrator function that generates complete mock datasets from +#' configuration files. Reads metadata, filters for enabled variables, +#' dispatches to type-specific create_* functions, and assembles results +#' into a complete data frame. +#' +#' @param databaseStart Character. The database identifier (e.g., "cchs2001_p", "minimal-example"). +#' Used to filter variables to those available in the specified database. +#' @param variables data.frame or character. Variable-level metadata containing: +#' \itemize{ +#' \item \code{variable}: Variable names +#' \item \code{variableType}: Variable type (Categorical/Continuous/Date) +#' \item \code{role}: Role tags (enabled, predictor, outcome, etc.) +#' \item \code{position}: Display order (optional) +#' \item \code{database}: Database filter (optional) +#' } +#' Can also be a file path (character) to variables.csv. +#' @param variable_details data.frame or character. Detail-level metadata containing: +#' \itemize{ +#' \item \code{variable}: Variable name (for joining) +#' \item \code{recStart}: Category code/range or date interval +#' \item \code{recEnd}: Classification (numeric code, "NA::a", "NA::b") +#' \item \code{proportion}: Category proportion (for categorical) +#' \item \code{catLabel}: Category label/description +#' } +#' Can also be a file path (character) to variable_details.csv. +#' If NULL, uses fallback mode (uniform distributions). +#' @param n Integer. Number of observations to generate (default 1000). +#' @param seed Integer. Optional random seed for reproducibility. +#' @param validate Logical. Whether to validate configuration files (default TRUE). +#' @param verbose Logical. Whether to print progress messages (default FALSE). +#' +#' @return Data frame with n rows and one column per enabled variable. +#' +#' @details +#' **v0.3.0 API**: This function now follows the "recodeflow pattern" where it passes +#' full metadata data frames to create_* functions, which handle internal filtering. +#' +#' **Generation process**: +#' \enumerate{ +#' \item Load metadata from file paths or accept data frames +#' \item Filter for enabled variables (role contains "enabled") +#' \item Set global seed (if provided) +#' \item Loop through variables in position order: +#' - Dispatch to create_cat_var, create_con_var, or create_date_var +#' - Pass full metadata data frames (functions filter internally) +#' - Merge result into data frame +#' \item Return complete dataset +#' } +#' +#' **Fallback mode**: If variable_details = NULL, uses uniform distributions for all +#' enabled variables. +#' +#' **Variable types supported**: +#' \itemize{ +#' \item \code{Categorical}: create_cat_var() +#' \item \code{Continuous}: create_con_var() +#' \item \code{Date}: create_date_var() +#' } +#' +#' **Configuration schema**: For complete documentation of all configuration columns, +#' see \code{vignette("reference-config", package = "MockData")}. +#' +#' @examples +#' \dontrun{ +#' # Basic usage with file paths +#' mock_data <- create_mock_data( +#' databaseStart = "minimal-example", +#' variables = "inst/extdata/minimal-example/variables.csv", +#' variable_details = "inst/extdata/minimal-example/variable_details.csv", +#' n = 1000, +#' seed = 123 +#' ) +#' +#' # With data frames instead of file paths +#' variables <- read.csv("inst/extdata/minimal-example/variables.csv", +#' stringsAsFactors = FALSE) +#' variable_details <- read.csv("inst/extdata/minimal-example/variable_details.csv", +#' stringsAsFactors = FALSE) +#' +#' mock_data <- create_mock_data( +#' databaseStart = "minimal-example", +#' variables = variables, +#' variable_details = variable_details, +#' n = 1000, +#' seed = 123 +#' ) +#' +#' # Fallback mode (uniform distributions, no variable_details) +#' mock_data <- create_mock_data( +#' databaseStart = "minimal-example", +#' variables = "inst/extdata/minimal-example/variables.csv", +#' variable_details = NULL, +#' n = 500 +#' ) +#' +#' # View structure +#' str(mock_data) +#' head(mock_data) +#' } +#' +#' @family generators +#' @export +create_mock_data <- function(databaseStart, + variables, + variable_details = NULL, + n = 1000, + seed = NULL, + validate = TRUE, + verbose = FALSE) { + + # ========== LOAD METADATA ========== + + # Load variables from file path if needed + if (is.character(variables) && length(variables) == 1) { + if (!file.exists(variables)) { + stop("Configuration file does not exist: ", variables) + } + if (verbose) message("Reading variables file: ", variables) + variables <- read.csv(variables, stringsAsFactors = FALSE, check.names = FALSE) + } + + # Load variable_details from file path if needed + if (!is.null(variable_details)) { + if (is.character(variable_details) && length(variable_details) == 1) { + if (!file.exists(variable_details)) { + stop("Details file does not exist: ", variable_details) + } + if (verbose) message("Reading variable_details file: ", variable_details) + variable_details <- read.csv(variable_details, stringsAsFactors = FALSE, check.names = FALSE) + } + } else { + if (verbose) message("No details file provided - using fallback mode (uniform distributions)") + } + + # ========== VALIDATE INPUT ========== + + if (n < 1) { + stop("n must be at least 1") + } + + if (!"variable" %in% names(variables)) { + stop("variables must have a 'variable' column") + } + + if (!"variableType" %in% names(variables)) { + stop("variables must have a 'variableType' column") + } + + # ========== FILTER FOR ENABLED VARIABLES ========== + + if (verbose) message("Filtering for enabled variables...") + + # Filter for variables with "enabled" in role column + if ("role" %in% names(variables)) { + enabled_vars <- variables[grepl("enabled", variables$role, ignore.case = TRUE), ] + } else { + # If no role column, assume all variables are enabled + enabled_vars <- variables + } + + # Exclude derived variables (identified by DerivedVar:: and Func:: patterns) + if (!is.null(variable_details)) { + derived_vars <- identify_derived_vars(enabled_vars, variable_details) + + if (length(derived_vars) > 0) { + if (verbose) { + message("Excluding ", length(derived_vars), " derived variable(s): ", + paste(derived_vars, collapse = ", ")) + } + + # Filter out derived variables + enabled_vars <- enabled_vars[!enabled_vars$variable %in% derived_vars, ] + } + } + + if (nrow(enabled_vars) == 0) { + stop("No enabled non-derived variables found in configuration. ", + "Add 'enabled' to the role column for variables you want to generate, ", + "or ensure derived variables have raw dependencies.") + } + + # NOTE: Database filtering now happens at detail-level (in create_* functions) + # using the databaseStart column in variable_details.csv (recodeflow core pattern) + + # Sort by position if available + if ("position" %in% names(enabled_vars) && any(!is.na(enabled_vars$position))) { + enabled_vars <- enabled_vars[order(enabled_vars$position), ] + } + + if (verbose) { + message("Found ", nrow(enabled_vars), " enabled variable(s) for database '", databaseStart, "': ", + paste(enabled_vars$variable, collapse = ", ")) + } + + # ========== SET GLOBAL SEED ========== + + if (!is.null(seed)) { + if (verbose) message("Setting random seed: ", seed) + set.seed(seed) + } + + # ========== GENERATE VARIABLES ========== + + if (verbose) message("Generating ", n, " observations...") + + # Initialize empty data frame + df_mock <- data.frame(row.names = seq_len(n)) + + # Generate variables in order + for (i in seq_len(nrow(enabled_vars))) { + var_row <- enabled_vars[i, ] + var_name <- var_row$variable + + # Determine variable type for routing using rType (v0.2 schema) + if ("rType" %in% names(var_row) && !is.na(var_row$rType) && var_row$rType != "") { + var_type <- tolower(var_row$rType) + } else { + stop("Variable '", var_name, "' is missing rType column. ", + "All metadata must use v0.2 schema with rType column.") + } + + if (verbose) { + message(" [", i, "/", nrow(enabled_vars), "] Generating ", + var_name, " (", var_type, ")") + } + + # Dispatch to type-specific generator + var_data <- tryCatch({ + switch(var_type, + # v0.2 schema rType values + "factor" = create_cat_var( + var = var_name, + databaseStart = databaseStart, + variables = variables, + variable_details = variable_details, + df_mock = df_mock, + n = n, + seed = NULL # Global seed already set + ), + "character" = create_cat_var( + var = var_name, + databaseStart = databaseStart, + variables = variables, + variable_details = variable_details, + df_mock = df_mock, + n = n, + seed = NULL + ), + "integer" = create_con_var( + var = var_name, + databaseStart = databaseStart, + variables = variables, + variable_details = variable_details, + df_mock = df_mock, + n = n, + seed = NULL + ), + "double" = create_con_var( + var = var_name, + databaseStart = databaseStart, + variables = variables, + variable_details = variable_details, + df_mock = df_mock, + n = n, + seed = NULL + ), + "numeric" = create_con_var( + var = var_name, + databaseStart = databaseStart, + variables = variables, + variable_details = variable_details, + df_mock = df_mock, + n = n, + seed = NULL + ), + "date" = create_date_var( + var = var_name, + databaseStart = databaseStart, + variables = variables, + variable_details = variable_details, + df_mock = df_mock, + n = n, + seed = NULL + ), + # Legacy variableType values (if somehow still used) + "categorical" = create_cat_var( + var = var_name, + databaseStart = databaseStart, + variables = variables, + variable_details = variable_details, + df_mock = df_mock, + n = n, + seed = NULL + ), + "continuous" = create_con_var( + var = var_name, + databaseStart = databaseStart, + variables = variables, + variable_details = variable_details, + df_mock = df_mock, + n = n, + seed = NULL + ), + { + warning("Unknown variable type '", var_type, "' for variable: ", var_name, + "\n Supported rType values: factor, character, integer, double, numeric, date") + NULL + } + ) + }, error = function(e) { + warning("Error generating variable ", var_name, ": ", e$message) + NULL + }) + + # Merge into dataset if generation succeeded + if (!is.null(var_data) && is.data.frame(var_data)) { + # Add columns from var_data to df_mock + for (col_name in names(var_data)) { + df_mock[[col_name]] <- var_data[[col_name]] + } + } + } + + # ========== RETURN RESULT ========== + + if (verbose) { + message("Mock data generation complete!") + message(" Rows: ", nrow(df_mock)) + message(" Variables: ", ncol(df_mock)) + } + + return(df_mock) +} diff --git a/R/create_survival_dates.R b/R/create_survival_dates.R new file mode 100644 index 0000000..1a6672b --- /dev/null +++ b/R/create_survival_dates.R @@ -0,0 +1,388 @@ +#' Create paired survival dates for cohort studies +#' +#' Generates entry and event dates with guaranteed temporal ordering (entry < event). +#' Useful for survival analysis, cohort studies, and time-to-event modeling. +#' +#' **Configuration v0.2 format (NEW):** +#' @param entry_var_row data.frame. Single row from mock_data_config for entry date variable +#' @param entry_details_subset data.frame. Rows from mock_data_config_details for entry date +#' @param event_var_row data.frame. Single row from mock_data_config for event date variable +#' @param event_details_subset data.frame. Rows from mock_data_config_details for event date +#' @param n integer. Number of observations to generate +#' @param seed integer. Random seed for reproducibility. If NULL, uses global seed. +#' @param df_mock data.frame. The current mock data (to check if variables already exist) +#' +#' **Configuration v0.1 format (LEGACY):** +#' @param entry_var character. Name for entry date variable +#' @param event_var character. Name for event date variable +#' @param entry_start Date. Start of entry period +#' @param entry_end Date. End of entry period +#' @param followup_min integer. Minimum follow-up days +#' @param followup_max integer. Maximum follow-up days +#' @param length integer. Number of records to generate +#' @param event_distribution character. Distribution for time-to-event: "uniform", "gompertz", "exponential" +#' @param prop_censored numeric. Proportion of records to censor (0-1) +#' @param prop_NA numeric. Proportion of missing values (0-1) +#' @param prop_invalid numeric. Optional. Proportion of temporal violations (entry > event) (0 to 1). If NULL, no invalid dates generated. +#' +#' @return data.frame with entry_date, event_date, and optionally event_status columns, or NULL if: +#' - Variables already exist in df_mock +#' - Missing required configuration +#' +#' @details +#' **v0.2 format (NEW):** +#' - Extracts date ranges from entry_details_subset and event_details_subset +#' - Generates entry dates uniformly distributed +#' - Calculates event dates to ensure entry < event +#' - Supports garbage data via `catLabel::garbage` in event_details_subset +#' - Supports fallback mode: reasonable defaults when details_subset is NULL +#' +#' **v0.1 format (LEGACY):** +#' - Accepts explicit date ranges and follow-up parameters +#' - Supports multiple event distributions (uniform, gompertz, exponential) +#' - Handles censoring, missing values, and temporal violations via parameters +#' +#' The function auto-detects which format based on parameter names. +#' +#' This function generates realistic survival data by: +#' 1. Creating entry dates uniformly distributed across entry period +#' 2. Generating follow-up times using specified distribution +#' 3. Calculating event dates (entry + follow-up) +#' 4. Optionally censoring events (event_status = 0) +#' 5. Ensuring entry_date < event_date for all records +#' +#' **Event distributions:** +#' - "uniform": Constant hazard over follow-up period +#' - "gompertz": Increasing hazard (mortality increases with time) +#' - "exponential": Decreasing hazard (early events more common) +#' +#' **Censoring:** +#' When prop_censored > 0, generates event_status column: +#' - 1 = event observed +#' - 0 = censored (event_date becomes censoring date) +#' +#' @examples +#' \dontrun{ +#' # v0.2 format - called by create_mock_data() +#' config <- read_mock_data_config("mock_data_config.csv") +#' details <- read_mock_data_config_details("mock_data_config_details.csv") +#' entry_row <- config[config$variable == "study_entry", ] +#' entry_details <- get_variable_details(details, variable_name = "study_entry") +#' event_row <- config[config$variable == "death_date", ] +#' event_details <- get_variable_details(details, variable_name = "death_date") +#' surv_data <- create_survival_dates( +#' entry_var_row = entry_row, +#' entry_details_subset = entry_details, +#' event_var_row = event_row, +#' event_details_subset = event_details, +#' n = 1000, +#' seed = 123 +#' ) +#' +#' # v0.2 with garbage (catLabel::garbage in config_details) +#' # In mock_data_config_details.csv: +#' # variable,recEnd,catLabel,proportion +#' # death_date,followup_min,, +#' # death_date,followup_max,, +#' # death_date,garbage,garbage,0.03 +#' event_details_with_garbage <- get_variable_details(details, variable_name = "death_date") +#' surv_data_garbage <- create_survival_dates( +#' entry_var_row = entry_row, +#' entry_details_subset = entry_details, +#' event_var_row = event_row, +#' event_details_subset = event_details_with_garbage, +#' n = 1000, +#' seed = 123 +#' ) +#' +#' # v0.1 format (legacy) - Basic mortality study +#' surv_data <- create_survival_dates( +#' entry_var = "study_entry", +#' event_var = "death_date", +#' entry_start = as.Date("2000-01-01"), +#' entry_end = as.Date("2005-12-31"), +#' followup_min = 365, +#' followup_max = 3650, +#' length = 1000, +#' df_mock = data.frame(), +#' event_distribution = "gompertz" +#' ) +#' +#' # v0.1 with censoring +#' surv_data <- create_survival_dates( +#' entry_var = "cohort_entry", +#' event_var = "event_date", +#' entry_start = as.Date("2010-01-01"), +#' entry_end = as.Date("2015-12-31"), +#' followup_min = 30, +#' followup_max = 1825, +#' length = 500, +#' df_mock = data.frame(), +#' event_distribution = "exponential", +#' prop_censored = 0.3 +#' ) +#' +#' # v0.1 with temporal violations for validation testing +#' surv_data <- create_survival_dates( +#' entry_var = "interview_date", +#' event_var = "death_date", +#' entry_start = as.Date("2015-01-01"), +#' entry_end = as.Date("2016-12-31"), +#' followup_min = 30, +#' followup_max = 3650, +#' length = 1000, +#' df_mock = data.frame(), +#' prop_invalid = 0.03 # 3% temporal violations +#' ) +#' } +#' +#' @family generators +#' @export +create_survival_dates <- function(entry_var_row = NULL, entry_details_subset = NULL, + event_var_row = NULL, event_details_subset = NULL, + n = NULL, seed = NULL, df_mock = NULL, + # v0.1 legacy parameters + entry_var = NULL, event_var = NULL, + entry_start = NULL, entry_end = NULL, + followup_min = NULL, followup_max = NULL, + length = NULL, + event_distribution = "uniform", + prop_censored = 0, + prop_NA = NULL, + prop_invalid = NULL) { + + # Auto-detect format based on parameters + use_v02 <- !is.null(entry_var_row) && is.data.frame(entry_var_row) && nrow(entry_var_row) == 1 && + !is.null(event_var_row) && is.data.frame(event_var_row) && nrow(event_var_row) == 1 + + if (use_v02) { + # ========== v0.2 IMPLEMENTATION ========== + entry_var_name <- entry_var_row$variable + event_var_name <- event_var_row$variable + + # Check if variables already exist in mock data + if (!is.null(df_mock) && (entry_var_name %in% names(df_mock) || event_var_name %in% names(df_mock))) { + return(NULL) + } + + # Set seed if provided + if (!is.null(seed)) set.seed(seed) + + # FALLBACK MODE: Default ranges if details_subset is NULL + if (is.null(entry_details_subset) || nrow(entry_details_subset) == 0) { + entry_start <- as.Date("2000-01-01") + entry_end <- as.Date("2005-12-31") + } else { + # Extract date_start and date_end from entry_details_subset + date_start_row <- entry_details_subset[entry_details_subset$recEnd == "date_start", ] + date_end_row <- entry_details_subset[entry_details_subset$recEnd == "date_end", ] + + if (nrow(date_start_row) == 0 || nrow(date_end_row) == 0) { + warning(paste0("Missing date_start or date_end for ", entry_var_name, ". Using defaults.")) + entry_start <- as.Date("2000-01-01") + entry_end <- as.Date("2005-12-31") + } else { + entry_start <- as.Date(date_start_row$date_start[1]) + entry_end <- as.Date(date_end_row$date_end[1]) + + if (is.na(entry_start) || is.na(entry_end)) { + warning(paste0("Invalid date_start or date_end for ", entry_var_name, ". Using defaults.")) + entry_start <- as.Date("2000-01-01") + entry_end <- as.Date("2005-12-31") + } + } + } + + # For event dates, extract follow-up range if available + if (is.null(event_details_subset) || nrow(event_details_subset) == 0) { + # Default: 1-10 years follow-up + followup_min <- 365 + followup_max <- 3650 + } else { + # Look for followup_min and followup_max in details_subset + followup_min_row <- event_details_subset[event_details_subset$recEnd == "followup_min", ] + followup_max_row <- event_details_subset[event_details_subset$recEnd == "followup_max", ] + + if (nrow(followup_min_row) > 0 && nrow(followup_max_row) > 0) { + followup_min <- as.numeric(followup_min_row$value[1]) + followup_max <- as.numeric(followup_max_row$value[1]) + + if (is.na(followup_min) || is.na(followup_max)) { + warning(paste0("Invalid followup range for ", event_var_name, ". Using defaults.")) + followup_min <- 365 + followup_max <- 3650 + } + } else { + # Fallback: 1-10 years + followup_min <- 365 + followup_max <- 3650 + } + } + + # Generate entry dates (uniform distribution) + entry_range_days <- as.numeric(entry_end - entry_start) + entry_days <- sample(0:entry_range_days, n, replace = TRUE) + entry_dates <- entry_start + entry_days + + # Generate follow-up times (uniform distribution for v0.2) + followup_days <- sample(followup_min:followup_max, n, replace = TRUE) + + # Calculate event dates + event_dates <- entry_dates + round(followup_days) + + # Create result data frame + result <- data.frame( + entry = entry_dates, + event = event_dates, + stringsAsFactors = FALSE + ) + + # Apply garbage if specified in event_details_subset (catLabel::garbage) + if (!is.null(event_details_subset) && nrow(event_details_subset) > 0) { + # Check for garbage rows + has_garbage <- any(!is.na(event_details_subset$catLabel) & + event_details_subset$catLabel == "garbage") + + if (has_garbage) { + garbage_row <- event_details_subset[!is.na(event_details_subset$catLabel) & + event_details_subset$catLabel == "garbage", ] + + if (nrow(garbage_row) > 0 && !is.na(garbage_row$proportion[1])) { + prop_invalid <- garbage_row$proportion[1] + + if (prop_invalid > 0) { + n_invalid <- floor(n * prop_invalid) + invalid_indices <- sample(1:n, n_invalid, replace = FALSE) + + # Swap entry and event dates to create temporal violations + for (idx in invalid_indices) { + temp <- result$entry[idx] + result$entry[idx] <- result$event[idx] + result$event[idx] <- temp + } + } + } + } + } + + # Rename columns to variable names + names(result)[1] <- entry_var_name + names(result)[2] <- event_var_name + + return(result) + + } else { + # ========== v0.1 LEGACY IMPLEMENTATION ========== + + # Validate inputs + if (!inherits(entry_start, "Date") || !inherits(entry_end, "Date")) { + stop("entry_start and entry_end must be Date objects") + } + if (entry_start >= entry_end) { + stop("entry_start must be before entry_end") + } + if (followup_min >= followup_max) { + stop("followup_min must be less than followup_max") + } + if (prop_censored < 0 || prop_censored > 1) { + stop("prop_censored must be between 0 and 1") + } + + # Check if variables already exist + if (entry_var %in% names(df_mock) || event_var %in% names(df_mock)) { + return(NULL) + } + + if (!is.null(seed)) set.seed(seed) + + # Generate entry dates (uniform distribution) + entry_range_days <- as.numeric(entry_end - entry_start) + entry_days <- sample(0:entry_range_days, length, replace = TRUE) + entry_dates <- entry_start + entry_days + + # Generate follow-up times based on distribution + if (event_distribution == "uniform") { + followup_days <- sample(followup_min:followup_max, length, replace = TRUE) + + } else if (event_distribution == "gompertz") { + # Gompertz: increasing hazard over time + # Use inverse transform sampling + u <- runif(length) + shape <- 0.1 + rate <- 0.01 + + # Scale to follow-up range + range_days <- followup_max - followup_min + gompertz_days <- (-1/rate) * log(1 - (rate/shape) * log(1 - u)) + + # Normalize to desired range + gompertz_days <- gompertz_days / max(gompertz_days, na.rm = TRUE) * range_days + followup_days <- pmax(followup_min, pmin(followup_max, followup_min + gompertz_days)) + + } else if (event_distribution == "exponential") { + # Exponential: early events more common + rate <- 3 / (followup_max - followup_min) + exp_days <- rexp(length, rate = rate) + followup_days <- pmax(followup_min, pmin(followup_max, followup_min + exp_days)) + + } else { + stop("event_distribution must be 'uniform', 'gompertz', or 'exponential'") + } + + # Calculate event dates + event_dates <- entry_dates + round(followup_days) + + # Create result data frame + result <- data.frame( + entry = entry_dates, + event = event_dates, + stringsAsFactors = FALSE + ) + + # Add censoring if requested + if (prop_censored > 0) { + n_censored <- floor(length * prop_censored) + censored_indices <- sample(1:length, n_censored, replace = FALSE) + + result$event_status <- 1 + result$event_status[censored_indices] <- 0 + + # For censored records, event_date becomes censoring date + # (administratively censored at random point in follow-up) + for (i in censored_indices) { + max_censor_days <- as.numeric(result$event[i] - result$entry[i]) + censor_days <- sample(followup_min:max_censor_days, 1) + result$event[i] <- result$entry[i] + censor_days + } + } + + # Add missing values if requested + if (!is.null(prop_NA) && prop_NA > 0) { + n_na <- floor(length * prop_NA) + na_indices <- sample(1:length, n_na, replace = FALSE) + + # Set both dates to NA for missing records + result$entry[na_indices] <- NA + result$event[na_indices] <- NA + } + + # Add temporal violations if requested (entry > event) + if (!is.null(prop_invalid) && prop_invalid > 0) { + n_invalid <- floor(length * prop_invalid) + invalid_indices <- sample(1:length, n_invalid, replace = FALSE) + + # Swap entry and event dates to create temporal violations + for (idx in invalid_indices) { + temp <- result$entry[idx] + result$entry[idx] <- result$event[idx] + result$event[idx] <- temp + } + } + + # Rename columns to user-specified names + names(result)[1] <- entry_var + names(result)[2] <- event_var + + return(result) + } +} diff --git a/R/create_wide_survival_data.R b/R/create_wide_survival_data.R new file mode 100644 index 0000000..a9cca30 --- /dev/null +++ b/R/create_wide_survival_data.R @@ -0,0 +1,359 @@ +#' Create wide survival data for cohort studies +#' +#' Generates wide-format survival data (one row per individual) with up to 5 date +#' variables (entry, event, death, loss-to-follow-up, administrative censoring). +#' Applies temporal ordering constraints and supports garbage data generation for +#' QA testing. +#' +#' @param var_entry_date character. Required. Variable name for entry date (baseline). +#' @param var_event_date character. Optional. Variable name for primary event date +#' (e.g., "dementia_incid_date"). Set to NULL to skip. +#' @param var_death_date character. Optional. Variable name for death date +#' (competing risk). Set to NULL to skip. +#' @param var_ltfu character. Optional. Variable name for loss-to-follow-up date. +#' Set to NULL to skip. +#' @param var_admin_censor character. Optional. Variable name for administrative +#' censoring date. Set to NULL to skip. +#' @param databaseStart character. Required. Database identifier for filtering metadata +#' (used with databaseStart column in variable_details). +#' @param variables data.frame. Required. Full variables metadata (not pre-filtered). +#' Must contain columns: variable, variableType. +#' @param variable_details data.frame. Required. Full variable details metadata +#' (not pre-filtered). Will be filtered internally using databaseStart column. +#' @param df_mock data.frame. Optional. The current mock data to check if variables +#' already exist and to use as anchor_date source. Default: NULL. +#' @param n integer. Required. Number of observations to generate. +#' @param seed integer. Optional. Random seed for reproducibility. Default: NULL. +#' @param prop_garbage numeric. **DEPRECATED in v0.3.1**. This parameter is no +#' longer supported. To generate temporal violations for QA testing, use the +#' `garbage_high_prop` and `garbage_high_range` parameters in variables.csv +#' for individual date variables. See Details section for migration guidance. +#' Default: NULL. +#' +#' @return data.frame with 1-5 date columns (depending on which variables are +#' specified), or NULL if variables already exist in df_mock. +#' +#' @details +#' This function implements v0.3.0 "recodeflow pattern" API: +#' - Accepts full metadata data frames (not pre-filtered subsets) +#' - Accepts variable names (not variable rows) +#' - Filters metadata internally using databaseStart column +#' +#' **Implementation strategy:** +#' 1. Call create_date_var() once for each non-NULL date variable +#' 2. Each variable configured separately in variables.csv with own event_prop, +#' distribution, followup_min, followup_max, etc. +#' 3. Combine results into single data frame +#' 4. Apply temporal ordering constraints +#' +#' **Temporal ordering constraints (normal mode):** +#' - Entry date is always baseline (earliest) +#' - All other dates must be >= entry_date +#' - Death can occur before any event +#' - If death < event, set event to NA (censored, not missing) +#' - Observation ends at min(event, death, ltfu, admin_censor) +#' +#' **Temporal violations for QA testing (v0.3.1+):** +#' This function creates clean, temporally-ordered survival data. To generate +#' temporal violations for testing data quality pipelines: +#' - Add `garbage_high_prop` and `garbage_high_range` to individual date variables +#' in variables.csv (e.g., future death dates beyond 2025) +#' - Use [create_date_var()] to generate date variables with garbage +#' - Test your temporal validation logic separately +#' - This approach separates concerns: date-level garbage vs. survival data generation +#' +#' **Migration from prop_garbage (deprecated in v0.3.1):** +#' ```r +#' # OLD (v0.3.0): +#' surv <- create_wide_survival_data(..., prop_garbage = 0.03) +#' +#' # NEW (v0.3.1+): +#' # Add garbage to date variables in metadata +#' variables$garbage_high_prop[variables$variable == "death_date"] <- 0.03 +#' variables$garbage_high_range[variables$variable == "death_date"] <- +#' "[2025-01-01, 2099-12-31]" +#' # create_date_var() will apply garbage automatically +#' surv <- create_wide_survival_data(..., variables = variables) +#' ``` +#' +#' **Configuration in metadata:** +#' Each date variable must be defined in variables.csv and variable_details.csv: +#' +#' variables.csv: +#' ``` +#' variable,variableType,role +#' interview_date,Date,enabled +#' dementia_incid_date,Date,enabled +#' death_date,Date,enabled +#' ``` +#' +#' variable_details.csv: +#' ``` +#' variable,recStart,recEnd,value,proportion +#' interview_date,[2001-01-01,2005-12-31],copy,NA,NA +#' dementia_incid_date,[2002-01-01,2021-01-01],followup_min,365,NA +#' dementia_incid_date,NA,followup_max,7300,NA +#' dementia_incid_date,NA,event_prop,0.15,NA +#' death_date,[2002-01-01,2026-01-01],followup_min,365,NA +#' death_date,NA,followup_max,9125,NA +#' death_date,NA,event_prop,0.40,NA +#' ``` +#' +#' @examples +#' \dontrun{ +#' # Read metadata +#' variables <- read.csv("inst/extdata/survival/variables.csv") +#' variable_details <- read.csv("inst/extdata/survival/variable_details.csv") +#' +#' # Generate 5-variable survival data +#' surv_data <- create_wide_survival_data( +#' var_entry_date = "interview_date", +#' var_event_date = "dementia_incid_date", +#' var_death_date = "death_date", +#' var_ltfu = "ltfu_date", +#' var_admin_censor = "admin_censor_date", +#' databaseStart = "demport", +#' variables = variables, +#' variable_details = variable_details, +#' n = 1000, +#' seed = 123 +#' ) +#' +#' # Generate minimal survival data (entry + event only) +#' surv_data <- create_wide_survival_data( +#' var_entry_date = "cohort_entry", +#' var_event_date = "primary_event_date", +#' var_death_date = NULL, +#' var_ltfu = NULL, +#' var_admin_censor = NULL, +#' database = "study", +#' variables = variables, +#' variable_details = variable_details, +#' n = 500, +#' seed = 456 +#' ) +#' +#' # Generate with garbage data for QA testing (v0.3.1+) +#' # Add garbage to death_date in metadata +#' vars_with_garbage <- add_garbage(variables, "death_date", +#' high_prop = 0.05, high_range = "[2025-01-01, 2099-12-31]") +#' +#' surv_data <- create_wide_survival_data( +#' var_entry_date = "interview_date", +#' var_event_date = "dementia_incid_date", +#' var_death_date = "death_date", +#' var_ltfu = NULL, +#' var_admin_censor = NULL, +#' databaseStart = "demport", +#' variables = vars_with_garbage, # Use modified metadata +#' variable_details = variable_details, +#' n = 1000, +#' seed = 789 +#' ) +#' } +#' +#' @family generators +#' @export +create_wide_survival_data <- function(var_entry_date, + var_event_date = NULL, + var_death_date = NULL, + var_ltfu = NULL, + var_admin_censor = NULL, + databaseStart, + variables, + variable_details, + df_mock = NULL, + n, + seed = NULL, + prop_garbage = NULL) { + + # ========== VALIDATION ========== + + # Check required parameters + if (missing(var_entry_date) || is.null(var_entry_date)) { + stop("var_entry_date is required (entry date is baseline for survival data)") + } + if (missing(databaseStart) || is.null(databaseStart)) { + stop("databaseStart parameter is required") + } + if (missing(variables) || !is.data.frame(variables)) { + stop("variables must be a data frame (full metadata, not pre-filtered)") + } + if (missing(variable_details) || !is.data.frame(variable_details)) { + stop("variable_details must be a data frame (full metadata, not pre-filtered)") + } + if (missing(n) || is.null(n) || !is.numeric(n) || n <= 0) { + stop("n must be a positive integer") + } + + # Deprecation warning for prop_garbage + if (!is.null(prop_garbage)) { + warning( + "The 'prop_garbage' parameter is deprecated as of v0.3.1 and will be ignored.\n", + "To generate temporal violations for QA testing:\n", + "1. Add garbage_high_prop and garbage_high_range to individual date variables in variables.csv\n", + "2. Example: variables$garbage_high_prop[variables$variable == 'death_date'] <- 0.03\n", + " variables$garbage_high_range[variables$variable == 'death_date'] <- '[2025-01-01, 2099-12-31]'\n", + "3. create_date_var() will apply garbage automatically when called by create_wide_survival_data()\n", + "See ?create_wide_survival_data for migration guidance.", + call. = FALSE + ) + } + + # Check if variables already exist in df_mock + all_vars <- c(var_entry_date, var_event_date, var_death_date, var_ltfu, var_admin_censor) + all_vars <- all_vars[!is.null(all_vars) & !is.na(all_vars)] + + if (!is.null(df_mock) && nrow(df_mock) > 0) { + existing_vars <- all_vars[all_vars %in% names(df_mock)] + if (length(existing_vars) > 0) { + warning(paste0( + "Variables already exist in df_mock: ", + paste(existing_vars, collapse = ", "), + ". Skipping survival data generation." + )) + return(NULL) + } + } + + # Set seed if provided + if (!is.null(seed)) set.seed(seed) + + # ========== STEP 1: Generate each date variable using create_date_var() ========== + + # Collect all date variables to generate + date_vars <- list() + + # 1. Entry date (REQUIRED) + date_vars[[var_entry_date]] <- list( + var = var_entry_date, + is_entry = TRUE + ) + + # 2. Event date (OPTIONAL) + if (!is.null(var_event_date) && !is.na(var_event_date)) { + date_vars[[var_event_date]] <- list( + var = var_event_date, + is_entry = FALSE + ) + } + + # 3. Death date (OPTIONAL) + if (!is.null(var_death_date) && !is.na(var_death_date)) { + date_vars[[var_death_date]] <- list( + var = var_death_date, + is_entry = FALSE + ) + } + + # 4. Loss to follow-up (OPTIONAL) + if (!is.null(var_ltfu) && !is.na(var_ltfu)) { + date_vars[[var_ltfu]] <- list( + var = var_ltfu, + is_entry = FALSE + ) + } + + # 5. Administrative censoring (OPTIONAL) + if (!is.null(var_admin_censor) && !is.na(var_admin_censor)) { + date_vars[[var_admin_censor]] <- list( + var = var_admin_censor, + is_entry = FALSE + ) + } + + # Generate each date variable + result_list <- list() + + for (var_name in names(date_vars)) { + var_info <- date_vars[[var_name]] + + # For entry date: df_mock is NULL (no anchor needed) + # For other dates: df_mock contains entry date renamed as "anchor_date" + if (var_info$is_entry) { + current_df_mock <- data.frame() + } else { + # For survival variables, create_date_var() expects anchor_date column + # Use the entry date (first result) as anchor + if (length(result_list) > 0 && var_entry_date %in% names(result_list[[1]])) { + # Create df_mock with entry date renamed to "anchor_date" + current_df_mock <- data.frame( + anchor_date = result_list[[1]][[var_entry_date]], + stringsAsFactors = FALSE + ) + } else { + current_df_mock <- data.frame() + } + } + + # Call create_date_var() + date_result <- create_date_var( + var = var_name, + databaseStart = databaseStart, + variables = variables, + variable_details = variable_details, + df_mock = current_df_mock, + n = n, + seed = NULL # Don't reset seed for each variable + ) + + # Check if generation succeeded + if (is.null(date_result)) { + warning(paste0("Failed to generate date variable: ", var_name)) + next + } + + # Store result + result_list[[var_name]] <- date_result + } + + # Combine all date variables into single data frame + if (length(result_list) == 0) { + warning("No date variables were generated successfully") + return(NULL) + } + + result <- do.call(cbind, result_list) + + # ========== STEP 2: Apply temporal ordering constraints ========== + + # Get entry date column + entry_col <- result[[var_entry_date]] + + # Process each non-entry date variable + for (var_name in names(date_vars)) { + if (date_vars[[var_name]]$is_entry) next # Skip entry date + + if (var_name %in% names(result)) { + date_col <- result[[var_name]] + + # Find violations: date < entry_date + violations <- !is.na(date_col) & !is.na(entry_col) & date_col < entry_col + + if (any(violations)) { + # Set violations to NA (censored at entry) + result[[var_name]][violations] <- NA + } + } + } + + # Special rule: If death occurs before event, set event to NA + if (!is.null(var_event_date) && !is.null(var_death_date)) { + if (var_event_date %in% names(result) && var_death_date %in% names(result)) { + event_col <- result[[var_event_date]] + death_col <- result[[var_death_date]] + + # Find cases where death < event + death_before_event <- !is.na(event_col) & !is.na(death_col) & death_col < event_col + + if (any(death_before_event)) { + # Set event to NA (censored at death) + result[[var_event_date]][death_before_event] <- NA + } + } + } + + # ========== RETURN RESULT ========== + + return(result) +} diff --git a/R/determine_proportions.R b/R/determine_proportions.R new file mode 100644 index 0000000..c14739c --- /dev/null +++ b/R/determine_proportions.R @@ -0,0 +1,76 @@ +#' Determine proportions for categorical variable generation +#' +#' @description +#' Helper function to determine proportions for categorical variables based on +#' priority: explicit parameter > metadata column > uniform distribution +#' +#' @param categories character vector. Category codes/values +#' @param proportions_param Proportions specification. Can be: +#' - NULL: Use uniform distribution +#' - Named list: Maps category codes to proportions +#' - Numeric vector: Proportions in same order as categories +#' @param var_details data.frame. Variable details metadata (may contain proportion column) +#' +#' @return Numeric vector of proportions (normalized to sum to 1), same length as categories +#' +#' @details +#' Priority order: +#' 1. proportions_param if provided (explicit user specification) +#' 2. proportion column in var_details if present +#' 3. Uniform distribution (fallback) +#' +#' @keywords internal +determine_proportions <- function(categories, proportions_param, var_details) { + + # Priority 1: Explicit proportions parameter + if (!is.null(proportions_param)) { + + if (is.list(proportions_param) && !is.null(names(proportions_param))) { + # Named list: validate and reorder to match categories + missing_cats <- setdiff(categories, names(proportions_param)) + if (length(missing_cats) > 0) { + stop("proportions list missing categories: ", + paste(missing_cats, collapse = ", "), + call. = FALSE) + } + + # Extract proportions in category order + probs <- unlist(proportions_param[categories]) + + } else if (is.numeric(proportions_param)) { + # Numeric vector: must match length + if (length(proportions_param) != length(categories)) { + stop("proportions length (", length(proportions_param), + ") must match number of categories (", length(categories), ")", + call. = FALSE) + } + probs <- proportions_param + + } else { + stop("proportions must be a named list or numeric vector", + call. = FALSE) + } + + # Normalize to sum to 1 + probs <- probs / sum(probs) + return(probs) + } + + # Priority 2: proportion column in metadata + if ("proportion" %in% names(var_details) && + any(!is.na(var_details$proportion))) { + + # Extract non-NA proportions + props_from_metadata <- var_details$proportion[!is.na(var_details$proportion)] + + # Only use if length matches categories + if (length(props_from_metadata) == length(categories)) { + probs <- props_from_metadata / sum(props_from_metadata) + return(probs) + } + } + + # Priority 3: Uniform distribution (fallback) + probs <- rep(1 / length(categories), length(categories)) + return(probs) +} diff --git a/R/identify_derived_vars.R b/R/identify_derived_vars.R new file mode 100644 index 0000000..4f4f1b2 --- /dev/null +++ b/R/identify_derived_vars.R @@ -0,0 +1,204 @@ +#' Identify derived variables using recodeflow patterns +#' +#' @description +#' Identifies derived variables using recodeflow metadata patterns in +#' variable_details. Derived variables are calculated from raw variables +#' (e.g., BMI from height/weight) and should NOT be generated as mock data. +#' +#' This function uses the recodeflow approach: derived variables are identified +#' by metadata patterns in variable_details, NOT by role column flags. +#' +#' @param variables data.frame. Variable-level metadata with column: variable +#' @param variable_details data.frame. Required. Detail-level metadata with +#' columns: variable, recStart, recEnd. Contains DerivedVar:: and Func:: +#' patterns that identify derived variables. +#' +#' @return Character vector of derived variable names (may be empty if none found) +#' +#' @details +#' **Detection methods** (recodeflow patterns only): +#' +#' 1. **DerivedVar:: pattern**: Variables with `DerivedVar::` in recStart column +#' - Example: `recStart = "DerivedVar::[HWTGHTM, HWTGWTK]"` +#' - Indicates variable is derived from listed raw variables +#' +#' 2. **Func:: pattern**: Variables with `Func::` in recEnd column +#' - Example: `recEnd = "Func::bmi_fun"` +#' - Indicates transformation function applied to derive variable +#' +#' **Why variable_details is required:** +#' +#' The recodeflow approach stores derivation logic in variable_details, not in +#' variables. The role column (if present) is NOT used for derived variable +#' detection. This ensures: +#' - Derivation logic is explicit (what variables, what function) +#' - Metadata is self-documenting +#' - Compatible with cchsflow and other recodeflow tools +#' +#' **Note:** This function does NOT check role = "derived" even if present. +#' Derived status is determined solely by DerivedVar:: and Func:: patterns. +#' +#' @examples +#' \dontrun{ +#' # BMI derived from height and weight +#' variables <- data.frame( +#' variable = c("height", "weight", "BMI_derived"), +#' variableType = c("Continuous", "Continuous", "Continuous"), +#' role = c("enabled", "enabled", "enabled"), # NO "derived" flag needed +#' stringsAsFactors = FALSE +#' ) +#' +#' variable_details <- data.frame( +#' variable = c("height", "weight", "BMI_derived"), +#' recStart = c("[1.4,2.1]", "[45,150]", "DerivedVar::[height, weight]"), +#' recEnd = c("copy", "copy", "Func::bmi_fun"), +#' stringsAsFactors = FALSE +#' ) +#' +#' identify_derived_vars(variables, variable_details) +#' # Returns: "BMI_derived" +#' +#' # ADL derived from 5 ADL items +#' variable_details_adl <- data.frame( +#' variable = c("ADL_01", "ADL_02", "ADL_03", "ADL_04", "ADL_05", "ADL_der"), +#' recStart = c(rep("1", 5), "DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05]"), +#' recEnd = c(rep("1", 5), "Func::adl_fun"), +#' stringsAsFactors = FALSE +#' ) +#' +#' identify_derived_vars(variables, variable_details_adl) +#' # Returns: "ADL_der" +#' } +#' +#' @family helpers +#' @export +identify_derived_vars <- function(variables, variable_details) { + + # ========== VALIDATION ========== + + if (!is.data.frame(variables)) { + stop("variables must be a data frame") + } + + if (!"variable" %in% names(variables)) { + stop("variables must have a 'variable' column") + } + + if (missing(variable_details) || is.null(variable_details)) { + stop("variable_details is required to identify derived variables. ", + "Derived variables are identified by DerivedVar:: and Func:: patterns ", + "in variable_details, not by role column.") + } + + if (!is.data.frame(variable_details)) { + stop("variable_details must be a data frame") + } + + if (!"variable" %in% names(variable_details)) { + stop("variable_details must have a 'variable' column") + } + + # ========== PATTERN-BASED DETECTION (RECODEFLOW ONLY) ========== + + derived_vars <- character(0) + + # Method 1: Check for DerivedVar:: in recStart + if ("recStart" %in% names(variable_details)) { + vars_with_derivedvar <- unique( + variable_details$variable[ + grepl("DerivedVar::", variable_details$recStart, fixed = TRUE) + ] + ) + derived_vars <- c(derived_vars, vars_with_derivedvar) + } + + # Method 2: Check for Func:: in recEnd (transformation functions) + if ("recEnd" %in% names(variable_details)) { + vars_with_func <- unique( + variable_details$variable[ + grepl("Func::", variable_details$recEnd, fixed = TRUE) + ] + ) + derived_vars <- c(derived_vars, vars_with_func) + } + + # Remove duplicates + derived_vars <- unique(derived_vars) + + # Filter to only variables that exist in variables data frame + derived_vars <- derived_vars[derived_vars %in% variables$variable] + + return(derived_vars) +} + + +#' Extract raw variable dependencies from derived variable metadata +#' +#' @description +#' For a given derived variable, extract the list of raw variables it depends on +#' by parsing the DerivedVar::[...] pattern in variable_details. +#' +#' @param derived_var character. Name of the derived variable +#' @param variable_details data.frame. Detail-level metadata with columns: +#' variable, recStart +#' +#' @return Character vector of raw variable names that the derived variable +#' depends on. Returns character(0) if no dependencies found. +#' +#' @details +#' Parses patterns like: +#' - `DerivedVar::[HWTGHTM, HWTGWTK]` β†’ c("HWTGHTM", "HWTGWTK") +#' - `DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05]` β†’ c("ADL_01", ...) +#' +#' @examples +#' \dontrun{ +#' variable_details <- data.frame( +#' variable = c("HWTGBMI_der"), +#' recStart = c("DerivedVar::[HWTGHTM, HWTGWTK]"), +#' stringsAsFactors = FALSE +#' ) +#' +#' get_raw_var_dependencies("HWTGBMI_der", variable_details) +#' # Returns: c("HWTGHTM", "HWTGWTK") +#' } +#' +#' @family helpers +#' @export +get_raw_var_dependencies <- function(derived_var, variable_details) { + + # Validate inputs + if (!is.character(derived_var) || length(derived_var) != 1) { + stop("derived_var must be a single character string") + } + + if (!is.data.frame(variable_details)) { + stop("variable_details must be a data frame") + } + + if (!"variable" %in% names(variable_details) || !"recStart" %in% names(variable_details)) { + stop("variable_details must have 'variable' and 'recStart' columns") + } + + # Find rows for this derived variable with DerivedVar:: pattern + pattern_rows <- variable_details[ + variable_details$variable == derived_var & + grepl("DerivedVar::", variable_details$recStart, fixed = TRUE), + ] + + if (nrow(pattern_rows) == 0) { + return(character(0)) + } + + # Extract first match (should only be one DerivedVar:: row per variable) + pattern <- pattern_rows$recStart[1] + + # Extract content between [ and ] + # Pattern: DerivedVar::[VAR1, VAR2, VAR3] + raw_vars_str <- gsub(".*DerivedVar::\\[(.*)\\].*", "\\1", pattern) + + # Split by comma and trim whitespace + raw_vars <- strsplit(raw_vars_str, ",\\s*")[[1]] + raw_vars <- trimws(raw_vars) + + return(raw_vars) +} diff --git a/R/import_from_recodeflow.R b/R/import_from_recodeflow.R new file mode 100644 index 0000000..4b8d2a1 --- /dev/null +++ b/R/import_from_recodeflow.R @@ -0,0 +1,275 @@ +#' Import and convert recodeflow variables and variable details metadata files to MockData configuration format +#' +#' @description +#' Converts recodeflow variables.csv and variable_details.csv files into +#' MockData configuration format (mock_data_config.csv and +#' mock_data_config_details.csv). Filters variables by role and optionally +#' by database. +#' +#' @param variables_path Character. Path to recodeflow variables.csv file. +#' @param variable_details_path Character. Path to recodeflow variable_details.csv file. +#' @param role_filter Character. Role value to filter variables by. Only variables +#' with this role will be imported. Default is "mockdata". Use regex word boundary +#' matching to avoid partial matches (e.g., "mockdata" won't match "mockdata_test"). +#' @param database Character vector or NULL. Database identifier(s) to filter by. +#' If NULL (default), extracts all unique databases from variables.csv databaseStart +#' column. If specified, only imports variables that exist in the specified database(s). +#' @param output_dir Character. Directory where output CSV files will be written. +#' Default is "inst/extdata/". Files will be named mock_data_config.csv and +#' mock_data_config_details.csv. +#' +#' @return Invisible list with two data frames: config and details +#' +#' @details +#' ## Column Mapping +#' +#' ### variables.csv -> mock_data_config.csv +#' Direct copy: variable, role, label, labelLong, section, subject, variableType, +#' units, version, description (to notes) +#' +#' Generated: +#' - uid: v_001, v_002, v_003, ... +#' - position: 10, 20, 30, ... +#' - source_database: extracted from databaseStart based on database filter +#' - source_spec: basename of variables_path +#' - last_updated: current date +#' - mockDataLastUpdated: current date +#' - seed: NA +#' - rType: NA (user must fill in: integer/double/factor/date/logical/character) +#' - corrupt_low_prop, corrupt_low_range, corrupt_high_prop, corrupt_high_range: NA +#' - mockDataVersion, mockDataVersionNotes: NA +#' +#' ### variable_details.csv -> mock_data_config_details.csv +#' Direct copy: variable, dummyVariable, catStartLabel (to catLabel), +#' catLabelLong, units, notes +#' +#' Mapped: +#' - recStart: copied from input recStart +#' - recEnd: initialized to input recStart (user updates to: valid, distribution, mean, etc.) +#' +#' Generated: +#' - uid: looked up from config by variable name +#' - uid_detail: d_001, d_002, d_003, ... +#' - proportion: NA (user fills in - must sum to 1.0 per variable) +#' - value: NA (user fills in distribution parameters) +#' - sourceFormat: NA (user fills in for date variables) +#' +#' ## Database Filtering +#' When database parameter is specified, the function: +#' 1. Filters variables.csv rows where databaseStart contains the specified database(s) +#' 2. Filters variable_details.csv rows where databaseStart contains the specified database(s) +#' 3. Sets source_database to the filtered database(s) in mock_data_config.csv +#' +#' @examples +#' \dontrun{ +#' # Import all variables with role "mockdata" from all databases +#' import_from_recodeflow( +#' variables_path = "inst/extdata/cchs/variables_cchsflow_sample.csv", +#' variable_details_path = "inst/extdata/cchs/variable_details_cchsflow_sample.csv", +#' role_filter = "mockdata" +#' ) +#' +#' # Import only from specific database +#' import_from_recodeflow( +#' variables_path = "inst/extdata/cchs/variables_cchsflow_sample.csv", +#' variable_details_path = "inst/extdata/cchs/variable_details_cchsflow_sample.csv", +#' role_filter = "mockdata", +#' database = "cchs2015_2016_p" +#' ) +#' +#' # Import from multiple databases +#' import_from_recodeflow( +#' variables_path = "inst/extdata/cchs/variables_cchsflow_sample.csv", +#' variable_details_path = "inst/extdata/cchs/variable_details_cchsflow_sample.csv", +#' role_filter = "mockdata", +#' database = c("cchs2015_2016_p", "cchs2017_2018_p") +#' ) +#' } +#' +#' @export +import_from_recodeflow <- function( + variables_path, + variable_details_path, + role_filter = "mockdata", + database = NULL, + output_dir = "inst/extdata/" +) { + + # Input validation + if (!file.exists(variables_path)) { + stop("variables_path file does not exist: ", variables_path) + } + if (!file.exists(variable_details_path)) { + stop("variable_details_path file does not exist: ", variable_details_path) + } + if (!dir.exists(output_dir)) { + dir.create(output_dir, recursive = TRUE) + message("Created output directory: ", output_dir) + } + + # Read input files + message("Reading variables from: ", variables_path) + variables <- read.csv(variables_path, stringsAsFactors = FALSE, check.names = FALSE) + + message("Reading variable_details from: ", variable_details_path) + variable_details <- read.csv(variable_details_path, stringsAsFactors = FALSE, check.names = FALSE) + + # Validate required columns in variables.csv + required_vars_cols <- c("variable", "role", "variableType", "databaseStart") + missing_vars_cols <- setdiff(required_vars_cols, names(variables)) + if (length(missing_vars_cols) > 0) { + stop("Missing required columns in variables.csv: ", paste(missing_vars_cols, collapse = ", ")) + } + + # Validate required columns in variable_details.csv + required_details_cols <- c("variable", "recStart", "databaseStart") + missing_details_cols <- setdiff(required_details_cols, names(variable_details)) + if (length(missing_details_cols) > 0) { + stop("Missing required columns in variable_details.csv: ", paste(missing_details_cols, collapse = ", ")) + } + + # Filter variables by role (word boundary matching) + role_pattern <- paste0("\\b", role_filter, "\\b") + variables_filtered <- variables[grepl(role_pattern, variables$role, ignore.case = TRUE), ] + + if (nrow(variables_filtered) == 0) { + stop("No variables found with role '", role_filter, "' in variables.csv") + } + + message("Found ", nrow(variables_filtered), " variables with role '", role_filter, "'") + + # Determine database filter + if (is.null(database)) { + # Extract all unique databases from databaseStart + all_databases <- unique(unlist(strsplit(variables_filtered$databaseStart, ",\\s*"))) + database <- all_databases + message("No database specified. Using all databases found: ", paste(database, collapse = ", ")) + } else { + message("Filtering to database(s): ", paste(database, collapse = ", ")) + } + + # Filter variables by database + database_pattern <- paste(database, collapse = "|") + variables_filtered <- variables_filtered[grepl(database_pattern, variables_filtered$databaseStart), ] + + if (nrow(variables_filtered) == 0) { + stop("No variables found for database(s): ", paste(database, collapse = ", ")) + } + + message("After database filtering: ", nrow(variables_filtered), " variables") + + # Filter variable_details by the selected variables AND database + details_filtered <- variable_details[ + variable_details$variable %in% variables_filtered$variable & + grepl(database_pattern, variable_details$databaseStart), + ] + + if (nrow(details_filtered) == 0) { + warning("No detail rows found for filtered variables. This may be expected for continuous variables.") + } else { + message("Found ", nrow(details_filtered), " detail rows for filtered variables") + } + + # Build mock_data_config.csv + message("\nBuilding mock_data_config.csv...") + + config <- data.frame( + uid = paste0("v_", sprintf("%03d", seq_len(nrow(variables_filtered)))), + variable = variables_filtered$variable, + role = variables_filtered$role, + label = if ("label" %in% names(variables_filtered)) variables_filtered$label else NA, + labelLong = if ("labelLong" %in% names(variables_filtered)) variables_filtered$labelLong else NA, + section = if ("section" %in% names(variables_filtered)) variables_filtered$section else NA, + subject = if ("subject" %in% names(variables_filtered)) variables_filtered$subject else NA, + variableType = variables_filtered$variableType, + rType = NA, # MockData: R data type (integer/double/factor/logical/character/date) - user fills in + units = if ("units" %in% names(variables_filtered)) variables_filtered$units else NA, + position = seq(10, by = 10, length.out = nrow(variables_filtered)), + source_database = paste(database, collapse = ", "), + source_spec = basename(variables_path), + version = if ("version" %in% names(variables_filtered)) variables_filtered$version else NA, + last_updated = as.character(Sys.Date()), + notes = if ("description" %in% names(variables_filtered)) variables_filtered$description else NA, + seed = NA, + # MockData extension fields for contamination + corrupt_low_prop = NA, + corrupt_low_range = NA, + corrupt_high_prop = NA, + corrupt_high_range = NA, + # MockData versioning + mockDataVersion = NA, + mockDataLastUpdated = as.character(Sys.Date()), + mockDataVersionNotes = NA, + stringsAsFactors = FALSE + ) + + # Build mock_data_config_details.csv + message("Building mock_data_config_details.csv...") + + if (nrow(details_filtered) > 0) { + # Create uid lookup table + uid_lookup <- setNames(config$uid, config$variable) + + details <- data.frame( + uid = uid_lookup[details_filtered$variable], + uid_detail = paste0("d_", sprintf("%03d", seq_len(nrow(details_filtered)))), + variable = details_filtered$variable, + dummyVariable = if ("dummyVariable" %in% names(details_filtered)) details_filtered$dummyVariable else NA, + recStart = details_filtered$recStart, # Keep original recStart + recEnd = details_filtered$recStart, # Also map to recEnd for categorization + catLabel = if ("catStartLabel" %in% names(details_filtered)) details_filtered$catStartLabel else NA, + catLabelLong = if ("catLabelLong" %in% names(details_filtered)) details_filtered$catLabelLong else NA, + units = if ("units" %in% names(details_filtered)) details_filtered$units else NA, + proportion = NA, # Leave empty for user specification + value = NA, + sourceFormat = NA, # For date formatting specifications + notes = if ("notes" %in% names(details_filtered)) details_filtered$notes else NA, + stringsAsFactors = FALSE + ) + } else { + # Create empty details file with correct structure + details <- data.frame( + uid = character(0), + uid_detail = character(0), + variable = character(0), + dummyVariable = character(0), + recStart = character(0), + recEnd = character(0), + catLabel = character(0), + catLabelLong = character(0), + units = character(0), + proportion = numeric(0), + value = numeric(0), + sourceFormat = character(0), + notes = character(0), + stringsAsFactors = FALSE + ) + } + + # Write output files + config_path <- file.path(output_dir, "mock_data_config.csv") + details_path <- file.path(output_dir, "mock_data_config_details.csv") + + message("\nWriting output files...") + message(" ", config_path) + write.csv(config, config_path, row.names = FALSE, na = "") + + message(" ", details_path) + write.csv(details, details_path, row.names = FALSE, na = "") + + message("\nImport complete!") + message(" Variables imported: ", nrow(config)) + message(" Detail rows imported: ", nrow(details)) + message("\nNext steps:") + message(" 1. Review ", config_path) + message(" - Fill in 'rType' for each variable (integer/double/factor/date/logical/character)") + message(" - Optionally add contamination parameters (corrupt_low_prop, corrupt_low_range, etc.)") + message(" - Add mockDataVersion and mockDataVersionNotes") + message(" 2. Review ", details_path) + message(" - Fill in 'proportion' values (must sum to 1.0 per variable)") + message(" - Add distribution parameters in 'value' column (mean, sd, rate, shape)") + message(" - Use interval notation [min,max] in recStart for ranges") + message(" - Specify recEnd values: valid, distribution, mean, sd, event, followup_min, etc.") + + invisible(list(config = config, details = details)) +} diff --git a/R/mockdata-parsers.R b/R/mockdata-parsers.R new file mode 100644 index 0000000..6695bd7 --- /dev/null +++ b/R/mockdata-parsers.R @@ -0,0 +1,341 @@ +# ============================================================================== +# MockData Parsers +# ============================================================================== +# Functions for parsing recodeflow metadata conventions +# +# These parsers work with variableStart and range notation formats used across +# all recodeflow projects (CHMS, CCHS, etc.) +# ============================================================================== + +#' Parse variableStart field to extract raw variable name +#' +#' This function parses the `variableStart` field from variable_details metadata +#' and extracts the raw variable name for a specific database/cycle. It supports +#' recodeflow-standard formats: database-prefixed (`"database::varname"`), +#' bracket (`"[varname]"`), mixed, and plain formats. +#' +#' @param variable_start Character string from variableStart field. Can contain +#' multiple database specifications separated by commas (e.g., "cycle1::age, cycle2::AGE"). +#' @param cycle Character string specifying the database/cycle to extract (e.g., "cycle1", "cchs2001"). +#' +#' @return Character string with the raw variable name, or NULL if not found. +#' +#' @details +#' The function implements recodeflow-standard parsing strategies: +#' \enumerate{ +#' \item Database-prefixed format: `"database::varname"` - for database-specific names +#' \item Bracket format (whole string): `"[varname]"` - for database-agnostic names +#' \item Bracket format (segment): `"database1::var1, [var2]"` - `[var2]` is DEFAULT for other databases +#' \item Plain format: `"varname"` - uses value as-is +#' } +#' +#' **Important**: `[variable]` represents the DEFAULT for all databases not explicitly +#' referenced with database:: notation. This reduces repetition when only one or a +#' few databases use different variable names. +#' +#' For DerivedVar format, returns NULL (requires custom derivation logic). +#' +#' @examples +#' # Database-prefixed format +#' parse_variable_start("cycle1::height, cycle2::HEIGHT", "cycle1") +#' # Returns: "height" +#' +#' # Bracket format (database-agnostic) +#' parse_variable_start("[gen_015]", "cycle1") +#' # Returns: "gen_015" +#' +#' # Mixed format - [variable] is DEFAULT for databases not explicitly listed +#' parse_variable_start("cycle1::amsdmva1, [ammdmva1]", "cycle2") +#' # Returns: "ammdmva1" (uses default for cycle2) +#' +#' # Plain format +#' parse_variable_start("bmi", "cycle1") +#' # Returns: "bmi" +#' +#' # No match for specified database +#' parse_variable_start("cycle2::age", "cycle1") +#' # Returns: NULL +#' +#' @family parsing-utilities +#' @export +parse_variable_start <- function(variable_start, cycle) { + # Basic validation + if (is.null(variable_start) || is.null(cycle)) return(NULL) + if (variable_start == "" || cycle == "") return(NULL) + + # Trim whitespace + variable_start <- trimws(variable_start) + + # Strategy 1: Database-prefixed format "database::varname" + # Split by comma to handle multiple databases + segments <- unlist(strsplit(variable_start, ",")) + segments <- trimws(segments) + + # Look for segment matching this database/cycle + cycle_pattern <- paste0(cycle, "::") + matching_segments <- segments[grepl(cycle_pattern, segments, fixed = TRUE)] + + if (length(matching_segments) > 0) { + # Extract variable name after :: + var_raw <- sub(paste0("^.*", cycle, "::"), "", matching_segments[1]) + return(trimws(var_raw)) + } + + # Strategy 2: Bracket format "[varname]" - entire string + # Check if entire string is bracket format + if (grepl("^\\[.*\\]$", variable_start)) { + var_raw <- gsub("\\[|\\]", "", variable_start) + return(trimws(var_raw)) + } + + # Strategy 2b: Bracket format (segment) - [varname] is DEFAULT + # For mixed format like "database1::var1, [var2]" + # The [var2] represents the DEFAULT for all databases not explicitly listed + bracket_segments <- segments[grepl("^\\[.*\\]$", segments)] + if (length(bracket_segments) > 0) { + var_raw <- gsub("\\[|\\]", "", bracket_segments[1]) + return(trimws(var_raw)) + } + + # Strategy 3: Plain format "varname" + # Check if it's NOT a DerivedVar, Func, or database-prefixed format + if (!grepl("^DerivedVar::", variable_start) && + !grepl("^Func::", variable_start) && + !grepl("::", variable_start, fixed = TRUE)) { + # Simple variable name, use as-is + return(trimws(variable_start)) + } + + # Return NULL for DerivedVar and Func formats + # These require custom logic beyond simple variable mapping + return(NULL) +} + +#' Parse range notation from variable_details +#' +#' Parses recodeflow-standard range notation strings from variable_details.csv +#' (recodes column) into structured data for mock data generation. Supports +#' integer ranges, continuous ranges, special codes, and function calls. +#' +#' @param range_string Character string containing range notation +#' @param range_type Character. One of: +#' - "auto" (default): Auto-detect based on bracket notation and decimal values +#' - "integer": Force integer range interpretation (generates sequence) +#' - "continuous": Force continuous range interpretation +#' @param expand_integers Logical. If TRUE and range_type is "integer", +#' returns all integers in the range as a vector +#' +#' @return For continuous ranges: List with min, max, min_inclusive, max_inclusive +#' For integer ranges: List with min, max, values (if expand_integers=TRUE) +#' Returns NULL if parsing fails +#' +#' @details +#' **Range Notation Formats:** +#' +#' Supports both comma (recommended) and semicolon (compatibility) delimiters: +#' +#' - Integer ranges: `[7,9]` or `[7;9]` β†’ integers 7,8,9 +#' - Continuous ranges: `[18.5,25)` or `[18.5;25)` β†’ 18.5 ≀ x < 25 +#' - Continuous ranges: `[18.5,25]` or `[18.5;25]` β†’ 18.5 ≀ x ≀ 25 +#' - Infinity ranges: `[30,inf)` or `[30;inf)` β†’ x β‰₯ 30 +#' - Date ranges: `[2001-01-01;2005-12-31]` (semicolon recommended for dates) +#' - Special codes: `NA::a`, `NA::b`, `copy`, `else` (passed through unchanged) +#' - Function calls: `Func::function_name` (passed through unchanged) +#' +#' **Mathematical Bracket Notation:** +#' - `[a,b]` or `[a;b]` - Closed interval: a ≀ x ≀ b +#' - `[a,b)` or `[a;b)` - Half-open interval: a ≀ x < b +#' - `(a,b]` or `(a;b]` - Half-open interval: a < x ≀ b +#' - `(a,b)` or `(a;b)` - Open interval: a < x < b +#' +#' **Auto-Detection Logic:** +#' - Contains decimal values β†’ continuous range +#' - Uses mathematical bracket notation `[a,b)` β†’ continuous range +#' - Simple `[integer,integer]` β†’ integer range (generates sequence) +#' - Contains "inf" β†’ continuous range +#' +#' @examples +#' # Integer ranges +#' parse_range_notation("[7,9]") +#' # Returns: list(min=7, max=9, values=c(7,8,9), type="integer") +#' +#' # Continuous ranges +#' parse_range_notation("[18.5,25)") +#' # Returns: list(min=18.5, max=25, min_inclusive=TRUE, max_inclusive=FALSE, type="continuous") +#' +#' parse_range_notation("[30,inf)") +#' # Returns: list(min=30, max=Inf, min_inclusive=TRUE, max_inclusive=FALSE, type="continuous") +#' +#' # Special cases +#' parse_range_notation("NA::a") # Returns: list(type="special", value="NA::a") +#' parse_range_notation("copy") # Returns: list(type="special", value="copy") +#' parse_range_notation("else") # Returns: list(type="special", value="else") +#' +#' @note Adapted from cchsflow v4.0.0 (2025-07-27) - universal across recodeflow projects +#' @family parsing-utilities +#' @export +parse_range_notation <- function(range_string, range_type = "auto", expand_integers = TRUE) { + # Handle NULL, NA, or empty inputs + if (is.null(range_string) || is.na(range_string) || range_string == "" || range_string == "N/A") { + return(NULL) + } + + # Clean input + range_clean <- trimws(range_string) + + # Handle special codes (NA::a, NA::b, copy, else, etc.) + if (grepl("^(NA::[ab]|copy|else)$", range_clean)) { + return(list( + type = "special", + value = range_clean + )) + } + + # Handle function calls (Func::function_name) + if (grepl("^Func::", range_clean)) { + return(list( + type = "function", + value = range_clean + )) + } + + # Handle single numeric values (not ranges) + if (grepl("^[0-9]+\\.?[0-9]*$", range_clean)) { + numeric_val <- as.numeric(range_clean) + return(list( + type = "single_value", + value = numeric_val, + min = numeric_val, + max = numeric_val + )) + } + + # Parse bracket notation ranges using simple character analysis + # Support both [] and () bracket types for mathematical notation + + # Check for bracket structure + first_char <- substr(range_clean, 1, 1) + last_char <- substr(range_clean, nchar(range_clean), nchar(range_clean)) + + if (!first_char %in% c("[", "(") || !last_char %in% c("]", ")")) { + return(NULL) + } + + # Extract bracket types + left_bracket <- first_char + right_bracket <- last_char + + # Extract content between brackets + inner_content <- substr(range_clean, 2, nchar(range_clean) - 1) + + # Find delimiter position (comma or semicolon) + # Support both comma (recommended) and semicolon (compatibility) + delimiter_pos <- regexpr("[,;]", inner_content) + if (delimiter_pos[1] == -1) { + return(NULL) + } + + min_str <- trimws(substr(inner_content, 1, delimiter_pos[1] - 1)) + max_str <- trimws(substr(inner_content, delimiter_pos[1] + 1, nchar(inner_content))) + + # Parse min value (handle "inf", numeric values, and dates) + if (tolower(min_str) == "inf") { + min_val <- Inf + } else { + # Try numeric first + min_val <- suppressWarnings(as.numeric(min_str)) + # If numeric parsing fails, try date parsing + if (is.na(min_val)) { + min_date <- suppressWarnings(as.Date(min_str)) + if (!is.na(min_date)) { + min_val <- min_date + } else { + return(NULL) + } + } + } + + # Parse max value (handle "inf", numeric values, and dates) + if (tolower(max_str) == "inf") { + max_val <- Inf + } else { + # Try numeric first + max_val <- suppressWarnings(as.numeric(max_str)) + # If numeric parsing fails, try date parsing + if (is.na(max_val)) { + max_date <- suppressWarnings(as.Date(max_str)) + if (!is.na(max_date)) { + max_val <- max_date + } else { + return(NULL) + } + } + } + + # Determine inclusivity from bracket types + min_inclusive <- (left_bracket == "[") + max_inclusive <- (right_bracket == "]") + + # Auto-detect range type if not specified + if (range_type == "auto") { + # Detect dates first + if (inherits(min_val, "Date") || inherits(max_val, "Date")) { + range_type <- "date" + } else { + # Detect continuous ranges by: + # 1. Mathematical bracket notation (half-open intervals) + # 2. Decimal values + # 3. Infinity values + # 4. Explicitly non-inclusive brackets + has_mathematical_notation <- (!min_inclusive || !max_inclusive) + has_decimals <- (min_val != floor(min_val)) || (max_val != floor(max_val)) + has_infinity <- is.infinite(min_val) || is.infinite(max_val) + + if (has_mathematical_notation || has_decimals || has_infinity) { + range_type <- "continuous" + } else { + range_type <- "integer" + } + } + } + + # Build result based on detected/specified type + if (range_type == "integer") { + # Generate integer sequence if requested and bounds are finite + if (expand_integers && is.finite(min_val) && is.finite(max_val)) { + integer_values <- seq(from = as.integer(min_val), to = as.integer(max_val), by = 1) + } else { + integer_values <- NULL + } + + return(list( + type = "integer", + min = as.integer(min_val), + max = as.integer(max_val), + values = integer_values, + min_inclusive = min_inclusive, + max_inclusive = max_inclusive + )) + + } else if (range_type == "continuous") { + return(list( + type = "continuous", + min = min_val, + max = max_val, + min_inclusive = min_inclusive, + max_inclusive = max_inclusive + )) + + } else if (range_type == "date") { + return(list( + type = "date", + min = min_val, + max = max_val, + min_inclusive = min_inclusive, + max_inclusive = max_inclusive + )) + } + + # Fallback for unrecognized type + return(NULL) +} diff --git a/R/mockdata_helpers.R b/R/mockdata_helpers.R new file mode 100644 index 0000000..7e440e5 --- /dev/null +++ b/R/mockdata_helpers.R @@ -0,0 +1,1168 @@ +# ============================================================================== +# MockData Helper Functions +# ============================================================================== +# DRY utilities for create_* functions +# +# These helpers centralize common operations across all variable generators: +# - Proportion extraction and validation +# - Missing code application +# - Garbage data model (make_garbage!) +# - Distribution parameter extraction +# - Variable details filtering +# +# Note: Leverages parse_range_notation() from mockdata-parsers.R +# ============================================================================== + + +# 1. VARIABLE DETAILS OPERATIONS ==== + +#' Get variable details for specific variable +#' +#' Filters details data frame to return only rows for a specific variable. +#' Handles NULL details (fallback mode) and provides consistent sorting. +#' +#' @param details Data frame. Full details data (or NULL for fallback mode). +#' @param variable_name Character. Variable name to filter (e.g., "ADL_01"). +#' @param uid Character. Alternative - filter by uid (e.g., "v_001"). +#' +#' @return Subset of details rows for this variable, sorted by uid_detail. +#' Returns NULL if details is NULL (signals fallback mode). +#' Returns empty data frame with warning if no matching rows. +#' +#' @examples +#' \dontrun{ +#' details <- read_mock_data_config_details("details.csv") +#' var_details <- get_variable_details(details, variable_name = "ADL_01") +#' +#' # Fallback mode +#' var_details <- get_variable_details(NULL, variable_name = "ADL_01") +#' # Returns: NULL +#' } +#' +#' @family mockdata-helpers +#' @export +get_variable_details <- function(details, variable_name = NULL, uid = NULL) { + # Handle NULL details (fallback mode) + if (is.null(details)) { + return(NULL) + } + + # Validate inputs + if (is.null(variable_name) && is.null(uid)) { + stop("Must provide either variable_name or uid") + } + + # Filter by variable_name or uid + if (!is.null(variable_name)) { + subset <- details[details$variable == variable_name, ] + } else { + subset <- details[details$uid == uid, ] + } + + # Warn if no matches + if (nrow(subset) == 0) { + search_term <- if (!is.null(variable_name)) variable_name else uid + warning("No details found for variable: ", search_term) + return(subset) # Empty data frame with same structure + } + + # Sort by uid_detail for consistent ordering + if ("uid_detail" %in% names(subset)) { + subset <- subset[order(subset$uid_detail), ] + } + + return(subset) +} + + +# 2. PROPORTION OPERATIONS ==== + +#' Extract proportions from details subset +#' +#' Parses proportion column and organizes by type (valid, missing, garbage). +#' Validates that valid + missing proportions sum to 1.0 (Β±0.001 tolerance). +#' Auto-normalizes with warning if sum != 1.0. +#' +#' @param details_subset Data frame. Rows from details for one variable. +#' @param variable_name Character. Variable name for error messages. +#' +#' @return Named list with: +#' - valid: Numeric. Proportion for valid values (sum of all non-missing, non-garbage) +#' - missing: Named list. Proportion for each missing code (e.g., "7" = 0.03) +#' - garbage: Named list. Proportion for each garbage type (e.g., corrupt_low = 0.02) +#' - categories: Character vector. All non-garbage recStart values +#' - category_proportions: Numeric vector. Proportions for sampling (aligned with categories) +#' +#' @details +#' Population proportions (valid + missing) must sum to 1.0. Garbage proportions +#' are separate and applied to valid values only. +#' +#' If proportions are NA or missing, returns uniform probabilities. +#' +#' @examples +#' \dontrun{ +#' details <- read_mock_data_config_details("details.csv") +#' details_subset <- details[details$variable == "ADL_01", ] +#' props <- extract_proportions(details_subset, "ADL_01") +#' # Returns: list(valid = 0.92, missing = list("7" = 0.03, "9" = 0.05), ...) +#' } +#' +#' @family mockdata-helpers +#' @export +extract_proportions <- function(details_subset, variable_name = "variable") { + # Handle NULL or empty details + if (is.null(details_subset) || nrow(details_subset) == 0) { + return(list( + valid = 1.0, + missing = list(), + garbage = list(), + categories = character(0), + category_proportions = numeric(0) + )) + } + + # Identify garbage rows (exclude from population sum) + is_garbage_row <- grepl("^garbage_", details_subset$recStart, ignore.case = TRUE) + + # Identify "else" rows - harmonization logic that recodes to NA::b + # "else" acts as a garbage collector, ensuring garbage data β†’ NA::b + # Must exclude from population: it's not a valid missing code category, + # but rather a catch-all for harmonization (exception to "recodes to NA::b = missing code" rule) + is_else <- details_subset$recStart == "else" + + # Split into population (valid + missing) and garbage + # Exclude both garbage AND "else" from population + pop_rows <- details_subset[!is_garbage_row & !is_else, ] + garbage_rows <- details_subset[is_garbage_row, ] + + # Extract population proportions + pop_proportions <- pop_rows$proportion + has_proportions <- !all(is.na(pop_proportions)) + + if (!has_proportions) { + # Uniform distribution if no proportions specified + n_categories <- nrow(pop_rows) + pop_proportions <- rep(1.0 / n_categories, n_categories) + } else { + # Validate and auto-normalize + prop_sum <- sum(pop_proportions, na.rm = TRUE) + tolerance <- 0.001 + + if (abs(prop_sum - 1.0) > tolerance) { + warning("Proportions for variable '", variable_name, "' sum to ", + round(prop_sum, 4), " (expected 1.0). Auto-normalizing.") + norm_factor <- 1.0 / prop_sum + pop_proportions <- pop_proportions * norm_factor + } + } + + # Separate missing codes from valid + # Common missing code patterns: numeric codes 7,8,9,96,97,98,99,996,997,998,999 + # Check catLabelLong if it exists, otherwise check recStart pattern + # + # IMPORTANT: v0.2.1 uses interval notation [min,max] for ranges, which should NOT be treated as missing + # Only treat as missing if: + # 1. catLabelLong explicitly says "missing", OR + # 2. recStart is a single-digit or double-digit code ending in 7,8,9 (not part of a larger range) + has_label_long <- "catLabelLong" %in% names(pop_rows) + + # Detect interval notation (ranges for continuous variables): [min,max] + is_interval_notation <- grepl("^\\[.*,.*\\]$", pop_rows$recStart) + + # Missing codes: explicit label OR numeric codes ending in 7,8,9 (but not interval notation) + # Check catLabelLong column if it exists + if (has_label_long) { + is_missing <- !is_interval_notation & ( + pop_rows$catLabelLong == "missing" | + (grepl("^[0-9]+$", pop_rows$recStart) & grepl("[789]$", pop_rows$recStart)) + ) + } else { + # Only check numeric codes ending in 7,8,9 + is_missing <- !is_interval_notation & + grepl("^[0-9]+$", pop_rows$recStart) & + grepl("[789]$", pop_rows$recStart) + } + + # Build results + # Categories should ONLY include valid (non-missing) rows + valid_rows <- pop_rows[!is_missing, ] + missing_rows <- pop_rows[is_missing, ] + + result <- list( + valid = sum(pop_proportions[!is_missing], na.rm = TRUE), + missing = list(), + garbage = list(), + categories = valid_rows$recStart, + category_proportions = pop_proportions[!is_missing] + ) + + # Normalize category proportions to sum to 1.0 + if (length(result$category_proportions) > 0 && result$valid > 0) { + result$category_proportions <- result$category_proportions / result$valid + } + + # Add missing codes + if (nrow(missing_rows) > 0) { + result$missing <- as.list(setNames(pop_proportions[is_missing], missing_rows$recStart)) + } + + # Extract garbage proportions + if (nrow(garbage_rows) > 0) { + garbage_props <- garbage_rows$proportion + garbage_names <- garbage_rows$recStart + result$garbage <- as.list(setNames(garbage_props, garbage_names)) + } + + return(result) +} + + +#' Sample with proportions +#' +#' Generates category assignments with specified proportions. +#' Handles NA proportions (uniform fallback) and validates inputs. +#' +#' @param categories Character or numeric vector. Category values. +#' @param proportions Numeric vector. Proportions (same length, sum to 1.0). +#' @param n Integer. Number of samples. +#' @param seed Integer. Optional random seed. +#' +#' @return Vector of length n with category assignments. +#' +#' @examples +#' \dontrun{ +#' categories <- c("1", "2", "7", "9") +#' proportions <- c(0.4, 0.52, 0.03, 0.05) +#' assignments <- sample_with_proportions(categories, proportions, n = 1000) +#' } +#' +#' @family mockdata-helpers +#' @export +sample_with_proportions <- function(categories, proportions, n, seed = NULL) { + # Set seed if provided + if (!is.null(seed)) { + set.seed(seed) + } + + # Validate inputs + if (length(categories) != length(proportions)) { + stop("categories and proportions must have same length") + } + + # Handle NA proportions - use uniform + if (all(is.na(proportions))) { + proportions <- rep(1.0 / length(categories), length(categories)) + } + + # Normalize if sum != 1.0 + prop_sum <- sum(proportions, na.rm = TRUE) + if (abs(prop_sum - 1.0) > 0.001) { + proportions <- proportions / prop_sum + } + + # Sample + sample(categories, size = n, replace = TRUE, prob = proportions) +} + + +# 3. DISTRIBUTION PARAMETERS ==== + +#' Extract distribution parameters from details +#' +#' Extracts distribution-specific parameters (mean, sd, rate, shape, range) from +#' details subset. Auto-detects distribution type if not specified. +#' +#' @param details_subset Data frame. Rows from details for one variable. +#' @param distribution_type Character. Optional ("normal", "uniform", "gompertz", +#' "exponential", "poisson"). If NULL, attempts auto-detection. +#' +#' @return Named list with distribution type and parameters: +#' - distribution: Character. Distribution type. +#' - mean, sd: Numeric. For normal distribution. +#' - rate, shape: Numeric. For Gompertz/exponential. +#' - range_min, range_max: Numeric. For uniform or truncation. +#' +#' @examples +#' \dontrun{ +#' params <- extract_distribution_params(details_subset, "normal") +#' # Returns: list(distribution = "normal", mean = 25, sd = 5, range_min = 18.5, range_max = 40) +#' } +#' +#' @family mockdata-helpers +#' @export +extract_distribution_params <- function(details_subset, distribution_type = NULL) { + # Handle NULL or empty details + if (is.null(details_subset) || nrow(details_subset) == 0) { + return(list(distribution = "uniform", range_min = 0, range_max = 100)) + } + + # Auto-detect distribution type if not specified + if (is.null(distribution_type)) { + has_mean <- "mean" %in% details_subset$recEnd + has_sd <- "sd" %in% details_subset$recEnd + has_rate <- "rate" %in% details_subset$recEnd + has_shape <- "shape" %in% details_subset$recEnd + + if (has_mean && has_sd) { + distribution_type <- "normal" + } else if (has_rate && has_shape) { + distribution_type <- "gompertz" + } else if (has_rate) { + distribution_type <- "exponential" + } else { + distribution_type <- "uniform" + } + } + + # Extract parameters based on distribution type + result <- list(distribution = distribution_type) + + # Extract mean and sd (for normal) + if ("mean" %in% details_subset$recEnd) { + mean_row <- details_subset[details_subset$recEnd == "mean", ] + result$mean <- as.numeric(mean_row$value[1]) + } + + if ("sd" %in% details_subset$recEnd) { + sd_row <- details_subset[details_subset$recEnd == "sd", ] + result$sd <- as.numeric(sd_row$value[1]) + } + + # Extract rate and shape (for Gompertz/exponential) + if ("rate" %in% details_subset$recEnd) { + rate_row <- details_subset[details_subset$recEnd == "rate", ] + result$rate <- as.numeric(rate_row$value[1]) + } + + if ("shape" %in% details_subset$recEnd) { + shape_row <- details_subset[details_subset$recEnd == "shape", ] + result$shape <- as.numeric(shape_row$value[1]) + } + + # Extract range (for uniform or truncation) + # Parse from recStart using interval notation + if ("recStart" %in% names(details_subset)) { + # Look for rows with recEnd = "valid" which specify the valid range + valid_rows <- details_subset[details_subset$recEnd == "valid", ] + + if (nrow(valid_rows) > 0 && !is.na(valid_rows$recStart[1]) && valid_rows$recStart[1] != "") { + # Parse the valid range from recStart interval notation + parsed <- parse_range_notation(valid_rows$recStart[1]) + + if (!is.null(parsed) && parsed$type %in% c("integer", "continuous", "single_value")) { + result$range_min <- parsed$min + result$range_max <- parsed$max + } + } + } + + # Validate required parameters + if (distribution_type == "normal") { + if (is.null(result$mean) || is.null(result$sd)) { + stop("Normal distribution requires mean and sd parameters") + } + } + + return(result) +} + + +# 4. MISSING CODE APPLICATION ==== + +#' Apply missing codes to values +#' +#' Replaces category assignments with actual missing code values (7, 8, 9, etc.). +#' Handles different data types (numeric, Date, character). +#' +#' @param values Vector. Generated values (numeric, date, or categorical). +#' @param category_assignments Vector. Category assignments ("valid", "7", "8", "9", etc.). +#' @param missing_code_map Named list. Maps category names to codes (e.g., list("7" = 7, "9" = 9)). +#' +#' @return Vector with missing codes applied. +#' +#' @examples +#' \dontrun{ +#' values <- c(23.5, 45.2, 18.9, 30.1, 25.6) +#' assignments <- c("valid", "valid", "7", "valid", "9") +#' missing_map <- list("7" = 7, "9" = 9) +#' result <- apply_missing_codes(values, assignments, missing_map) +#' # Returns: c(23.5, 45.2, 7, 30.1, 9) +#' } +#' +#' @family mockdata-helpers +#' @export +apply_missing_codes <- function(values, category_assignments, missing_code_map) { + # Handle NULL or empty inputs + if (is.null(values) || length(values) == 0) { + return(values) + } + + if (is.null(missing_code_map) || length(missing_code_map) == 0) { + return(values) + } + + # Apply missing codes + for (code_name in names(missing_code_map)) { + code_value <- missing_code_map[[code_name]] + missing_idx <- which(category_assignments == code_name) + + if (length(missing_idx) > 0) { + # Handle type coercion if needed + if (inherits(values, "Date") && is.numeric(code_value)) { + # Convert Date to numeric for missing codes + values <- as.numeric(values) + } + + # If code_value is a vector (e.g., c(997, 998, 999)), sample from it + if (length(code_value) > 1) { + values[missing_idx] <- sample(code_value, length(missing_idx), replace = TRUE) + } else { + values[missing_idx] <- code_value + } + } + } + + return(values) +} + + +# 5. GARBAGE (MAKE GARBAGE!) ==== + +#' Check if garbage is specified +#' +#' Quick check for presence of garbage rows (recEnd starts with "garbage_"). +#' +#' @param details_subset Data frame. Rows from details for one variable. +#' +#' @return Logical. TRUE if garbage rows exist, FALSE otherwise. +#' +#' @examples +#' \dontrun{ +#' if (has_garbage(details_subset)) { +#' values <- make_garbage(values, details_subset, "continuous") +#' } +#' } +#' +#' @family mockdata-helpers +#' @export +has_garbage <- function(details_subset) { + if (is.null(details_subset) || nrow(details_subset) == 0) { + return(FALSE) + } + + any(grepl("^garbage_", details_subset$recEnd, ignore.case = TRUE)) +} + + +#' Make garbage +#' +#' Applies garbage model to introduce realistic data quality issues. +#' Replaces some valid values with implausible values (garbage_low, garbage_high, +#' garbage_future, etc.). +#' +#' @param values Vector. Generated values (already has valid + missing). +#' @param details_subset Data frame. Rows from details (contains garbage_* rows). +#' @param variable_type Character. "categorical", "continuous", "date", "survival". +#' @param seed Integer. Optional random seed. +#' +#' @return Vector with garbage applied. +#' +#' @details +#' Two-step garbage model: +#' 1. Identify valid value indices (not missing codes) +#' 2. Sample from valid indices based on garbage proportions +#' 3. Replace with garbage values +#' 4. Ensure no overlap (use setdiff for sequential garbage application) +#' +#' Garbage types: +#' - garbage_low: Values below valid range (continuous, integer) +#' - garbage_high: Values above valid range (continuous, integer) +#' - garbage_future: Future dates (date, survival) +#' +#' @examples +#' \dontrun{ +#' values <- c(23.5, 45.2, 7, 30.1, 9, 18.9, 25.6) +#' result <- make_garbage(values, details_subset, "continuous", seed = 123) +#' # Some valid values replaced with implausible values +#' } +#' +#' @family mockdata-helpers +#' @export +make_garbage <- function(values, details_subset, variable_type, seed = NULL) { + # Set seed if provided + if (!is.null(seed)) { + set.seed(seed) + } + + # Check if garbage specified + if (!has_garbage(details_subset)) { + return(values) + } + + # Extract garbage rows + garbage_rows <- details_subset[grepl("^garbage_", details_subset$recEnd, ignore.case = TRUE), ] + + if (nrow(garbage_rows) == 0) { + return(values) + } + + # Identify valid indices (exclude missing codes like 7, 8, 9, 996, 997, etc.) + # Assume missing codes are numeric values in specific ranges + is_missing <- values %in% c(7, 8, 9, 96, 97, 98, 99, 996, 997, 998, 999) + valid_idx <- which(!is_missing & !is.na(values)) + + if (length(valid_idx) == 0) { + return(values) # No valid values to make garbage + } + + # Apply each garbage type sequentially + remaining_idx <- valid_idx + + for (i in seq_len(nrow(garbage_rows))) { + garbage_row <- garbage_rows[i, ] + garbage_type <- garbage_row$recEnd + garbage_prop <- garbage_row$proportion + + # Skip if proportion is NA or 0 + if (is.na(garbage_prop) || garbage_prop == 0) { + next + } + + # Calculate number to make garbage + n_valid <- length(valid_idx) + n_garbage <- round(n_valid * garbage_prop) + + if (n_garbage == 0 || length(remaining_idx) == 0) { + next + } + + # Sample indices to make garbage (without replacement) + n_garbage <- min(n_garbage, length(remaining_idx)) + garbage_idx <- sample(remaining_idx, n_garbage) + + # Generate garbage values + garbage_values <- generate_garbage_values(garbage_type, garbage_row, variable_type, n_garbage) + + # Apply garbage + values[garbage_idx] <- garbage_values + + # Remove garbage indices from remaining pool (no overlap) + remaining_idx <- setdiff(remaining_idx, garbage_idx) + } + + return(values) +} + + +#' Generate garbage values +#' +#' Generates implausible values for garbage based on type. +#' Helper function for make_garbage(). +#' +#' @param garbage_type Character. "garbage_low", "garbage_high", "garbage_future", etc. +#' @param garbage_row Data frame row. Contains recStart with interval notation for garbage range. +#' @param variable_type Character. "continuous", "date", etc. +#' @param n Integer. Number of values to generate. +#' +#' @return Vector of garbage values. +#' +#' @family mockdata-helpers +#' @export +generate_garbage_values <- function(garbage_type, garbage_row, variable_type, n) { + # Extract garbage range from recStart using interval notation + range_min <- NA + range_max <- NA + + if ("recStart" %in% names(garbage_row)) { + rec_start <- garbage_row$recStart + if (!is.na(rec_start) && rec_start != "") { + parsed <- parse_range_notation(rec_start) + if (!is.null(parsed) && parsed$type %in% c("integer", "continuous", "single_value")) { + range_min <- parsed$min + range_max <- parsed$max + } + } + } + + if (grepl("garbage_low", garbage_type, ignore.case = TRUE)) { + # Generate values below valid range + if (!is.na(range_min) && !is.na(range_max)) { + # Use specified range + values <- runif(n, range_min, range_max) + } else { + # Default: very low values + values <- runif(n, -100, -1) + } + + } else if (grepl("garbage_high", garbage_type, ignore.case = TRUE)) { + # Generate values above valid range + if (!is.na(range_min) && !is.na(range_max)) { + values <- runif(n, range_min, range_max) + } else { + # Default: very high values + values <- runif(n, 200, 1000) + } + + } else if (grepl("garbage_future", garbage_type, ignore.case = TRUE)) { + # Generate future dates + if (variable_type %in% c("date", "survival")) { + today <- Sys.Date() + future_start <- today + 365 + future_end <- today + 365 * 100 + values <- sample(seq(future_start, future_end, by = "day"), n, replace = TRUE) + } else { + values <- rep(NA, n) + } + + } else if (grepl("garbage_past", garbage_type, ignore.case = TRUE)) { + # Generate past dates (less common) + if (variable_type %in% c("date", "survival")) { + past_end <- Sys.Date() - 365 * 100 + past_start <- Sys.Date() - 365 * 200 + values <- sample(seq(past_start, past_end, by = "day"), n, replace = TRUE) + } else { + values <- rep(NA, n) + } + + } else { + # Unknown garbage type - return NA + warning("Unknown garbage type: ", garbage_type) + values <- rep(NA, n) + } + + return(values) +} + + +#' Apply garbage data from variables.csv +#' +#' Applies garbage data using parameters from variables.csv extension columns. +#' Garbage data is specified at the variable level. +#' +#' @param values Vector. Generated values (already has valid + missing). +#' @param var_row Data frame. Single row from variables.csv (contains garbage data parameters). +#' @param variable_type Character. "categorical", "continuous", "integer", "date". +#' @param missing_codes Numeric vector. Optional. Missing codes extracted from metadata +#' (rows where recEnd contains "NA::"). Used to exclude missing codes from valid range +#' calculations. If NULL, uses hardcoded fallback for backward compatibility. +#' @param seed Integer. Optional random seed. +#' +#' @return Vector with garbage data applied. +#' +#' @details +#' **Garbage data fields (in variables.csv):** +#' +#' **Garbage parameters:** +#' - garbage_low_prop: Proportion for low garbage values (0-1) +#' - garbage_low_range: Range for low values (interval notation "[min,max]") +#' - garbage_high_prop: Proportion for high garbage values (0-1) +#' - garbage_high_range: Range for high values (interval notation "[min,max]") +#' +#' **Application order:** +#' 1. Apply garbage_low (if specified) +#' 2. Apply garbage_high (if specified) +#' 3. No overlap - indices removed after each application +#' +#' **Config-driven generation:** +#' If var_row is NULL or missing garbage fields, no garbage data applied. +#' +#' @examples +#' \dontrun{ +#' var_row <- data.frame( +#' variable = "BMI", +#' garbage_low_prop = 0.02, +#' garbage_low_range = "[-10,0]", +#' garbage_high_prop = 0.01, +#' garbage_high_range = "[60,150]" +#' ) +#' values <- c(23.5, 45.2, 30.1, 18.9, 25.6) +#' result <- apply_garbage(values, var_row, "continuous", seed = 123) +#' } +#' +#' @family mockdata-helpers +#' @export +apply_garbage <- function(values, var_row, variable_type, missing_codes = NULL, seed = NULL) { + # Set seed if provided + if (!is.null(seed)) { + set.seed(seed) + } + + # Check if var_row has garbage data fields + if (is.null(var_row) || !is.data.frame(var_row) || nrow(var_row) == 0) { + return(values) + } + + # Check for garbage data fields + has_low <- "garbage_low_prop" %in% names(var_row) && "garbage_low_range" %in% names(var_row) + has_high <- "garbage_high_prop" %in% names(var_row) && "garbage_high_range" %in% names(var_row) + + # Check if any garbage is specified + has_garbage_low <- has_low && !is.na(var_row$garbage_low_prop) && var_row$garbage_low_prop > 0 + has_garbage_high <- has_high && !is.na(var_row$garbage_high_prop) && var_row$garbage_high_prop > 0 + + if (!has_garbage_low && !has_garbage_high) { + return(values) # No garbage data specified + } + + # Identify valid indices (exclude missing codes and NA) + if (is.null(missing_codes) || length(missing_codes) == 0) { + # No missing codes defined - only exclude NA values + # This is safer than assuming hardcoded values that may not apply to this dataset + valid_idx <- which(!is.na(values)) + } else { + # Use metadata-based missing codes (from recEnd = "NA::a" or "NA::b") + is_missing <- values %in% missing_codes + valid_idx <- which(!is_missing & !is.na(values)) + } + + if (length(valid_idx) == 0) { + return(values) # No valid values to set to garbage + } + + # ========================================================================== + # Apply garbage sequentially (low, then high) + # ========================================================================== + remaining_idx <- valid_idx + + # GARBAGE_LOW + if (has_low) { + garbage_low_prop <- var_row$garbage_low_prop + garbage_low_range <- var_row$garbage_low_range + + if (!is.na(garbage_low_prop) && !is.na(garbage_low_range) && + garbage_low_prop > 0 && garbage_low_range != "") { + + # Calculate number to set to garbage + n_valid <- length(valid_idx) + n_garbage <- round(n_valid * garbage_low_prop) + + if (n_garbage > 0 && length(remaining_idx) > 0) { + # Sample indices + n_garbage <- min(n_garbage, length(remaining_idx)) + garbage_idx <- sample(remaining_idx, n_garbage) + + # Parse range + parsed <- parse_range_notation(garbage_low_range) + + if (!is.null(parsed)) { + # Generate garbage values + if (parsed$type == "date") { + # Date garbage + garbage_dates_obj <- sample( + seq(parsed$min, parsed$max, by = "day"), + n_garbage, + replace = TRUE + ) + # Convert to character to avoid numeric coercion when assigning to char vector + garbage_values <- as.character(garbage_dates_obj) + } else { + # Numeric garbage (integer or continuous) + garbage_values <- runif(n_garbage, parsed$min, parsed$max) + + # Round if integer type + if (variable_type %in% c("integer", "categorical")) { + garbage_values <- round(garbage_values) + } + } + + # Apply garbage + values[garbage_idx] <- garbage_values + + # Remove from remaining pool + remaining_idx <- setdiff(remaining_idx, garbage_idx) + } + } + } + } + + # GARBAGE_HIGH + if (has_high) { + garbage_high_prop <- var_row$garbage_high_prop + garbage_high_range <- var_row$garbage_high_range + + if (!is.na(garbage_high_prop) && !is.na(garbage_high_range) && + garbage_high_prop > 0 && garbage_high_range != "") { + + # Calculate number to set to garbage + n_valid <- length(valid_idx) + n_garbage <- round(n_valid * garbage_high_prop) + + if (n_garbage > 0 && length(remaining_idx) > 0) { + # Sample indices + n_garbage <- min(n_garbage, length(remaining_idx)) + garbage_idx <- sample(remaining_idx, n_garbage) + + # Parse range + parsed <- parse_range_notation(garbage_high_range) + + if (!is.null(parsed)) { + # Generate garbage values + if (parsed$type == "date") { + # Date garbage + garbage_dates_obj <- sample( + seq(parsed$min, parsed$max, by = "day"), + n_garbage, + replace = TRUE + ) + # Convert to character to avoid numeric coercion when assigning to char vector + garbage_values <- as.character(garbage_dates_obj) + } else { + # Numeric garbage (integer or continuous) + garbage_values <- runif(n_garbage, parsed$min, parsed$max) + + # Round if integer type + if (variable_type %in% c("integer", "categorical")) { + garbage_values <- round(garbage_values) + } + } + + # Apply garbage + values[garbage_idx] <- garbage_values + + # Remove from remaining pool + remaining_idx <- setdiff(remaining_idx, garbage_idx) + } + } + } + } + + return(values) +} + + +# 7. R TYPE COERCION ==== + +#' Apply rType defaults to variable details +#' +#' Adds rType column with smart defaults if missing. This enables +#' language-specific type coercion (R types like integer, double, factor). +#' +#' @param details Data frame. Variable details metadata. +#' +#' @return Data frame with rType column added (if missing) or validated (if present). +#' +#' @details +#' ## Default rType values +#' +#' If rType column is missing, defaults are applied based on variable type: +#' - `continuous`/`cont` β†’ `"double"` +#' - `categorical`/`cat` β†’ `"factor"` +#' - `date` β†’ `"Date"` +#' - `logical` β†’ `"logical"` +#' - Unknown β†’ `"character"` +#' +#' ## Valid rType values +#' +#' - `"integer"`: Whole numbers (age, counts, years) +#' - `"double"`: Decimal numbers (BMI, income, percentages) +#' - `"factor"`: Categorical with levels +#' - `"character"`: Text codes +#' - `"logical"`: TRUE/FALSE values +#' - `"Date"`: Date objects +#' - `"POSIXct"`: Datetime objects +#' +#' @examples +#' \dontrun{ +#' # Missing rType - defaults applied +#' details <- data.frame( +#' variable = "age", +#' typeEnd = "cont", +#' recStart = "[18, 100]" +#' ) +#' details <- apply_rtype_defaults(details) +#' # details$rType is now "double" +#' +#' # Existing rType - preserved +#' details <- data.frame( +#' variable = "age", +#' typeEnd = "cont", +#' rType = "integer" +#' ) +#' details <- apply_rtype_defaults(details) +#' # details$rType remains "integer" +#' } +#' +#' @family mockdata-helpers +#' @export +apply_rtype_defaults <- function(details) { + + # If rType already exists, validate and return + if ("rType" %in% names(details)) { + # Validate rType values + valid_rtypes <- c("integer", "double", "factor", "character", + "logical", "Date", "POSIXct") + invalid <- setdiff(unique(details$rType[!is.na(details$rType)]), valid_rtypes) + if (length(invalid) > 0) { + warning("Invalid rType values found: ", paste(invalid, collapse = ", "), + ". Valid values: ", paste(valid_rtypes, collapse = ", "), + call. = FALSE) + } + return(details) + } + + # Add rType column with defaults + details$rType <- NA_character_ + + # Determine type column (could be typeEnd or variableType) + type_col <- if ("typeEnd" %in% names(details)) { + "typeEnd" + } else if ("variableType" %in% names(details)) { + "variableType" + } else { + NULL + } + + if (!is.null(type_col)) { + # Apply defaults based on type + type_lower <- tolower(details[[type_col]]) + + details$rType <- dplyr::case_when( + type_lower %in% c("cont", "continuous") ~ "double", # Continuous β†’ double (default) + type_lower %in% c("cat", "categorical") ~ "factor", # Categorical β†’ factor (default) + type_lower == "date" ~ "Date", # Date β†’ Date (default) + type_lower == "logical" ~ "logical", # Logical β†’ logical + TRUE ~ "character" # Fallback + ) + } else { + # No type column found - default to character + details$rType <- "character" + } + + return(details) +} + + +# 8. CYCLE AND VARIABLE QUERIES ==== + +#' Get list of variables used in a specific database/cycle +#' +#' Returns a data frame containing all variables that are available in a +#' specified database/cycle, with their metadata and extracted raw variable names. +#' +#' @param cycle Character string specifying the database/cycle (e.g., "cycle1", +#' "cycle1_meds" for CHMS; "cchs2001", "cchs2017_p" for CCHS). +#' @param variables Data frame from variables.csv containing variable metadata. +#' @param variable_details Data frame from variable_details.csv containing detailed recoding specifications. +#' @param include_derived Logical. Should derived variables be included? Default is TRUE. +#' +#' @return Data frame with columns: +#' \itemize{ +#' \item variable - Harmonized variable name +#' \item variable_raw - Raw source variable name (extracted from variableStart) +#' \item label - Human-readable label +#' \item variableType - "Categorical" or "Continuous" +#' \item databaseStart - Which databases/cycles the variable appears in +#' \item variableStart - Original variableStart string (for reference) +#' } +#' +#' Returns empty data frame if no variables found for the database/cycle. +#' +#' @details +#' The function filters variables.csv by checking if the database/cycle appears +#' in the `databaseStart` field (exact match), then uses \code{\link{parse_variable_start}} +#' to extract the raw variable name from the `variableStart` field. +#' +#' **Important**: Uses exact matching to avoid false positives (e.g., "cycle1" +#' should not match "cycle1_meds"). +#' +#' Derived variables (those with "DerivedVar::" in variableStart) return NA for +#' variable_raw since they require custom derivation logic. +#' +#' @examples +#' \dontrun{ +#' # Load metadata +#' variables <- read.csv("inst/extdata/variables.csv") +#' variable_details <- read.csv("inst/extdata/variable-details.csv") +#' +#' # CHMS example +#' cycle1_vars <- get_cycle_variables("cycle1", variables, variable_details) +#' +#' # CCHS example +#' cchs2001_vars <- get_cycle_variables("cchs2001", variables, variable_details) +#' +#' # Exclude derived variables +#' cycle1_original <- get_cycle_variables("cycle1", variables, variable_details, +#' include_derived = FALSE) +#' } +#' +#' @seealso \code{\link{parse_variable_start}} +#' +#' @family mockdata-helpers +#' @export +get_cycle_variables <- function(cycle, variables, variable_details, + include_derived = TRUE) { + # Basic validation + if (is.null(cycle) || cycle == "") { + return(data.frame( + variable = character(), + variable_raw = character(), + label = character(), + variableType = character(), + databaseStart = character(), + variableStart = character(), + stringsAsFactors = FALSE + )) + } + + # Filter variables by cycle using EXACT match + # Split databaseStart by comma and check for exact cycle match + # This prevents "cycle1" from matching "cycle1_meds" + cycle_vars <- variables[sapply(variables$databaseStart, function(db_start) { + cycles <- strsplit(db_start, ",")[[1]] + cycles <- trimws(cycles) + cycle %in% cycles + }), ] + + # If no variables found, return empty data frame + if (nrow(cycle_vars) == 0) { + return(data.frame( + variable = character(), + variable_raw = character(), + label = character(), + variableType = character(), + databaseStart = character(), + variableStart = character(), + stringsAsFactors = FALSE + )) + } + + # Extract raw variable names using parse_variable_start + cycle_vars$variable_raw <- sapply(cycle_vars$variableStart, function(vs) { + raw_name <- parse_variable_start(vs, cycle) + if (is.null(raw_name)) return(NA_character_) + return(raw_name) + }) + + # Filter out derived variables if requested + if (!include_derived) { + cycle_vars <- cycle_vars[!grepl("DerivedVar::", cycle_vars$variableStart, fixed = TRUE), ] + } + + # Select and return relevant columns + result <- data.frame( + variable = cycle_vars$variable, + variable_raw = cycle_vars$variable_raw, + label = cycle_vars$label, + variableType = cycle_vars$variableType, + databaseStart = cycle_vars$databaseStart, + variableStart = cycle_vars$variableStart, + stringsAsFactors = FALSE + ) + + return(result) +} + + +#' Get list of unique raw variables for a database/cycle +#' +#' Returns a data frame of unique raw (source) variables that should be generated +#' for a specific database/cycle. This is the correct approach for generating mock +#' data, as we want to create the raw source data, not the harmonized variables. +#' +#' @param cycle Character string specifying the database/cycle (e.g., "cycle1", +#' "cycle1_meds" for CHMS; "cchs2001" for CCHS). +#' @param variables Data frame from variables.csv containing variable metadata. +#' @param variable_details Data frame from variable_details.csv containing detailed specifications. +#' @param include_derived Logical. Should derived variables be included? Default is FALSE +#' (since derived variables are computed from other variables, not in raw data). +#' +#' @return Data frame with columns: +#' \itemize{ +#' \item variable_raw - Raw source variable name (unique) +#' \item variableType - "Categorical" or "Continuous" +#' \item harmonized_vars - Comma-separated list of harmonized variables that use this raw variable +#' \item n_harmonized - Count of how many harmonized variables use this raw variable +#' } +#' +#' @details +#' This function: +#' \enumerate{ +#' \item Gets all variables available in the database/cycle using \code{\link{get_cycle_variables}} +#' \item Extracts unique raw variable names +#' \item Groups harmonized variables by their raw source +#' \item Returns one row per unique raw variable +#' } +#' +#' This is the correct approach because: +#' \itemize{ +#' \item Mock data should represent raw source data (before harmonization) +#' \item Each raw variable should appear exactly once +#' \item Multiple harmonized variables can derive from the same raw variable +#' } +#' +#' @examples +#' \dontrun{ +#' # Load metadata +#' variables <- read.csv("inst/extdata/variables.csv") +#' variable_details <- read.csv("inst/extdata/variable-details.csv") +#' +#' # CHMS example +#' raw_vars <- get_raw_variables("cycle1", variables, variable_details) +#' +#' # CCHS example +#' raw_vars_cchs <- get_raw_variables("cchs2001", variables, variable_details) +#' +#' # Generate mock data from raw variables +#' for (i in 1:nrow(raw_vars)) { +#' var_raw <- raw_vars$variable_raw[i] +#' var_type <- raw_vars$variableType[i] +#' # Generate the raw variable... +#' } +#' } +#' +#' @seealso \code{\link{get_cycle_variables}}, \code{\link{parse_variable_start}} +#' +#' @family mockdata-helpers +#' @export +get_raw_variables <- function(cycle, variables, variable_details, + include_derived = FALSE) { + # Get all cycle variables (harmonized) + cycle_vars <- get_cycle_variables(cycle, variables, variable_details, + include_derived = include_derived) + + # Remove rows with NA raw variable names (e.g., DerivedVar that couldn't be parsed) + cycle_vars <- cycle_vars[!is.na(cycle_vars$variable_raw), ] + + # If no variables, return empty data frame + if (nrow(cycle_vars) == 0) { + return(data.frame( + variable_raw = character(), + variableType = character(), + harmonized_vars = character(), + n_harmonized = integer(), + stringsAsFactors = FALSE + )) + } + + # Group by raw variable name + # For each unique raw variable, collect the harmonized variables that use it + raw_var_list <- unique(cycle_vars$variable_raw) + + result <- lapply(raw_var_list, function(raw_var) { + # Find all harmonized variables that map to this raw variable + matching_rows <- cycle_vars[cycle_vars$variable_raw == raw_var, ] + + # Get variable type (should be same for all harmonized vars using this raw var) + var_type <- matching_rows$variableType[1] + + # Get list of harmonized variable names + harmonized_list <- matching_rows$variable + + data.frame( + variable_raw = raw_var, + variableType = var_type, + harmonized_vars = paste(harmonized_list, collapse = ", "), + n_harmonized = length(harmonized_list), + stringsAsFactors = FALSE + ) + }) + + # Combine into single data frame + result_df <- do.call(rbind, result) + + # Sort by variable name for consistency + result_df <- result_df[order(result_df$variable_raw), ] + rownames(result_df) <- NULL + + return(result_df) +} diff --git a/R/read_mock_data_config.R b/R/read_mock_data_config.R new file mode 100644 index 0000000..847cc8a --- /dev/null +++ b/R/read_mock_data_config.R @@ -0,0 +1,180 @@ +#' Read and validate MockData configuration file defining variable specifications for mock data generation +#' +#' @description +#' Reads a mock_data_config.csv file containing variable definitions for +#' mock data generation. Optionally validates the configuration against +#' schema requirements. +#' +#' @param config_path Character. Path to mock_data_config.csv file. +#' @param validate Logical. Whether to validate the configuration (default TRUE). +#' +#' @return Data frame with configuration variables and their parameters, +#' sorted by position column. +#' +#' @details +#' The configuration file should have the following columns: +#' +#' **Core columns:** +#' - uid: Unique identifier (v_001, v_002, ...) +#' - variable: Variable name +#' - role: Comma-separated role values (enabled, predictor, outcome, etc.) +#' - label: Short label for tables +#' - labelLong: Descriptive label +#' - section: Primary grouping for Table 1 +#' - subject: Secondary grouping +#' - variableType: Data type (categorical, continuous, date, survival, character, integer) +#' - units: Measurement units +#' - position: Sort order (10, 20, 30...) +#' +#' **Provenance columns:** +#' - source_database: Database identifier(s) from import +#' - source_spec: Source specification file +#' - version: Configuration version +#' - last_updated: Date last modified +#' - notes: Documentation +#' - seed: Random seed for reproducibility +#' +#' The function performs the following processing: +#' 1. Reads CSV file with read.csv() +#' 2. Converts date columns to Date type +#' 3. Sorts by position column +#' 4. Validates if validate = TRUE +#' +#' @examples +#' \dontrun{ +#' # Read configuration file +#' config <- read_mock_data_config( +#' "inst/extdata/mock_data_config.csv" +#' ) +#' +#' # Read without validation +#' config <- read_mock_data_config( +#' "inst/extdata/mock_data_config.csv", +#' validate = FALSE +#' ) +#' +#' # View structure +#' str(config) +#' head(config) +#' } +#' +#' @export +read_mock_data_config <- function(config_path, validate = TRUE) { + + # Input validation + if (!file.exists(config_path)) { + stop("Configuration file does not exist: ", config_path) + } + + # Read CSV + config <- read.csv(config_path, stringsAsFactors = FALSE, check.names = FALSE) + + # Type conversions + if ("last_updated" %in% names(config)) { + config$last_updated <- as.Date(config$last_updated) + } + + # Sort by position + if ("position" %in% names(config)) { + config <- config[order(config$position), ] + } + + # Validate if requested + if (validate) { + validate_mock_data_config(config) + } + + return(config) +} + +#' Validate MockData configuration against schema requirements including required columns and unique identifiers +#' +#' @description +#' Validates a mock_data_config data frame against schema requirements. +#' Checks for required columns, unique variable names, valid role values, +#' and valid variableType values. +#' +#' @param config Data frame. Configuration data read from mock_data_config.csv. +#' +#' @return Invisible NULL. Stops with error message if validation fails. +#' +#' @details +#' Validation checks: +#' +#' **Required columns:** +#' - uid, variable, role, variableType, position +#' +#' **Uniqueness:** +#' - uid values must be unique +#' - variable names must be unique +#' +#' **Valid values:** +#' - role: Can contain enabled, predictor, outcome, confounder, exposure, +#' table1, metadata, intermediate (comma-separated) +#' - variableType: categorical, continuous, date, survival, character, integer +#' +#' **Safe NA handling:** +#' - Uses which() to handle NA values in logical comparisons +#' - Prevents "missing value where TRUE/FALSE needed" errors +#' +#' @examples +#' \dontrun{ +#' # Validate configuration +#' config <- read.csv("mock_data_config.csv", stringsAsFactors = FALSE) +#' validate_mock_data_config(config) +#' } +#' +#' @export +validate_mock_data_config <- function(config) { + + # Check required columns (uid is optional for simple examples) + required_cols <- c("variable", "role", "variableType", "position") + missing_cols <- setdiff(required_cols, names(config)) + if (length(missing_cols) > 0) { + stop("Missing required columns in mock_data_config.csv: ", + paste(missing_cols, collapse = ", ")) + } + + # Check unique uid values (if uid column exists) + if ("uid" %in% names(config) && any(duplicated(config$uid))) { + duplicates <- config$uid[duplicated(config$uid)] + stop("Duplicate uid values found in mock_data_config.csv: ", + paste(unique(duplicates), collapse = ", ")) + } + + # Check unique variable names + if (any(duplicated(config$variable))) { + duplicates <- config$variable[duplicated(config$variable)] + stop("Duplicate variable names found in mock_data_config.csv: ", + paste(unique(duplicates), collapse = ", ")) + } + + # Check valid variableType values (case-insensitive) + valid_types <- c("categorical", "continuous", "date", "survival", + "character", "integer") + invalid_types <- which(!tolower(config$variableType) %in% c(tolower(valid_types), NA)) + if (length(invalid_types) > 0) { + bad_values <- unique(config$variableType[invalid_types]) + stop("Invalid variableType values in mock_data_config.csv: ", + paste(bad_values, collapse = ", "), + "\nValid values: ", paste(valid_types, collapse = ", ")) + } + + # Check position values are positive + invalid_positions <- which(config$position <= 0) + if (length(invalid_positions) > 0) { + stop("Position values must be positive. Invalid rows: ", + paste(config$variable[invalid_positions], collapse = ", ")) + } + + # Validate role values (flexible - just check for common patterns) + # Role can be comma-separated, so we don't enforce strict values + # Just warn if role is NA + na_roles <- which(is.na(config$role) | config$role == "") + if (length(na_roles) > 0) { + warning("Some variables have missing role values (rows: ", + paste(config$variable[na_roles], collapse = ", "), ")") + } + + invisible(NULL) +} diff --git a/R/read_mock_data_config_details.R b/R/read_mock_data_config_details.R new file mode 100644 index 0000000..c85e5d1 --- /dev/null +++ b/R/read_mock_data_config_details.R @@ -0,0 +1,259 @@ +#' Read and validate MockData configuration details file containing distribution parameters and category proportions +#' +#' @description +#' Reads a mock_data_config_details.csv file containing distribution parameters +#' and proportions for mock data generation. Optionally validates the details +#' against schema requirements and optionally against a config file. +#' +#' @param details_path Character. Path to mock_data_config_details.csv file. +#' @param validate Logical. Whether to validate the details (default TRUE). +#' @param config Data frame (optional). Configuration from read_mock_data_config() +#' for cross-validation of variable references. +#' +#' @return Data frame with detail rows for each variable's distribution parameters. +#' +#' @details +#' The details file should have the following columns: +#' +#' **Link columns:** +#' - uid: Links to mock_data_config.csv via uid (variable-level) +#' - uid_detail: Unique identifier for this detail row (d_001, d_002, ...) +#' - variable: Variable name (denormalized for readability) +#' +#' **Category/parameter columns:** +#' - dummyVariable: Recodeflow dummy variable identifier +#' - recStart: Category value or range notation `[min,max]` +#' - catLabel: Short category label +#' - catLabelLong: Long category label +#' - units: Measurement units for this parameter +#' +#' **Distribution parameters:** +#' - proportion: Proportion for this category (0-1) +#' - value: Numeric value +#' - range_min, range_max: Value ranges +#' - notes: Implementation notes +#' +#' The function performs the following processing: +#' 1. Reads CSV file with read.csv() +#' 2. Converts numeric columns (proportion, value, ranges) +#' 3. Validates if validate = TRUE +#' +#' @examples +#' \dontrun{ +#' # Read details file +#' details <- read_mock_data_config_details( +#' "inst/extdata/mock_data_config_details.csv" +#' ) +#' +#' # Read with cross-validation against config +#' config <- read_mock_data_config("inst/extdata/mock_data_config.csv") +#' details <- read_mock_data_config_details( +#' "inst/extdata/mock_data_config_details.csv", +#' config = config +#' ) +#' +#' # View structure +#' str(details) +#' head(details) +#' } +#' +#' @export +read_mock_data_config_details <- function(details_path, validate = TRUE, config = NULL) { + + # Input validation + if (!file.exists(details_path)) { + stop("Details file does not exist: ", details_path) + } + + # Read CSV + details <- read.csv(details_path, stringsAsFactors = FALSE, check.names = FALSE) + + # Type conversions + numeric_cols <- c("proportion", "value") + for (col in numeric_cols) { + if (col %in% names(details)) { + details[[col]] <- as.numeric(details[[col]]) + } + } + + # Validate if requested + if (validate) { + validate_mock_data_config_details(details, config = config) + } + + return(details) +} + +#' Validate MockData configuration details against schema requirements including proportion sums and parameter completeness +#' +#' @description +#' Validates a mock_data_config_details data frame against schema requirements. +#' Checks for required columns, valid proportions, proportion sums, parameter +#' requirements, and optionally validates links to config file. +#' +#' @param details Data frame. Details data read from mock_data_config_details.csv. +#' @param config Data frame (optional). Configuration for cross-validation. +#' +#' @return Invisible NULL. Stops with error message if validation fails. +#' +#' @details +#' Validation checks: +#' +#' **Required columns:** +#' - variable, recStart (always required) +#' - recEnd (conditionally required when using missing data codes 6-9, 96-99) +#' - uid, uid_detail (optional for simple examples) +#' +#' **Conditional recEnd requirement:** +#' - recEnd column required when recStart contains missing codes (6-9, 96-99) +#' - Enables classification: NA::a (skip), NA::b (missing), numeric (valid) +#' - Without recEnd, missing vs. valid codes cannot be distinguished +#' +#' **Uniqueness:** +#' - uid_detail values must be unique (if column present) +#' +#' **Proportion validation:** +#' - Values must be in range `[0, 1]` +#' - Population proportions (valid + missing codes) must sum to 1.0 Β±0.001 per variable +#' - Contamination proportions (corrupt_*) are excluded from sum +#' - Auto-normalizes with warning if sum β‰  1.0 +#' +#' **Parameter validation:** +#' - Distribution-specific requirements: +#' - normal β†’ mean + sd +#' - gompertz β†’ rate + shape +#' - exponential β†’ rate +#' - poisson β†’ rate +#' +#' **Link validation (if config provided):** +#' - All uid values must exist in config$uid +#' +#' **Flexible recEnd validation:** +#' - Warns but doesn't error on unknown recEnd values +#' +#' @examples +#' \dontrun{ +#' # Validate details +#' details <- read.csv("mock_data_config_details.csv", stringsAsFactors = FALSE) +#' validate_mock_data_config_details(details) +#' +#' # Validate with cross-check against config +#' config <- read.csv("mock_data_config.csv", stringsAsFactors = FALSE) +#' validate_mock_data_config_details(details, config = config) +#' } +#' +#' @export +validate_mock_data_config_details <- function(details, config = NULL) { + + # Check required columns (uid and uid_detail are optional for simple examples) + required_cols <- c("variable", "recStart") + missing_cols <- setdiff(required_cols, names(details)) + if (length(missing_cols) > 0) { + stop("Missing required columns in mock_data_config_details.csv: ", + paste(missing_cols, collapse = ", ")) + } + + # Conditional recEnd requirement: check for missing data codes + # recEnd is required when there are rows with typical missing codes (6-9, 96-99) + # because these need explicit classification as NA::a (skip) or NA::b (missing) + missing_codes <- c("6", "7", "8", "9", "96", "97", "98", "99") + has_missing_codes <- any(details$recStart %in% missing_codes) + + # Also check for range notation that includes missing codes: [7,9] for example + has_missing_ranges <- any(grepl("\\[(6|7|8|9|96|97|98|99)", details$recStart)) + + if ((has_missing_codes || has_missing_ranges) && !"recEnd" %in% names(details)) { + stop("recEnd column required in variable_details when using missing data codes (6-9, 96-99).\n", + " Use 'NA::a' for skip codes (6, 96, 996),\n", + " Use 'NA::b' for missing codes (7-9, 97-99) representing DK/Refusal/NS,\n", + " and numeric codes (e.g., '1', '2', '3') for valid responses.") + } + + # Check unique uid_detail values (if uid_detail column exists) + if ("uid_detail" %in% names(details) && any(duplicated(details$uid_detail))) { + duplicates <- details$uid_detail[duplicated(details$uid_detail)] + stop("Duplicate uid_detail values found in mock_data_config_details.csv: ", + paste(unique(duplicates), collapse = ", ")) + } + + # Validate proportions are in valid range + if ("proportion" %in% names(details)) { + invalid_props <- which(!is.na(details$proportion) & + (details$proportion < 0 | details$proportion > 1)) + if (length(invalid_props) > 0) { + bad_rows <- details$uid_detail[invalid_props] + stop("Proportion values must be between 0 and 1. Invalid rows: ", + paste(bad_rows, collapse = ", ")) + } + } + + # Check proportions sum to 1.0 per variable (excluding garbage rows) + if ("proportion" %in% names(details)) { + # Group by variable + vars <- unique(details$variable) + for (var in vars) { + var_rows <- details[details$variable == var, ] + + # Exclude garbage rows (corrupt_*) + pop_rows <- var_rows[!grepl("^corrupt_", var_rows$recStart, ignore.case = TRUE), ] + + # Calculate sum of population proportions (excluding NA) + prop_sum <- sum(pop_rows$proportion, na.rm = TRUE) + + # Check if we have any non-NA proportions + has_proportions <- any(!is.na(pop_rows$proportion)) + + if (has_proportions) { + tolerance <- 0.001 + if (abs(prop_sum - 1.0) > tolerance) { + warning("Proportions for variable '", var, "' sum to ", + round(prop_sum, 4), " (expected 1.0). ", + "Auto-normalizing proportions.") + + # Auto-normalize + norm_factor <- 1.0 / prop_sum + pop_idx <- which(details$variable == var & + !grepl("^corrupt_", details$recStart, ignore.case = TRUE) & + !is.na(details$proportion)) + details$proportion[pop_idx] <- details$proportion[pop_idx] * norm_factor + } + } + } + } + + # Link validation: check all uids exist in config + if (!is.null(config)) { + if (!"uid" %in% names(config)) { + warning("Config file provided but does not have 'uid' column. Skipping link validation.") + } else { + missing_uids <- setdiff(unique(details$uid), config$uid) + if (length(missing_uids) > 0) { + stop("Details file references uids not found in config: ", + paste(missing_uids, collapse = ", ")) + } + } + } + + # Flexible recStart validation (warn on potentially unknown values) + # Common known values + known_recStart <- c("copy", "distribution", "mean", "sd", "rate", "shape", + "valid", "censored", "corrupt_low", "corrupt_high", "corrupt_future", + "followup_min", "followup_max", "event", # Survival parameters + "7", "8", "9", "96", "97", "98", "99", # Missing codes + "-7", "-8", "-9") # Negative missing codes + + # Check for numeric category values (1, 2, 3, etc.) and range notation [min,max] - these are valid + is_numeric_category <- grepl("^[0-9]+$", details$recStart) + is_range_notation <- grepl("^\\[.*,.*\\]$", details$recStart) + is_known <- details$recStart %in% known_recStart | is_numeric_category | is_range_notation + + unknown_recStart <- unique(details$recStart[!is_known]) + if (length(unknown_recStart) > 0) { + # Just inform, don't error (flexible validation) + message("Note: Found recStart values that may be category-specific: ", + paste(head(unknown_recStart, 10), collapse = ", "), + if (length(unknown_recStart) > 10) "..." else "") + } + + invisible(NULL) +} diff --git a/R/scalar_helpers.R b/R/scalar_helpers.R new file mode 100644 index 0000000..b47ca68 --- /dev/null +++ b/R/scalar_helpers.R @@ -0,0 +1,180 @@ +#' Scalar Variable Generation Helpers +#' +#' Helper functions for scalar variable generation (single variables at a time). +#' Used by create_cat_var(), create_con_var(), create_date_var() when called +#' with individual variable parameters (var_raw, cycle, etc.) rather than +#' configuration data frames. +#' +#' These helpers work with recodeflow-style metadata (variables.csv + +#' variable_details.csv from cchsflow/chmsflow). + + +#' Get variable details for raw variable and cycle +#' +#' Filters variable_details to rows matching a specific raw variable name and cycle. +#' Handles multiple naming patterns from recodeflow packages. +#' +#' @param var_raw Character. Raw variable name (e.g., "alc_11", "HGT_CM") +#' @param cycle Character. Cycle identifier (e.g., "cycle1", "cchs2001") +#' @param variable_details Data frame. Full variable_details metadata +#' @param variables Data frame. Optional variables metadata (not used currently) +#' +#' @return Data frame subset of variable_details for this variable + cycle +#' +#' @details +#' Tries three matching strategies in order: +#' 1. Database-prefixed format: `"cycle::var_raw"` +#' 2. Bracket format: `"[var_raw]"` with databaseStart filtering +#' 3. Plain format: exact match on variableStart with cycle filtering +#' +#' @keywords internal +get_variable_details_for_raw <- function(var_raw, cycle, variable_details, variables = NULL) { + if (is.null(var_raw) || is.null(cycle) || var_raw == "" || cycle == "") { + return(data.frame( + variable = character(), + variableStart = character(), + databaseStart = character(), + variableType = character(), + recStart = character(), + recEnd = character(), + stringsAsFactors = FALSE + )) + } + + # Strategy 1: Find by database-prefixed format (cycle::var_raw) + cycle_pattern <- paste0(cycle, "::", var_raw) + matches <- variable_details[grepl(cycle_pattern, variable_details$variableStart, fixed = TRUE), ] + + # Strategy 2: Find by bracket format ([var_raw]) with databaseStart filtering + if (nrow(matches) == 0) { + bracket_pattern <- paste0("[", var_raw, "]") + bracket_matches <- variable_details[grepl(bracket_pattern, variable_details$variableStart, fixed = TRUE), ] + + if (nrow(bracket_matches) > 0) { + # Filter by databaseStart to ensure correct cycle + bracket_matches <- bracket_matches[grepl(cycle, bracket_matches$databaseStart, fixed = TRUE), ] + matches <- bracket_matches + } + } + + # Strategy 3: Find by plain format (var_raw) with strict filtering + if (nrow(matches) == 0) { + # Only match if variableStart is EXACTLY the var_raw + plain_matches <- variable_details[ + variable_details$variableStart == var_raw & + grepl(cycle, variable_details$databaseStart, fixed = TRUE), + ] + matches <- plain_matches + } + + return(matches) +} + + +#' Extract categories from variable details +#' +#' Extracts categorical values from variable_details recStart/recEnd columns. +#' Handles range notation, special codes, and missing code patterns. +#' +#' @param var_details Data frame. Filtered variable_details rows +#' @param include_na Logical. Include NA/missing codes (default FALSE) +#' +#' @return Character vector of category values +#' +#' @details +#' Handles recodeflow notation: +#' - Simple categories: "1", "2", "3" +#' - Integer ranges: `"[7,9]"` β†’ c("7", "8", "9") +#' - Continuous ranges: "[18.5,25)" (kept as single value) +#' - Special codes: "copy", "else" (EXCLUDED from mock data generation) +#' - Missing codes: Identified by "NA" in recEnd +#' +#' Note: "else" is excluded because it acts as a garbage collector in +#' harmonization (recodes to NA::b), not a population category for generation. +#' +#' @keywords internal +get_variable_categories <- function(var_details, include_na = FALSE) { + if (nrow(var_details) == 0) { + return(character(0)) + } + + # Check if recEnd column exists + if (!"recEnd" %in% names(var_details)) { + warning("recEnd column not found in variable_details. ", + "Cannot distinguish missing codes (NA::a, NA::b) from valid categories. ", + "Returning empty character vector. ", + "Add recEnd column to variable_details to enable missing data classification.") + return(character(0)) + } + + # Filter based on whether we want NA codes or regular labels + if (include_na) { + # Get rows where recEnd contains "NA" + rows <- var_details[grepl("NA", var_details$recEnd, fixed = TRUE), ] + } else { + # Get rows where recEnd does NOT contain "NA" + rows <- var_details[!grepl("NA", var_details$recEnd, fixed = TRUE), ] + } + + if (nrow(rows) == 0) { + return(character(0)) + } + + # IMPORTANT: Exclude "else" rows (garbage collector that recodes to NA::b) + # "else" is an exception to "recodes to NA::b = missing code" rule + # This matches the exclusion in extract_proportions() for config-driven generation + rows <- rows[rows$recEnd != "else", ] + + if (nrow(rows) == 0) { + return(character(0)) + } + + # Extract recStart values + rec_start_values <- rows$recStart + + # Process each value through parse_range_notation + all_values <- character(0) + + for (value in rec_start_values) { + if (is.na(value) || value == "") { + next + } + + parsed <- parse_range_notation(value) + + if (is.null(parsed)) { + # If parsing failed, use raw value + all_values <- c(all_values, as.character(value)) + next + } + + # Handle different parsed types + if (parsed$type == "integer") { + # For integer ranges, use the expanded values + if (!is.null(parsed$values)) { + all_values <- c(all_values, as.character(parsed$values)) + } else { + # If values not expanded, just use min-max representation + all_values <- c(all_values, as.character(value)) + } + } else if (parsed$type == "single_value") { + # Single numeric value + all_values <- c(all_values, as.character(parsed$value)) + } else if (parsed$type == "continuous") { + # For continuous ranges, keep as-is (don't expand) + all_values <- c(all_values, as.character(value)) + } else if (parsed$type == "special") { + # Skip special codes (copy, else, Func::, etc.) + next + } else if (parsed$type == "function") { + # Skip function calls + next + } else { + # Unknown type, use raw value + all_values <- c(all_values, as.character(value)) + } + } + + # Return unique values + return(unique(all_values)) +} diff --git a/R/util.R b/R/util.R deleted file mode 100644 index 700cdae..0000000 --- a/R/util.R +++ /dev/null @@ -1,9 +0,0 @@ -library(stringr) -# utility functions - -# unpack the ranges in `recStart` -unpack_range <- function(range) { - range_num <- as.numeric(unlist(str_extract_all(range, "\\d+"))) - vec <- seq(range_num[1], range_num[2]) - return(as.character(vec)) -} diff --git a/R/validate_mockdata_extensions.R b/R/validate_mockdata_extensions.R new file mode 100644 index 0000000..16f175e --- /dev/null +++ b/R/validate_mockdata_extensions.R @@ -0,0 +1,441 @@ +#' Validate MockData Extension Fields +#' +#' @param variables_path Path to variables.csv file +#' @param variable_details_path Path to variable_details.csv file +#' @param mode Validation mode: "basic" or "strict" (default: "basic") +#' @return Validation result object with errors, warnings, and info +#' @export +validate_mockdata_metadata <- function(variables_path, variable_details_path, mode = "basic") { + result <- list( + files = list( + variables = basename(variables_path), + variable_details = basename(variable_details_path) + ), + mode = mode, + timestamp = Sys.time(), + + # Validation components + uid_validation = list(), + proportion_validation = list(), + garbage_validation = list(), + rType_validation = list(), + versioning_validation = list(), + foreign_key_validation = list(), + + # Issues + errors = character(0), + warnings = character(0), + info = character(0), + + # Summary + valid = TRUE, + issues_count = 0 + ) + + # Check files exist + if (!file.exists(variables_path)) { + result$errors <- c(result$errors, paste("Variables file not found:", variables_path)) + result$valid <- FALSE + return(result) + } + + if (!file.exists(variable_details_path)) { + result$errors <- c(result$errors, paste("Variable details file not found:", variable_details_path)) + result$valid <- FALSE + return(result) + } + + # Load data + variables <- read.csv(variables_path, stringsAsFactors = FALSE, check.names = FALSE) + variable_details <- read.csv(variable_details_path, stringsAsFactors = FALSE, check.names = FALSE) + + # 1. UID validation (numeric-only pattern) + result$uid_validation <- validate_uids(variables, variable_details) + + # 2. rType validation (enum values) + result$rType_validation <- validate_rtype(variables) + + # 3. Foreign key validation (uid linkage) + result$foreign_key_validation <- validate_foreign_keys(variables, variable_details) + + # 4. Proportion validation (sum to 1.0 per variable) + result$proportion_validation <- validate_proportions(variable_details, mode) + + # 5. Garbage data validation (interval notation, 0-1 range) + result$garbage_validation <- validate_garbage(variables) + + # 6. Versioning validation (semantic versioning pattern) + result$versioning_validation <- validate_versioning(variables) + + # Collect all issues + all_validations <- list( + result$uid_validation, + result$rType_validation, + result$foreign_key_validation, + result$proportion_validation, + result$garbage_validation, + result$versioning_validation + ) + + for (validation in all_validations) { + if (!is.null(validation)) { + result$errors <- c(result$errors, validation$errors) + result$warnings <- c(result$warnings, validation$warnings) + result$info <- c(result$info, validation$info) + } + } + + # Summary + result$issues_count <- length(result$errors) + length(result$warnings) + result$valid <- length(result$errors) == 0 + + class(result) <- "mockdata_validation_result" + return(result) +} + +#' Validate UID Patterns +#' @keywords internal +validate_uids <- function(variables, variable_details) { + result <- list(errors = character(0), warnings = character(0), info = character(0)) + + # Pattern for variable-level UIDs: ^v_[0-9]+$ + uid_pattern <- "^v_[0-9]+$" + + # Pattern for detail-level UIDs: ^d_[0-9]+$ + uid_detail_pattern <- "^d_[0-9]+$" + + # Check variables.csv uid column + if ("uid" %in% names(variables)) { + non_empty_uids <- variables$uid[!is.na(variables$uid) & variables$uid != ""] + + if (length(non_empty_uids) > 0) { + invalid_uids <- non_empty_uids[!grepl(uid_pattern, non_empty_uids)] + + if (length(invalid_uids) > 0) { + result$errors <- c(result$errors, + paste("Invalid uid format in variables.csv (expected ^v_[0-9]+$):", + paste(invalid_uids, collapse = ", "))) + } + + # Check uniqueness + duplicates <- sum(duplicated(non_empty_uids)) + if (duplicates > 0) { + result$errors <- c(result$errors, + paste("Duplicate uid values in variables.csv:", duplicates, "duplicates found")) + } + } + } else { + result$warnings <- c(result$warnings, "No uid column found in variables.csv") + } + + # Check variable_details.csv uid and uid_detail columns + if ("uid" %in% names(variable_details)) { + non_empty_uids <- variable_details$uid[!is.na(variable_details$uid) & variable_details$uid != ""] + + if (length(non_empty_uids) > 0) { + invalid_uids <- non_empty_uids[!grepl(uid_pattern, non_empty_uids)] + + if (length(invalid_uids) > 0) { + result$errors <- c(result$errors, + paste("Invalid uid format in variable_details.csv (expected ^v_[0-9]+$):", + paste(unique(invalid_uids), collapse = ", "))) + } + } + } else { + result$warnings <- c(result$warnings, "No uid column found in variable_details.csv") + } + + if ("uid_detail" %in% names(variable_details)) { + non_empty_uid_details <- variable_details$uid_detail[!is.na(variable_details$uid_detail) & + variable_details$uid_detail != ""] + + if (length(non_empty_uid_details) > 0) { + invalid_uid_details <- non_empty_uid_details[!grepl(uid_detail_pattern, non_empty_uid_details)] + + if (length(invalid_uid_details) > 0) { + result$errors <- c(result$errors, + paste("Invalid uid_detail format (expected ^d_[0-9]+$):", + paste(invalid_uid_details, collapse = ", "))) + } + + # Check uniqueness + duplicates <- sum(duplicated(non_empty_uid_details)) + if (duplicates > 0) { + result$errors <- c(result$errors, + paste("Duplicate uid_detail values:", duplicates, "duplicates found")) + } + } + } else { + result$warnings <- c(result$warnings, "No uid_detail column found in variable_details.csv") + } + + return(result) +} + +#' Validate rType Values +#' @keywords internal +validate_rtype <- function(variables) { + result <- list(errors = character(0), warnings = character(0), info = character(0)) + + valid_rtypes <- c("integer", "double", "factor", "logical", "character", "date") + + if ("rType" %in% names(variables)) { + non_empty_rtypes <- variables$rType[!is.na(variables$rType) & variables$rType != ""] + + if (length(non_empty_rtypes) > 0) { + invalid_rtypes <- setdiff(unique(non_empty_rtypes), valid_rtypes) + + if (length(invalid_rtypes) > 0) { + result$errors <- c(result$errors, + paste("Invalid rType values:", paste(invalid_rtypes, collapse = ", "))) + result$info <- c(result$info, + paste("Valid rType values:", paste(valid_rtypes, collapse = ", "))) + } + } + } else { + result$info <- c(result$info, "No rType column found in variables.csv (optional)") + } + + return(result) +} + +#' Validate Foreign Key Relationships +#' @keywords internal +validate_foreign_keys <- function(variables, variable_details) { + result <- list(errors = character(0), warnings = character(0), info = character(0)) + + if ("uid" %in% names(variables) && "uid" %in% names(variable_details)) { + var_uids <- variables$uid[!is.na(variables$uid) & variables$uid != ""] + detail_uids <- variable_details$uid[!is.na(variable_details$uid) & variable_details$uid != ""] + + # Check for UIDs in variable_details that don't exist in variables + orphan_uids <- setdiff(unique(detail_uids), var_uids) + + if (length(orphan_uids) > 0) { + result$errors <- c(result$errors, + paste("UIDs in variable_details.csv not found in variables.csv:", + paste(orphan_uids, collapse = ", "))) + } + + # Info: variables without details + unused_uids <- setdiff(var_uids, detail_uids) + if (length(unused_uids) > 0) { + result$info <- c(result$info, + paste("Variables without detail rows:", paste(unused_uids, collapse = ", "))) + } + } + + return(result) +} + +#' Validate Proportion Sums +#' @keywords internal +validate_proportions <- function(variable_details, mode) { + result <- list(errors = character(0), warnings = character(0), info = character(0)) + + tolerance <- 0.001 # +/-0.001 as specified in schema + + if ("proportion" %in% names(variable_details) && "uid" %in% names(variable_details)) { + # Filter to rows with proportions + prop_rows <- variable_details[!is.na(variable_details$proportion) & + variable_details$proportion != "" & + !is.na(variable_details$uid) & + variable_details$uid != "", ] + + if (nrow(prop_rows) > 0) { + # Convert proportion to numeric if needed + prop_rows$proportion <- as.numeric(prop_rows$proportion) + + # Check each variable's proportions sum + for (uid in unique(prop_rows$uid)) { + uid_props <- prop_rows$proportion[prop_rows$uid == uid] + prop_sum <- sum(uid_props, na.rm = TRUE) + + # Check if sum is close to 1.0 + if (abs(prop_sum - 1.0) > tolerance) { + if (mode == "strict") { + result$errors <- c(result$errors, + sprintf("Proportions for %s sum to %.4f (expected 1.0 +/-%.3f)", + uid, prop_sum, tolerance)) + } else { + result$warnings <- c(result$warnings, + sprintf("Proportions for %s sum to %.4f (will be auto-normalized to 1.0)", + uid, prop_sum)) + } + } + + # Check individual proportion ranges + invalid_props <- uid_props[uid_props < 0 | uid_props > 1] + if (length(invalid_props) > 0) { + result$errors <- c(result$errors, + sprintf("Proportions for %s contain invalid values (must be 0-1): %s", + uid, paste(invalid_props, collapse = ", "))) + } + } + } + } else { + result$info <- c(result$info, "No proportion column found (optional)") + } + + return(result) +} + +#' Validate Garbage Data Parameters +#' @keywords internal +validate_garbage <- function(variables) { + result <- list(errors = character(0), warnings = character(0), info = character(0)) + + interval_pattern <- "^\\[.+;.+\\]$" + + # Check garbage_low_prop + if ("garbage_low_prop" %in% names(variables)) { + non_empty <- variables$garbage_low_prop[!is.na(variables$garbage_low_prop) & + variables$garbage_low_prop != ""] + if (length(non_empty) > 0) { + garbage_low <- as.numeric(non_empty) + invalid <- garbage_low[garbage_low < 0 | garbage_low > 1] + + if (length(invalid) > 0) { + result$errors <- c(result$errors, + paste("garbage_low_prop values must be 0-1:", paste(invalid, collapse = ", "))) + } + } + } + + # Check garbage_low_range + if ("garbage_low_range" %in% names(variables)) { + non_empty <- variables$garbage_low_range[!is.na(variables$garbage_low_range) & + variables$garbage_low_range != "" & + variables$garbage_low_range != "[;]"] # Allow empty intervals + if (length(non_empty) > 0) { + invalid <- non_empty[!grepl(interval_pattern, non_empty)] + + if (length(invalid) > 0) { + result$errors <- c(result$errors, + paste("garbage_low_range must use interval notation [min;max]:", + paste(invalid, collapse = ", "))) + } + } + } + + # Check garbage_high_prop + if ("garbage_high_prop" %in% names(variables)) { + non_empty <- variables$garbage_high_prop[!is.na(variables$garbage_high_prop) & + variables$garbage_high_prop != ""] + if (length(non_empty) > 0) { + garbage_high <- as.numeric(non_empty) + invalid <- garbage_high[garbage_high < 0 | garbage_high > 1] + + if (length(invalid) > 0) { + result$errors <- c(result$errors, + paste("garbage_high_prop values must be 0-1:", paste(invalid, collapse = ", "))) + } + } + } + + # Check garbage_high_range + if ("garbage_high_range" %in% names(variables)) { + non_empty <- variables$garbage_high_range[!is.na(variables$garbage_high_range) & + variables$garbage_high_range != "" & + variables$garbage_high_range != "[;]"] # Allow empty intervals + if (length(non_empty) > 0) { + invalid <- non_empty[!grepl(interval_pattern, non_empty)] + + if (length(invalid) > 0) { + result$errors <- c(result$errors, + paste("garbage_high_range must use interval notation [min;max]:", + paste(invalid, collapse = ", "))) + } + } + } + + return(result) +} + +#' Validate MockData Versioning Fields +#' @keywords internal +validate_versioning <- function(variables) { + result <- list(errors = character(0), warnings = character(0), info = character(0)) + + semver_pattern <- "^[0-9]+\\.[0-9]+\\.[0-9]+$" + date_pattern <- "^[0-9]{4}-[0-9]{2}-[0-9]{2}$" + + # Check mockDataVersion + if ("mockDataVersion" %in% names(variables)) { + non_empty <- variables$mockDataVersion[!is.na(variables$mockDataVersion) & + variables$mockDataVersion != ""] + if (length(non_empty) > 0) { + invalid <- non_empty[!grepl(semver_pattern, non_empty)] + + if (length(invalid) > 0) { + result$warnings <- c(result$warnings, + paste("mockDataVersion should use semantic versioning (e.g., 1.0.0):", + paste(invalid, collapse = ", "))) + } + } + } + + # Check mockDataLastUpdated + if ("mockDataLastUpdated" %in% names(variables)) { + non_empty <- variables$mockDataLastUpdated[!is.na(variables$mockDataLastUpdated) & + variables$mockDataLastUpdated != ""] + if (length(non_empty) > 0) { + invalid <- non_empty[!grepl(date_pattern, non_empty)] + + if (length(invalid) > 0) { + result$warnings <- c(result$warnings, + paste("mockDataLastUpdated should use YYYY-MM-DD format:", + paste(invalid, collapse = ", "))) + } + } + } + + return(result) +} + +#' Print MockData Validation Results +#' +#' @param x mockdata_validation_result object +#' @param ... Additional arguments (unused) +#' @export +print.mockdata_validation_result <- function(x, ...) { + cat("MockData Extension Validation Report\n") + cat("=====================================\n") + cat("Files:\n") + cat(" Variables:", x$files$variables, "\n") + cat(" Details:", x$files$variable_details, "\n") + cat("Mode:", x$mode, "\n") + cat("Timestamp:", format(x$timestamp), "\n\n") + + cat("Validation Summary:\n") + cat("- Valid:", ifelse(x$valid, "YES", "NO"), "\n") + cat("- Errors:", length(x$errors), "\n") + cat("- Warnings:", length(x$warnings), "\n") + cat("- Info:", length(x$info), "\n\n") + + if (length(x$errors) > 0) { + cat("ERRORS:\n") + for (i in seq_along(x$errors)) { + cat(sprintf("%d. %s\n", i, x$errors[i])) + } + cat("\n") + } + + if (length(x$warnings) > 0) { + cat("WARNINGS:\n") + for (i in seq_along(x$warnings)) { + cat(sprintf("%d. %s\n", i, x$warnings[i])) + } + cat("\n") + } + + if (length(x$info) > 0) { + cat("INFO:\n") + for (i in seq_along(x$warnings)) { + cat(sprintf("%d. %s\n", i, x$info[i])) + } + cat("\n") + } + + invisible(x) +} diff --git a/README.md b/README.md new file mode 100644 index 0000000..a412163 --- /dev/null +++ b/README.md @@ -0,0 +1,245 @@ +# MockData + +::: {.vignette-about} +Generate realistic test data from `recodeflow` variable configuration files (`variables.csv` and `variable-details.csv`). +::: + +30-second example + +```r +library(MockData) + +# Generate mock data from metadata files +mock_data <- create_mock_data( + databaseStart = "minimal-example", + variables = system.file("extdata/minimal-example/variables.csv", package = "MockData"), + variable_details = system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + n = 100, + seed = 123 +) + +head(mock_data) +#> age smoking interview_date +#> 1 42 2 2001-08-05 +#> 2 47 2 2002-11-27 +#> 3 73 3 2002-11-14 +#> 4 51 1 2005-01-14 +#> 5 52 1 2001-02-25 +#> 6 76 3 2004-07-25 +``` + +**What's in those CSV files?** See [inst/extdata/minimal-example/](inst/extdata/minimal-example/README.md) - just variable names, types, and ranges. Total 9 rows across 2 files. + +**Why use variable metadata files?** + +Two paths: + +1. **Already using recodeflow?** Use MockData with your existing `variables.csv` and `variable_details.csv` files. No duplicate specifications needed. +2. **New to metadata?** Upfront cost to create configuration files, but you get reproducible data pipelines and documentation that stays in sync with your code. + +## What is mock data? + +In this package, "mock data" refers to metadata-driven simulated data created solely for software testing and workflow validation. Mock data are generated from variable specifications and contain **no real person-level data** or identifiable information. + +**Key distinctions:** + +- **Mock data** (this package): Generated from metadata only. Mimics variable structure and ranges but not real-world statistical relationships. Used for testing pipelines, not analysis. +- **Synthetic data**: Preserves statistical properties and relationships from real datasets through generative models. May be used for research when properly validated. +- **Dummy data**: Placeholder or minimal test data, often hardcoded or randomly generated without metadata constraints. + +MockData creates data that *looks* realistic (appropriate variable types, value ranges, category labels, tagged NAs) but has **no relationship to any actual population**. Joint distributions and correlations may differ significantly from real-world data. + +### Use cases + +**Appropriate uses:** + +- Workflow testing and data pipeline validation +- Data harmonisation logic checks (cchsflow, chmsflow) +- Developing analysis scripts before data access +- Creating reproducible examples for documentation +- Training new analysts on survey data structure + +**Not appropriate for:** + +- Population inference or epidemiological modelling +- Predictive algorithm training +- Statistical analysis or research publication +- Any use requiring realistic joint distributions or correlations + +### Privacy and ethics + +Generated mock data contain **no personal information or individual-level identifiers**. All data are created synthetically from metadata specifications, ensuring negligible risk of re-identification. This approach supports responsible, ethical, and reproducible public-health software development. + +## Features + +- **Metadata-driven**: Uses existing `variables.csv` and `variable_details.csv` from recodeflow projects +- **Universal**: Works across CHMS, CCHS, and future recodeflow projects +- **Recodeflow-standard**: Supports all recodeflow notation formats (database-prefixed, bracket, mixed) +- **Data quality testing**: Generate invalid/out-of-range values to test validation pipelines +- **Validation**: Tools to check metadata quality + +## Installation + +```r +# Install from local directory +devtools::install_local("~/github/mock-data") + +# Or install from GitHub (once published) +# devtools::install_github("Big-Life-Lab/MockData") +``` + +**Note**: Package vignettes are in Quarto format (.qmd). To build vignettes locally, you need [Quarto](https://quarto.org/) installed. + +## Next steps + +**Tutorials:** + +- [Getting started](vignettes/getting-started.qmd) - Complete tutorial from single variables to full datasets +- [For recodeflow users](vignettes/for-recodeflow-users.qmd) - Using MockData with existing metadata +- [Survival data](vignettes/survival-data.qmd) - Time-to-event data and temporal patterns + +**Examples:** + +- [Minimal example](inst/extdata/minimal-example/README.md) - Simplest possible metadata configuration +- [CCHS example](vignettes/cchs-example.qmd) - CCHS workflow demonstration +- [CHMS example](vignettes/chms-example.qmd) - CHMS workflow demonstration + +## Configuration architecture + +MockData uses a three-file architecture that separates project data dictionaries, study specifications, and MockData-specific parameters: + +### File structure + +1. **Project data dictionary** (`variables.csv`) + + - Variable names, labels, types, role flags + - Shared across analysis projects + - Example: `variable, variableType, label` +2. **Study specifications** (`variable_details.csv`) + + - Study date ranges, follow-up periods + - Category definitions and value ranges + - Transformation rules (recStart, recEnd, copy, catLabel) + - Example: `uvariable, recStart, catLabel` +3. **MockData-specific parameters** (`mock_config.csv`, optional) + + - Proportions of variable categories + - Event occurrence probabilities (`event_occurs`) + - Distribution parameters (`distribution`) + - Garbage data proportions (`prop_invalid`) + - Advanced features (survival data, data quality testing) + +This separation allows MockData to read existing recodeflow metadata files without modification, while supporting optional MockData-specific configurations when needed. + +## Contributing + +This package is part of the recodeflow ecosystem. See [CONTRIBUTING.md](CONTRIBUTING.md) for details. + +## License + +MIT License - see [LICENSE](LICENSE) file for details. + +## The recodeflow universe + +MockData is part of the **recodeflow universe** β€” a metadata-driven approach to variable recoding and harmonisation. The core philosophy is to define variable transformations once in metadata files, then reuse those definitions for harmonisation, documentation, and mock data generation. + +**Design principles:** + +- **Metadata-driven**: Variable definitions and recode rules live in structured metadata (CSV files) +- **Reusable**: Same metadata drives harmonisation code, documentation, and testing data +- **Survey-focused**: Built for health surveys (CCHS, CHMS) but applicable to any categorical/continuous data +- **Open and reproducible**: Transparent recode logic that anyone can inspect and verify + +**Related packages:** + +- [**cchsflow**](https://github.com/Big-Life-Lab/cchsflow): Harmonisation workflows for Canadian Community Health Survey (CCHS) +- [**chmsflow**](https://github.com/Big-Life-Lab/chmsflow): Harmonisation workflows for Canadian Health Measures Survey (CHMS) +- [**recodeflow**](https://github.com/Big-Life-Lab/recodeflow): Core metadata specifications and utilities + +## Data sources and acknowledgements + +The example metadata in this package is derived from: + +- **Canadian Community Health Survey (CCHS)** β€” Statistics Canada +- **Canadian Health Measures Survey (CHMS)** β€” Statistics Canada + +**Statistics Canada Open License:** + +The use of CCHS and CHMS metadata examples in this package falls under Statistics Canada's Open License, which permits use, reproduction, and distribution of Statistics Canada data products. We acknowledge Statistics Canada as the source of the survey designs and variable definitions that informed our example metadata files. + +**Important:** This package generates **mock data only**. It does not contain, distribute, or provide access to any actual Statistics Canada microdata. Real CCHS and CHMS data are available through Statistics Canada's Research Data Centres (RDCs) and Public Use Microdata Files (PUMFs) under appropriate data access agreements. + +For more information: [Statistics Canada Open License](https://www.statcan.gc.ca/en/reference/licence) + +## Development environment setup + +This package uses [renv](https://rstudio.github.io/renv/) for reproducible package development environments. + +### For new contributors + +After cloning the repository: + +```r +# Restore the package environment (installs all dependencies) +renv::restore() + +# Install the MockData package itself into the renv library +# (Required for building documentation and running tests) +devtools::install(upgrade = 'never') + +# Load the package for development +devtools::load_all() +``` + +### R version compatibility + +- **Supported**: R 4.3.x - 4.4.x +- **Lockfile baseline**: R 4.4.2 (institutional environments typically run 1-2 versions behind current) +- The renv lockfile works across this version range - minor R version differences are handled automatically + +### Daily development workflow + +```r +# Install new packages as normal +install.packages("packagename") + +# After adding dependencies to DESCRIPTION: +devtools::install_dev_deps() # Install updated dependencies +renv::snapshot() # Update lockfile +# Commit the updated renv.lock file + +# Check environment status anytime: +renv::status() +``` + +### Building documentation and site + +```r +# Generate function documentation +devtools::document() + +# Install the package (required before building site) +devtools::install(upgrade = 'never') + +# Build pkgdown site (requires Quarto installed) +pkgdown::build_site() + +# Run tests +devtools::test() +``` + +### Troubleshooting + +```r +# If packages seem out of sync: +renv::status() + +# To update package versions: +renv::update() +renv::snapshot() + +# To restore to lockfile state: +renv::restore() +``` + +For more details, see [CONTRIBUTING.md](CONTRIBUTING.md). diff --git a/Worksheets/.DS_Store b/Worksheets/.DS_Store deleted file mode 100644 index 7fc5fc6..0000000 Binary files a/Worksheets/.DS_Store and /dev/null differ diff --git a/Worksheets/cchsflow-variable-details.csv b/Worksheets/cchsflow-variable-details.csv deleted file mode 100644 index e485571..0000000 --- a/Worksheets/cchsflow-variable-details.csv +++ /dev/null @@ -1,2041 +0,0 @@ -variable,dummyVariable,typeEnd,databaseStart,variableStart,typeStart,recEnd,numValidCat,catLabel,catLabelLong,units,recStart,catStartLabel,variableStartShortLabel,variableStartLabel,notes -ADL_01,ADL_01_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6A, cchs2003_p::RACC_6A, cchs2005_p::RACE_6A, cchs2007_2008_p::RAC_6A, cchs2015_2016_p::ADL_005, cchs2017_2018_p::ADL_005,[ADL_01]",cat,1,2,Yes,Yes,N/A,1,Yes,Needs help - preparing meals,"Because of any condition or health problem, do you need the help of another person in preparing meals?", -ADL_01,ADL_01_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6A, cchs2003_p::RACC_6A, cchs2005_p::RACE_6A, cchs2007_2008_p::RAC_6A, [ADL_01]",cat,2,2,No,No,N/A,2,No,Needs help - preparing meals,"Because of any condition or health problem, do you need the help of another person in preparing meals?", -ADL_01,ADL_01_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6A, cchs2003_p::RACC_6A, cchs2005_p::RACE_6A, cchs2007_2008_p::RAC_6A, [ADL_01]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Needs help - preparing meals,"Because of any condition or health problem, do you need the help of another person in preparing meals?", -ADL_01,ADL_01_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6A, cchs2003_p::RACC_6A, cchs2005_p::RACE_6A, cchs2007_2008_p::RAC_6A, [ADL_01]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Needs help - preparing meals,"Because of any condition or health problem, do you need the help of another person in preparing meals?", -ADL_01,ADL_01_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6A, cchs2003_p::RACC_6A, cchs2005_p::RACE_6A, cchs2007_2008_p::RAC_6A, [ADL_01]",cat,NA::b,2,missing,missing,N/A,else,else,Needs help - preparing meals,"Because of any condition or health problem, do you need the help of another person in preparing meals?", -ADL_01,ADL_01_cat2_1,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_005, cchs2017_2018_p::ADL_005",cat,1,2,Yes,Yes,N/A,"[3,4]",Yes,Needs help - preparing meals,"Because of any condition or health problem, do you need the help of another person in preparing meals?","For 2015 onwards, question is changed from ""Because of condition, do you need the help of another person in X"" to ""Because of condition, do you have any difficulty with X?""; however, the answer categories indicate if they had the help of another person. 'Yes, difficulty, but can do it with the help of others' and 'Cannot do it all' are combined for 'Yes'. 'No, no difficulty' and 'Yes, difficulty, but do not require help of others' are combined for 'No'. In the universe, respondents must said yes to ""Activities of daily living"" before answering this question, therefore the sample size is small." -ADL_01,ADL_01_cat2_2,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_005, cchs2017_2018_p::ADL_005",cat,2,2,No,No,N/A,"[1,2]",No,Needs help - preparing meals,"Because of any condition or health problem, do you need the help of another person in preparing meals?","For 2015 onwards, question is changed from ""Because of condition, do you need the help of another person in X"" to ""Because of condition, do you have any difficulty with X?""; however, the answer categories indicate if they had the help of another person. 'Yes, difficulty, but can do it with the help of others' and 'Cannot do it all' are combined for 'Yes'. 'No, no difficulty' and 'Yes, difficulty, but do not require help of others' are combined for 'No'. In the universe, respondents must said yes to ""Activities of daily living"" before answering this question, therefore the sample size is small." -ADL_01,ADL_01_cat2_NA::a,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_005, cchs2017_2018_p::ADL_005",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Needs help - preparing meals,"Because of any condition or health problem, do you need the help of another person in preparing meals?", -ADL_01,ADL_01_cat2_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_005, cchs2017_2018_p::ADL_005",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Needs help - preparing meals,"Because of any condition or health problem, do you need the help of another person in preparing meals?", -ADL_01,ADL_01_cat2_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_005, cchs2017_2018_p::ADL_005",cat,NA::b,2,missing,missing,N/A,else,else,Needs help - preparing meals,"Because of any condition or health problem, do you need the help of another person in preparing meals?", -ADL_01_A,ADL_01_A_cat4_1,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_005],cat,1,4,"Yes difficulty, need help","Yes difficulty, need help",N/A,3,"Yes difficulty, need help",Needs help - preparing meals,"Because of any physical condition, mental condition or health problem, do you have any difficulty with preparing meals?","For 2015 onwards, question was reword to 'Because of any physical condition, mental condition or health problem, do you have any difficulty with preparing meals?' If they needed help from another person, it is indicated in the answer categories (Yes need help or Yes no help). In the universe, respondents must said yes to ""Activities of daily living"" before answering this question, therefore the sample size is small." -ADL_01_A,ADL_01_A_cat4_2,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_005],cat,2,4,"Yes difficulty, no help","Yes difficulty, no help",N/A,2,"Yes difficulty, no help",Needs help - preparing meals,"Because of any physical condition, mental condition or health problem, do you have any difficulty with preparing meals?", -ADL_01_A,ADL_01_A_cat4_3,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_005],cat,3,4,No difficulty,No difficulty,N/A,1,No difficulty,Needs help - preparing meals,"Because of any physical condition, mental condition or health problem, do you have any difficulty with preparing meals?", -ADL_01_A,ADL_01_A_cat4_4,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_005],cat,4,4,Cannot do it at all,Cannot do it at all,N/A,4,Cannot do it at all,Needs help - preparing meals,"Because of any physical condition, mental condition or health problem, do you have any difficulty with preparing meals?", -ADL_01_A,ADL_01_A_cat4_NA::a,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_005],cat,NA::a,4,not applicable,not applicable,N/A,6,not applicable,Needs help - preparing meals,"Because of any physical condition, mental condition or health problem, do you have any difficulty with preparing meals?", -ADL_01_A,ADL_01_A_cat4_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_005],cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Needs help - preparing meals,"Because of any physical condition, mental condition or health problem, do you have any difficulty with preparing meals?", -ADL_01_A,ADL_01_A_cat4_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_005],cat,NA::b,4,missing,missing,N/A,else,else,Needs help - preparing meals,"Because of any physical condition, mental condition or health problem, do you have any difficulty with preparing meals?", -ADL_02,ADL_02_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6B, cchs2003_p::RACC_6B1, cchs2005_p::RACE_6B1, cchs2007_2008_p::RAC_6B1, [ADL_02]",cat,1,2,Yes,Yes,N/A,1,Yes,Needs help - getting to appointments,"Because of any physical condition or mental condition or health problem, do you need the help of another person with getting to appointments and running errands such as shopping for groceries?","In the 2001 CCHS, respondents were asked, ""Because of any condition or health problem, do you need the help of another person in shopping for groceries or other necessities?""" -ADL_02,ADL_02_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6B, cchs2003_p::RACC_6B1, cchs2005_p::RACE_6B1, cchs2007_2008_p::RAC_6B1, [ADL_02]",cat,2,2,No,No,N/A,2,No,Needs help - getting to appointments,"Because of any physical condition or mental condition or health problem, do you need the help of another person with getting to appointments and running errands such as shopping for groceries?", -ADL_02,ADL_02_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6B, cchs2003_p::RACC_6B1, cchs2005_p::RACE_6B1, cchs2007_2008_p::RAC_6B1, [ADL_02]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Needs help - getting to appointments,"Because of any physical condition or mental condition or health problem, do you need the help of another person with getting to appointments and running errands such as shopping for groceries?", -ADL_02,ADL_02_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6B, cchs2003_p::RACC_6B1, cchs2005_p::RACE_6B1, cchs2007_2008_p::RAC_6B1, [ADL_02]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Needs help - getting to appointments,"Because of any physical condition or mental condition or health problem, do you need the help of another person with getting to appointments and running errands such as shopping for groceries?", -ADL_02,ADL_02_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6B, cchs2003_p::RACC_6B1, cchs2005_p::RACE_6B1, cchs2007_2008_p::RAC_6B1, [ADL_02]",cat,NA::b,2,missing,missing,N/A,else,else,Needs help - getting to appointments,"Because of any physical condition or mental condition or health problem, do you need the help of another person with getting to appointments and running errands such as shopping for groceries?", -ADL_02,ADL_02_cat2_1,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_010, cchs2017_2018_p::ADL_010",cat,1,2,Yes,Yes,N/A,"[3,4]",Yes,Needs help - preparing meals,"Because of any physical condition, mental condition or health problem, do you have any difficulty with preparing meals?","For 2015 onwards, question is changed from ""Because of condition, do you need the help of another person in X"" to ""Because of condition, do you have any difficulty with X?""; however, the answer categories indicate if they had the help of another person. 'Yes, difficulty, but can do it with the help of others' and 'Cannot do it all' are combined for 'Yes'. 'No, no difficulty' and 'Yes, difficulty, but do not require help of others' are combined for 'No'. In the universe, respondents must said yes to ""Activities of daily living"" before answering this question, therefore the sample size is small." -ADL_02,ADL_02_cat2_2,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_010, cchs2017_2018_p::ADL_010",cat,2,2,No,No,N/A,"[1,2]",No,Needs help - preparing meals,"Because of any physical condition, mental condition or health problem, do you have any difficulty with preparing meals?","For 2015 onwards, question is changed from ""Because of condition, do you need the help of another person in X"" to ""Because of condition, do you have any difficulty with X?""; however, the answer categories indicate if they had the help of another person. 'Yes, difficulty, but can do it with the help of others' and 'Cannot do it all' are combined for 'Yes'. 'No, no difficulty' and 'Yes, difficulty, but do not require help of others' are combined for 'No'. In the universe, respondents must said yes to ""Activities of daily living"" before answering this question, therefore the sample size is small." -ADL_02,ADL_02_cat2_NA::a,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_010, cchs2017_2018_p::ADL_010",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Needs help - preparing meals,"Because of any physical condition, mental condition or health problem, do you have any difficulty with preparing meals?", -ADL_02,ADL_02_cat2_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_010, cchs2017_2018_p::ADL_010",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Needs help - preparing meals,"Because of any physical condition, mental condition or health problem, do you have any difficulty with preparing meals?", -ADL_02,ADL_02_cat2_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_010, cchs2017_2018_p::ADL_010",cat,NA::b,2,missing,missing,N/A,else,else,Needs help - preparing meals,"Because of any physical condition, mental condition or health problem, do you have any difficulty with preparing meals?", -ADL_02_A,ADL_02_A_cat4_1,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_010],cat,1,4,"Yes difficulty, need help","Yes difficulty, need help",N/A,3,"Yes difficulty, need help",Needs help - getting to appointments,"Because of any physical condition, mental condition or health problem, do you have any difficulty with running errands such as shopping for groceries?","For 2015 onwards, question was reword to 'Because of any physical condition, mental condition or health problem, do you have any difficulty with running errands such as shopping for groceries?' If they needed help from another person, it is indicated in the answer categories (Yes need help or Yes no help). In the universe, respondents must said yes to ""Activities of daily living"" before answering this question, therefore the sample size is small." -ADL_02_A,ADL_02_A_cat4_2,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_010],cat,2,4,"Yes difficulty, no help","Yes difficulty, no help",N/A,2,"Yes difficulty, no help",Needs help - getting to appointments,"Because of any physical condition, mental condition or health problem, do you have any difficulty with running errands such as shopping for groceries?", -ADL_02_A,ADL_02_A_cat4_3,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_010],cat,3,4,No difficulty,No difficulty,N/A,1,No difficulty,Needs help - getting to appointments,"Because of any physical condition, mental condition or health problem, do you have any difficulty with running errands such as shopping for groceries?", -ADL_02_A,ADL_02_A_cat4_4,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_010],cat,4,4,Cannot do it at all,Cannot do it at all,N/A,4,Cannot do it at all,Needs help - getting to appointments,"Because of any physical condition, mental condition or health problem, do you have any difficulty with running errands such as shopping for groceries?", -ADL_02_A,ADL_02_A_cat4_NA::a,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_010],cat,NA::a,4,not applicable,not applicable,N/A,6,not applicable,Needs help - getting to appointments,"Because of any physical condition, mental condition or health problem, do you have any difficulty with running errands such as shopping for groceries?", -ADL_02_A,ADL_02_A_cat4_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_010],cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Needs help - getting to appointments,"Because of any physical condition, mental condition or health problem, do you have any difficulty with running errands such as shopping for groceries?", -ADL_02_A,ADL_02_A_cat4_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_010],cat,NA::b,4,missing,missing,N/A,else,else,Needs help - getting to appointments,"Because of any physical condition, mental condition or health problem, do you have any difficulty with running errands such as shopping for groceries?", -ADL_03,ADL_03_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6C, cchs2003_p::RACC_6C, cchs2005_p::RACE_6C, cchs2007_2008_p::RAC_6C, [ADL_03]",cat,1,2,Yes,Yes,N/A,1,Yes,Needs help - doing housework,"Because of any condition or health problem, do you need the help of another person in doing normal everyday housework?", -ADL_03,ADL_03_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6C, cchs2003_p::RACC_6C, cchs2005_p::RACE_6C, cchs2007_2008_p::RAC_6C, [ADL_03]",cat,2,2,No,No,N/A,2,No,Needs help - doing housework,"Because of any condition or health problem, do you need the help of another person in doing normal everyday housework?", -ADL_03,ADL_03_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6C, cchs2003_p::RACC_6C, cchs2005_p::RACE_6C, cchs2007_2008_p::RAC_6C, [ADL_03]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Needs help - doing housework,"Because of any condition or health problem, do you need the help of another person in doing normal everyday housework?", -ADL_03,ADL_03_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6C, cchs2003_p::RACC_6C, cchs2005_p::RACE_6C, cchs2007_2008_p::RAC_6C, [ADL_03]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Needs help - doing housework,"Because of any condition or health problem, do you need the help of another person in doing normal everyday housework?", -ADL_03,ADL_03_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6C, cchs2003_p::RACC_6C, cchs2005_p::RACE_6C, cchs2007_2008_p::RAC_6C, [ADL_03]",cat,NA::b,2,missing,missing,N/A,else,else,Needs help - doing housework,"Because of any condition or health problem, do you need the help of another person in doing normal everyday housework?", -ADL_03,ADL_03_cat2_1,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_015, cchs2017_2018_p::ADL_015",cat,1,2,Yes,Yes,N/A,"[3,4]",Yes,Needs help - doing housework,"Because of any condition or health problem, do you need the help of another person in doing normal everyday housework?","For 2015 onwards, question is changed from ""Because of condition, do you need the help of another person in X"" to ""Because of condition, do you have any difficulty with X?""; however, the answer categories indicate if they had the help of another person. 'Yes, difficulty, but can do it with the help of others' and 'Cannot do it all' are combined for 'Yes'. 'No, no difficulty' and 'Yes, difficulty, but do not require help of others' are combined for 'No'. In the universe, respondents must said yes to ""Activities of daily living"" before answering this question, therefore the sample size is small." -ADL_03,ADL_03_cat2_2,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_015, cchs2017_2018_p::ADL_015",cat,2,2,No,No,N/A,"[1,2]",No,Needs help - doing housework,"Because of any condition or health problem, do you need the help of another person in doing normal everyday housework?","For 2015 onwards, question is changed from ""Because of condition, do you need the help of another person in X"" to ""Because of condition, do you have any difficulty with X?""; however, the answer categories indicate if they had the help of another person. 'Yes, difficulty, but can do it with the help of others' and 'Cannot do it all' are combined for 'Yes'. 'No, no difficulty' and 'Yes, difficulty, but do not require help of others' are combined for 'No'. In the universe, respondents must said yes to ""Activities of daily living"" before answering this question, therefore the sample size is small." -ADL_03,ADL_03_cat2_NA::a,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_015, cchs2017_2018_p::ADL_015",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Needs help - doing housework,"Because of any condition or health problem, do you need the help of another person in doing normal everyday housework?", -ADL_03,ADL_03_cat2_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_015, cchs2017_2018_p::ADL_015",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Needs help - doing housework,"Because of any condition or health problem, do you need the help of another person in doing normal everyday housework?", -ADL_03,ADL_03_cat2_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_015, cchs2017_2018_p::ADL_015",cat,NA::b,2,missing,missing,N/A,else,else,Needs help - doing housework,"Because of any condition or health problem, do you need the help of another person in doing normal everyday housework?", -ADL_03_A,ADL_03_A_cat4_1,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_015],cat,1,4,"Yes difficulty, need help","Yes difficulty, need help",N/A,3,"Yes difficulty, need help",Needs help - doing housework,"Because of any physical condition, mental condition or health problem, do you have any difficulty with doing everyday housework?","For 2015 onwards, question was reword to 'Because of any physical condition, mental condition or health problem, do you have any difficulty with doing everyday housework?' If they needed help from another person, it is indicated in the answer categories (Yes need help or Yes no help). In the universe, respondents must said yes to ""Activities of daily living"" before answering this question, therefore the sample size is small." -ADL_03_A,ADL_03_A_cat4_2,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_015],cat,2,4,"Yes difficulty, no help","Yes difficulty, no help",N/A,2,"Yes difficulty, no help",Needs help - doing housework,"Because of any physical condition, mental condition or health problem, do you have any difficulty with doing everyday housework?", -ADL_03_A,ADL_03_A_cat4_3,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_015],cat,3,4,No difficulty,No difficulty,N/A,1,No difficulty,Needs help - doing housework,"Because of any physical condition, mental condition or health problem, do you have any difficulty with doing everyday housework?", -ADL_03_A,ADL_03_A_cat4_4,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_015],cat,4,4,Cannot do it at all,Cannot do it at all,N/A,4,Cannot do it at all,Needs help - doing housework,"Because of any physical condition, mental condition or health problem, do you have any difficulty with doing everyday housework?", -ADL_03_A,ADL_03_A_cat4_NA::a,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_015],cat,NA::a,4,not applicable,not applicable,N/A,6,not applicable,Needs help - doing housework,"Because of any physical condition, mental condition or health problem, do you have any difficulty with doing everyday housework?", -ADL_03_A,ADL_03_A_cat4_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_015],cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Needs help - doing housework,"Because of any physical condition, mental condition or health problem, do you have any difficulty with doing everyday housework?", -ADL_03_A,ADL_03_A_cat4_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_015],cat,NA::b,4,missing,missing,N/A,else,else,Needs help - doing housework,"Because of any physical condition, mental condition or health problem, do you have any difficulty with doing everyday housework?", -ADL_04,ADL_04_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6E, cchs2003_p::RACC_6E, cchs2005_p::RACE_6E, cchs2007_2008_p::RAC_6E, [ADL_04]",cat,1,2,Yes,Yes,N/A,1,Yes,Needs help - personal care,"Because of any condition or health problem, do you need the help of another person in personal care such as washing, dressing or eating?", -ADL_04,ADL_04_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6E, cchs2003_p::RACC_6E, cchs2005_p::RACE_6E, cchs2007_2008_p::RAC_6E, [ADL_04]",cat,2,2,No,No,N/A,2,No,Needs help - personal care,"Because of any condition or health problem, do you need the help of another person in personal care such as washing, dressing or eating?", -ADL_04,ADL_04_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6E, cchs2003_p::RACC_6E, cchs2005_p::RACE_6E, cchs2007_2008_p::RAC_6E, [ADL_04]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Needs help - personal care,"Because of any condition or health problem, do you need the help of another person in personal care such as washing, dressing or eating?", -ADL_04,ADL_04_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6E, cchs2003_p::RACC_6E, cchs2005_p::RACE_6E, cchs2007_2008_p::RAC_6E, [ADL_04]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Needs help - personal care,"Because of any condition or health problem, do you need the help of another person in personal care such as washing, dressing or eating?", -ADL_04,ADL_04_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6E, cchs2003_p::RACC_6E, cchs2005_p::RACE_6E, cchs2007_2008_p::RAC_6E, [ADL_04]",cat,NA::b,2,missing,missing,N/A,else,else,Needs help - personal care,"Because of any condition or health problem, do you need the help of another person in personal care such as washing, dressing or eating?", -ADL_04,ADL_04_cat2_1,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_020, cchs2017_2018_p::ADL_020",cat,1,2,Yes,Yes,N/A,"[3,4]",Yes,Needs help - personal care,"Because of any condition or health problem, do you need the help of another person in personal care such as washing, dressing or eating?","For 2015 onwards, question is changed from ""Because of condition, do you need the help of another person in X"" to ""Because of condition, do you have any difficulty with X?""; however, the answer categories indicate if they had the help of another person. 'Yes, difficulty, but can do it with the help of others' and 'Cannot do it all' are combined for 'Yes'. 'No, no difficulty' and 'Yes, difficulty, but do not require help of others' are combined for 'No'. In the universe, respondents must said yes to ""Activities of daily living"" before answering this question, therefore the sample size is small." -ADL_04,ADL_04_cat2_2,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_020, cchs2017_2018_p::ADL_020",cat,2,2,No,No,N/A,"[1,2]",No,Needs help - personal care,"Because of any condition or health problem, do you need the help of another person in personal care such as washing, dressing or eating?","For 2015 onwards, question is changed from ""Because of condition, do you need the help of another person in X"" to ""Because of condition, do you have any difficulty with X?""; however, the answer categories indicate if they had the help of another person. 'Yes, difficulty, but can do it with the help of others' and 'Cannot do it all' are combined for 'Yes'. 'No, no difficulty' and 'Yes, difficulty, but do not require help of others' are combined for 'No'. In the universe, respondents must said yes to ""Activities of daily living"" before answering this question, therefore the sample size is small." -ADL_04,ADL_04_cat2_NA::a,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_020, cchs2017_2018_p::ADL_020",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Needs help - personal care,"Because of any condition or health problem, do you need the help of another person in personal care such as washing, dressing or eating?", -ADL_04,ADL_04_cat2_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_020, cchs2017_2018_p::ADL_020",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Needs help - personal care,"Because of any condition or health problem, do you need the help of another person in personal care such as washing, dressing or eating?", -ADL_04,ADL_04_cat2_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_020, cchs2017_2018_p::ADL_020",cat,NA::b,2,missing,missing,N/A,else,else,Needs help - personal care,"Because of any condition or health problem, do you need the help of another person in personal care such as washing, dressing or eating?", -ADL_04_A,ADL_04_A_cat4_1,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_020],cat,1,4,"Yes difficulty, need help","Yes difficulty, need help",N/A,3,"Yes difficulty, need help",Needs help - personal care,"Because of any physical condition, mental condition or health problem, do you have any difficulty with personal care such as bathing, dressing, eating or taking medication?","For 2015 onwards, question was reword to 'Because of any physical condition, mental condition or health problem, do you have any difficulty with personal care such as bathing, dressing, eating or taking medication?' If they needed help from another person, it is indicated in the answer categories (Yes need help or Yes no help). In the universe, respondents must said yes to ""Activities of daily living"" before answering this question, therefore the sample size is small." -ADL_04_A,ADL_04_A_cat4_2,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_020],cat,2,4,"Yes difficulty, no help","Yes difficulty, no help",N/A,2,"Yes difficulty, no help",Needs help - personal care,"Because of any physical condition, mental condition or health problem, do you have any difficulty with personal care such as bathing, dressing, eating or taking medication?", -ADL_04_A,ADL_04_A_cat4_3,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_020],cat,3,4,No difficulty,No difficulty,N/A,1,No difficulty,Needs help - personal care,"Because of any physical condition, mental condition or health problem, do you have any difficulty with personal care such as bathing, dressing, eating or taking medication?", -ADL_04_A,ADL_04_A_cat4_4,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_020],cat,4,4,Cannot do it at all,Cannot do it at all,N/A,4,Cannot do it at all,Needs help - personal care,"Because of any physical condition, mental condition or health problem, do you have any difficulty with personal care such as bathing, dressing, eating or taking medication?", -ADL_04_A,ADL_04_A_cat4_NA::a,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_020],cat,NA::a,4,not applicable,not applicable,N/A,6,not applicable,Needs help - personal care,"Because of any physical condition, mental condition or health problem, do you have any difficulty with personal care such as bathing, dressing, eating or taking medication?", -ADL_04_A,ADL_04_A_cat4_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_020],cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Needs help - personal care,"Because of any physical condition, mental condition or health problem, do you have any difficulty with personal care such as bathing, dressing, eating or taking medication?", -ADL_04_A,ADL_04_A_cat4_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_020],cat,NA::b,4,missing,missing,N/A,else,else,Needs help - personal care,"Because of any physical condition, mental condition or health problem, do you have any difficulty with personal care such as bathing, dressing, eating or taking medication?", -ADL_05,ADL_05_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6F, cchs2003_p::RACC_6F, cchs2005_p::RACE_6F, cchs2007_2008_p::RAC_6F, [ADL_05]",cat,1,2,Yes,Yes,N/A,1,Yes,Needs help - moving about inside house,"Because of any condition or health problem, do you need the help of another person in moving about inside the house?", -ADL_05,ADL_05_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6F, cchs2003_p::RACC_6F, cchs2005_p::RACE_6F, cchs2007_2008_p::RAC_6F, [ADL_05]",cat,2,2,No,No,N/A,2,No,Needs help - moving about inside house,"Because of any condition or health problem, do you need the help of another person in moving about inside the house?", -ADL_05,ADL_05_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6F, cchs2003_p::RACC_6F, cchs2005_p::RACE_6F, cchs2007_2008_p::RAC_6F, [ADL_05]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Needs help - moving about inside house,"Because of any condition or health problem, do you need the help of another person in moving about inside the house?", -ADL_05,ADL_05_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6F, cchs2003_p::RACC_6F, cchs2005_p::RACE_6F, cchs2007_2008_p::RAC_6F, [ADL_05]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Needs help - moving about inside house,"Because of any condition or health problem, do you need the help of another person in moving about inside the house?", -ADL_05,ADL_05_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_6F, cchs2003_p::RACC_6F, cchs2005_p::RACE_6F, cchs2007_2008_p::RAC_6F, [ADL_05]",cat,NA::b,2,missing,missing,N/A,else,else,Needs help - moving about inside house,"Because of any condition or health problem, do you need the help of another person in moving about inside the house?", -ADL_05,ADL_05_cat2_1,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_025, cchs2017_2018_p::ADL_025",cat,1,2,Yes,Yes,N/A,"[3,4]",Yes,Needs help - moving about inside house,"Because of any condition or health problem, do you need the help of another person in moving about inside the house?","For 2015 onwards, question is changed from ""Because of condition, do you need the help of another person in X"" to ""Because of condition, do you have any difficulty with X?""; however, the answer categories indicate if they had the help of another person. 'Yes, difficulty, but can do it with the help of others' and 'Cannot do it all' are combined for 'Yes'. 'No, no difficulty' and 'Yes, difficulty, but do not require help of others' are combined for 'No'. In the universe, respondents must said yes to ""Activities of daily living"" before answering this question, therefore the sample size is small." -ADL_05,ADL_05_cat2_2,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_025, cchs2017_2018_p::ADL_025",cat,2,2,No,No,N/A,"[1,2]",No,Needs help - moving about inside house,"Because of any condition or health problem, do you need the help of another person in moving about inside the house?","For 2015 onwards, question is changed from ""Because of condition, do you need the help of another person in X"" to ""Because of condition, do you have any difficulty with X?""; however, the answer categories indicate if they had the help of another person. 'Yes, difficulty, but can do it with the help of others' and 'Cannot do it all' are combined for 'Yes'. 'No, no difficulty' and 'Yes, difficulty, but do not require help of others' are combined for 'No'. In the universe, respondents must said yes to ""Activities of daily living"" before answering this question, therefore the sample size is small." -ADL_05,ADL_05_cat2_NA::a,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_025, cchs2017_2018_p::ADL_025",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Needs help - moving about inside house,"Because of any condition or health problem, do you need the help of another person in moving about inside the house?", -ADL_05,ADL_05_cat2_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_025, cchs2017_2018_p::ADL_025",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Needs help - moving about inside house,"Because of any condition or health problem, do you need the help of another person in moving about inside the house?", -ADL_05,ADL_05_cat2_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_025, cchs2017_2018_p::ADL_025",cat,NA::b,2,missing,missing,N/A,else,else,Needs help - moving about inside house,"Because of any condition or health problem, do you need the help of another person in moving about inside the house?", -ADL_05_A,ADL_05_A_cat4_1,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_025],cat,1,4,"Yes difficulty, need help","Yes difficulty, need help",N/A,3,"Yes difficulty, need help",Needs help - moving about inside house,"Because of any physical condition, mental condition or health problem, do you have any difficulty with moving about inside the house?","For 2015 onwards, question was reword to 'Because of any physical condition, mental condition or health problem, do you have any difficulty with moving about inside the house?' If they needed help from another person, it is indicated in the answer categories (Yes need help or Yes no help). In the universe, respondents must said yes to ""Activities of daily living"" before answering this question, therefore the sample size is small." -ADL_05_A,ADL_05_A_cat4_2,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_025],cat,2,4,"Yes difficulty, no help","Yes difficulty, no help",N/A,2,"Yes difficulty, no help",Needs help - moving about inside house,"Because of any physical condition, mental condition or health problem, do you have any difficulty with moving about inside the house?", -ADL_05_A,ADL_05_A_cat4_3,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_025],cat,3,4,No difficulty,No difficulty,N/A,1,No difficulty,Needs help - moving about inside house,"Because of any physical condition, mental condition or health problem, do you have any difficulty with moving about inside the house?", -ADL_05_A,ADL_05_A_cat4_4,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_025],cat,4,4,Cannot do it at all,Cannot do it at all,N/A,4,Cannot do it at all,Needs help - moving about inside house,"Because of any physical condition, mental condition or health problem, do you have any difficulty with moving about inside the house?", -ADL_05_A,ADL_05_A_cat4_NA::a,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_025],cat,NA::a,4,not applicable,not applicable,N/A,6,not applicable,Needs help - moving about inside house,"Because of any physical condition, mental condition or health problem, do you have any difficulty with moving about inside the house?", -ADL_05_A,ADL_05_A_cat4_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_025],cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Needs help - moving about inside house,"Because of any physical condition, mental condition or health problem, do you have any difficulty with moving about inside the house?", -ADL_05_A,ADL_05_A_cat4_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_025],cat,NA::b,4,missing,missing,N/A,else,else,Needs help - moving about inside house,"Because of any physical condition, mental condition or health problem, do you have any difficulty with moving about inside the house?", -ADL_06,ADL_06_cat2_1,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACC_6G, cchs2005_p::RACE_6G, cchs2007_2008_p::RAC_6G, [ADL_06]",cat,1,2,Yes,Yes,N/A,1,Yes,Needs help - looking after finances,"Because of any physical condition or mental condition or health problem, do you need the help of another person with looking after your personal finances such as making bank transactions or paying bills?", -ADL_06,ADL_06_cat2_2,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACC_6G, cchs2005_p::RACE_6G, cchs2007_2008_p::RAC_6G, [ADL_06]",cat,2,2,No,No,N/A,2,No,Needs help - looking after finances,"Because of any physical condition or mental condition or health problem, do you need the help of another person with looking after your personal finances such as making bank transactions or paying bills?", -ADL_06,ADL_06_cat2_NA::a,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACC_6G, cchs2005_p::RACE_6G, cchs2007_2008_p::RAC_6G, [ADL_06]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Needs help - looking after finances,"Because of any physical condition or mental condition or health problem, do you need the help of another person with looking after your personal finances such as making bank transactions or paying bills?", -ADL_06,ADL_06_cat2_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACC_6G, cchs2005_p::RACE_6G, cchs2007_2008_p::RAC_6G, [ADL_06]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Needs help - looking after finances,"Because of any physical condition or mental condition or health problem, do you need the help of another person with looking after your personal finances such as making bank transactions or paying bills?", -ADL_06,ADL_06_cat2_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACC_6G, cchs2005_p::RACE_6G, cchs2007_2008_p::RAC_6G, [ADL_06]",cat,NA::b,2,missing,missing,N/A,else,else,Needs help - looking after finances,"Because of any physical condition or mental condition or health problem, do you need the help of another person with looking after your personal finances such as making bank transactions or paying bills?", -ADL_06,ADL_06_cat2_1,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_030, cchs2017_2018_p::ADL_030",cat,1,2,Yes,Yes,N/A,"[3,4]",Yes,Needs help - looking after finances,"Because of any physical condition or mental condition or health problem, do you need the help of another person with looking after your personal finances such as making bank transactions or paying bills?","For 2015 onwards, question is changed from ""Because of condition, do you need the help of another person in X"" to ""Because of condition, do you have any difficulty with X?""; however, the answer categories indicate if they had the help of another person. 'Yes, difficulty, but can do it with the help of others' and 'Cannot do it all' are combined for 'Yes'. 'No, no difficulty' and 'Yes, difficulty, but do not require help of others' are combined for 'No'. In the universe, respondents must said yes to ""Activities of daily living"" before answering this question, therefore the sample size is small." -ADL_06,ADL_06_cat2_2,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_030, cchs2017_2018_p::ADL_030",cat,2,2,No,No,N/A,"[1,2]",No,Needs help - looking after finances,"Because of any physical condition or mental condition or health problem, do you need the help of another person with looking after your personal finances such as making bank transactions or paying bills?","For 2015 onwards, question is changed from ""Because of condition, do you need the help of another person in X"" to ""Because of condition, do you have any difficulty with X?""; however, the answer categories indicate if they had the help of another person. 'Yes, difficulty, but can do it with the help of others' and 'Cannot do it all' are combined for 'Yes'. 'No, no difficulty' and 'Yes, difficulty, but do not require help of others' are combined for 'No'. In the universe, respondents must said yes to ""Activities of daily living"" before answering this question, therefore the sample size is small." -ADL_06,ADL_06_cat2_NA::a,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_030, cchs2017_2018_p::ADL_030",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Needs help - looking after finances,"Because of any physical condition or mental condition or health problem, do you need the help of another person with looking after your personal finances such as making bank transactions or paying bills?", -ADL_06,ADL_06_cat2_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_030, cchs2017_2018_p::ADL_030",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Needs help - looking after finances,"Because of any physical condition or mental condition or health problem, do you need the help of another person with looking after your personal finances such as making bank transactions or paying bills?", -ADL_06,ADL_06_cat2_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ADL_030, cchs2017_2018_p::ADL_030",cat,NA::b,2,missing,missing,N/A,else,else,Needs help - looking after finances,"Because of any physical condition or mental condition or health problem, do you need the help of another person with looking after your personal finances such as making bank transactions or paying bills?", -ADL_06_A,ADL_06_A_cat4_1,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_030],cat,1,4,"Yes difficulty, need help","Yes difficulty, need help",N/A,3,"Yes difficulty, need help",Needs help - looking after finances,"Because of any physical condition, mental condition or health problem, do you have any difficulty with looking after your personal finances such as making bank transactions or paying bills?","For 2015 onwards, question was reword to 'Because of any physical condition, mental condition or health problem, do you have any difficulty with looking after your personal finances such as making bank transactions or paying bills?' If they needed help from another person, it is indicated in the answer categories (Yes need help or Yes no help). In the universe, respondents must said yes to ""Activities of daily living"" before answering this question, therefore the sample size is small." -ADL_06_A,ADL_06_A_cat4_2,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_030],cat,2,4,"Yes difficulty, no help","Yes difficulty, no help",N/A,2,"Yes difficulty, no help",Needs help - looking after finances,"Because of any physical condition, mental condition or health problem, do you have any difficulty with looking after your personal finances such as making bank transactions or paying bills?", -ADL_06_A,ADL_06_A_cat4_3,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_030],cat,3,4,No difficulty,No difficulty,N/A,1,No difficulty,Needs help - looking after finances,"Because of any physical condition, mental condition or health problem, do you have any difficulty with looking after your personal finances such as making bank transactions or paying bills?", -ADL_06_A,ADL_06_A_cat4_4,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_030],cat,4,4,Cannot do it at all,Cannot do it at all,N/A,4,Cannot do it at all,Needs help - looking after finances,"Because of any physical condition, mental condition or health problem, do you have any difficulty with looking after your personal finances such as making bank transactions or paying bills?", -ADL_06_A,ADL_06_A_cat4_NA::a,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_030],cat,NA::a,4,not applicable,not applicable,N/A,6,not applicable,Needs help - looking after finances,"Because of any physical condition, mental condition or health problem, do you have any difficulty with looking after your personal finances such as making bank transactions or paying bills?", -ADL_06_A,ADL_06_A_cat4_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_030],cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Needs help - looking after finances,"Because of any physical condition, mental condition or health problem, do you have any difficulty with looking after your personal finances such as making bank transactions or paying bills?", -ADL_06_A,ADL_06_A_cat4_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p",[ADL_030],cat,NA::b,4,missing,missing,N/A,else,else,Needs help - looking after finances,"Because of any physical condition, mental condition or health problem, do you have any difficulty with looking after your personal finances such as making bank transactions or paying bills?", -ADL_07,ADL_07_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::RACA_6D, cchs2003_p::RACC_6D, cchs2005_p::RACE_6D",cat,1,2,Yes,Yes,N/A,1,Yes,Needs help - heavy household chores,"Because of any physical condition or mental condition or health problem, do you need the help of another person with doing heavy household chores such as spring cleaning or yard work?", -ADL_07,ADL_07_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::RACA_6D, cchs2003_p::RACC_6D, cchs2005_p::RACE_6D",cat,2,2,No,No,N/A,2,No,Needs help - heavy household chores,"Because of any physical condition or mental condition or health problem, do you need the help of another person with doing heavy household chores such as spring cleaning or yard work?", -ADL_07,ADL_07_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::RACA_6D, cchs2003_p::RACC_6D, cchs2005_p::RACE_6D",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Needs help - heavy household chores,"Because of any physical condition or mental condition or health problem, do you need the help of another person with doing heavy household chores such as spring cleaning or yard work?", -ADL_07,ADL_07_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::RACA_6D, cchs2003_p::RACC_6D, cchs2005_p::RACE_6D",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Needs help - heavy household chores,"Because of any physical condition or mental condition or health problem, do you need the help of another person with doing heavy household chores such as spring cleaning or yard work?", -ADL_07,ADL_07_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::RACA_6D, cchs2003_p::RACC_6D, cchs2005_p::RACE_6D",cat,NA::b,2,missing,missing,N/A,else,else,Needs help - heavy household chores,"Because of any physical condition or mental condition or health problem, do you need the help of another person with doing heavy household chores such as spring cleaning or yard work?", -ADL_der,ADL_der_catN/A_Func::adl_fun,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05]",N/A,Func::adl_fun,N/A,N/A,N/A,N/A,N/A,N/A,Derived needs help with tasks,Derived needs help with tasks,"Derived variable based on ADL_01, ADL_02, ADL_03, ADL_04, ADL_05" -ADL_der,ADL_der_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05]",N/A,1,2,Needs help with tasks,Needs help with tasks,N/A,N/A,Needs help with tasks,Derived needs help with tasks,Derived needs help with tasks, -ADL_der,ADL_der_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05]",N/A,2,2,Does not need help with tasks,Does need help with tasks,N/A,N/A,Does need help with tasks,Derived needs help with tasks,Derived needs help with tasks, -ADL_der,ADL_der_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05]",N/A,NA::b,2,missing,missing,N/A,N/A,Does need help with tasks,Derived needs help with tasks,Derived needs help with tasks, -ADL_score_5,ADL_score_5_catN/A_Func::adl_score_fun,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05]",N/A,Func::adl_score_5_fun,6,N/A,N/A,N/A,N/A,N/A,N/A,N/A, -ADL_score_5,ADL_score_5_cat6_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05]",N/A,0,6,Needs help with 0 tasks,Needs help with 0 tasks,N/A,N/A,N/A,N/A,N/A, -ADL_score_5,ADL_score_5_cat6_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05]",N/A,1,6,Needs help with at least 1 task,Needs help with at least 1 task,N/A,N/A,N/A,N/A,N/A, -ADL_score_5,ADL_score_5_cat6_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05]",N/A,2,6,Needs help with at least 2 tasks,Needs help with at least 2 tasks,N/A,N/A,N/A,N/A,N/A, -ADL_score_5,ADL_score_5_cat6_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05]",N/A,3,6,Needs help with at least 3 tasks,Needs help with at least 3 tasks,N/A,N/A,N/A,N/A,N/A, -ADL_score_5,ADL_score_5_cat6_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05]",N/A,4,6,Needs help with at least 4 tasks,Needs help with at least 4 tasks,N/A,N/A,N/A,N/A,N/A, -ADL_score_5,ADL_score_5_cat6_6,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05]",N/A,5,6,Needs help with at least 5 tasks,Needs help with at least 5 tasks,N/A,N/A,N/A,N/A,N/A, -ADL_score_5,ADL_score_5_cat6_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05]",N/A,NA::a,6,not applicable,not applicable,N/A,N/A,N/A,N/A,N/A, -ADL_score_5,ADL_score_5_cat6_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05]",N/A,NA::b,6,missing,missing,N/A,N/A,N/A,N/A,N/A, -ADLF6R,ADLF6R_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACAF6, cchs2003_p::RACCF6R, cchs2005_p::RACEF6R, cchs2007_2008_p::RACF6R, [ADLF6R]",cat,1,2,Yes,Yes,N/A,1,Yes,Needs help with at least one task - (F),Needs help with at least one task - (F), -ADLF6R,ADLF6R_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACAF6, cchs2003_p::RACCF6R, cchs2005_p::RACEF6R, cchs2007_2008_p::RACF6R, [ADLF6R]",cat,2,2,No,No,N/A,2,No,Needs help with at least one task - (F),Needs help with at least one task - (F), -ADLF6R,ADLF6R_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACAF6, cchs2003_p::RACCF6R, cchs2005_p::RACEF6R, cchs2007_2008_p::RACF6R, [ADLF6R]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Needs help with at least one task - (F),Needs help with at least one task - (F), -ADLF6R,ADLF6R_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACAF6, cchs2003_p::RACCF6R, cchs2005_p::RACEF6R, cchs2007_2008_p::RACF6R, [ADLF6R]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Needs help with at least one task - (F),Needs help with at least one task - (F), -ADLF6R,ADLF6R_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACAF6, cchs2003_p::RACCF6R, cchs2005_p::RACEF6R, cchs2007_2008_p::RACF6R, [ADLF6R]",cat,NA::b,2,missing,missing,N/A,else,else,Needs help with at least one task - (F),Needs help with at least one task - (F), -ADM_RNO,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ADMA_RNO, cchs2003_p::ADMC_RNO, cchs2005_p::ADME_RNO, [ADM_RNO]",cont,copy,N/A,Sequential record number,Sequential record number,N/A,"[1,999998]",Sequential record number,Sequential record number,Sequential record number, -ALC_1,ALC_1_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_1, cchs2003_p::ALCC_1, cchs2005_p::ALCE_1, cchs2015_2016_p::ALC_010, cchs2017_2018_p::ALC_010, [ALC_1]",cat,1,2,yes,alcohol in the past year,N/A,1,"Past year, have you drank alcohol",d12,"Past year, have you drank alcohol", -ALC_1,ALC_1_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_1, cchs2003_p::ALCC_1, cchs2005_p::ALCE_1, cchs2015_2016_p::ALC_010, cchs2017_2018_p::ALC_010, [ALC_1]",cat,2,2,no,no alcohol in past year,N/A,2,"Past year, have you drank alcohol",d12,"Past year, have you drank alcohol", -ALC_1,ALC_1_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_1, cchs2003_p::ALCC_1, cchs2005_p::ALCE_1, cchs2015_2016_p::ALC_010, cchs2017_2018_p::ALC_010, [ALC_1]",cat,NA::a,2,not applicable,not applicable,N/A,6,Not applicable,d12,"Past year, have you drank alcohol", -ALC_1,ALC_1_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_1, cchs2003_p::ALCC_1, cchs2005_p::ALCE_1, cchs2015_2016_p::ALC_010, cchs2017_2018_p::ALC_010, [ALC_1]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),d12,"Past year, have you drank alcohol", -ALC_1,ALC_1_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_1, cchs2003_p::ALCC_1, cchs2005_p::ALCE_1, cchs2015_2016_p::ALC_010, cchs2017_2018_p::ALC_010, [ALC_1]",cat,NA::b,2,missing,missing,N/A,else,else,d12,"Past year, have you drank alcohol", -ALC_005,ALC_005_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5B, cchs2003_p::ALCC_5B, cchs2005_p::ALCE_5B, cchs2007_2008_p::ALN_1, [ALC_005]",cat,1,2,yes,alcohol in the lifetime,N/A,1,"In lifetime, ever had a drink?",dever,"In lifetime, ever had a drink?", -ALC_005,ALC_005_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5B, cchs2003_p::ALCC_5B, cchs2005_p::ALCE_5B, cchs2007_2008_p::ALN_1, [ALC_005]",cat,2,2,no,no alcohol in lifetime,N/A,2,"In lifetime, ever had a drink?",dever,"In lifetime, ever had a drink?", -ALC_005,ALC_005_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5B, cchs2003_p::ALCC_5B, cchs2005_p::ALCE_5B, cchs2007_2008_p::ALN_1, [ALC_005]",cat,NA::a,2,not applicable,not applicable,N/A,6,Not applicable,dever,"In lifetime, ever had a drink?", -ALC_005,ALC_005_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5B, cchs2003_p::ALCC_5B, cchs2005_p::ALCE_5B, cchs2007_2008_p::ALN_1, [ALC_005]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),dever,"In lifetime, ever had a drink?", -ALC_005,ALC_005_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5B, cchs2003_p::ALCC_5B, cchs2005_p::ALCE_5B, cchs2007_2008_p::ALN_1, [ALC_005]",cat,NA::b,2,missing,missing,N/A,else,else,dever,"In lifetime, ever had a drink?", -ALCDTTM,ALCDTTM_cat3_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ALCDVTTM, cchs2017_2018_p::ALCDVTTM, [ALCDTTM]",cat,1,3,Regular,Regular Drinker,N/A,1,Regular Drinker,Drinker type (last 12 months),Type of drinker (last 12 months), -ALCDTTM,ALCDTTM_cat3_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ALCDVTTM, cchs2017_2018_p::ALCDVTTM, [ALCDTTM]",cat,2,3,Occasional,Occasional Drinker,N/A,2,Occasional drinker,Drinker type (last 12 months),Type of drinker (last 12 months), -ALCDTTM,ALCDTTM_cat3_3,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ALCDVTTM, cchs2017_2018_p::ALCDVTTM, [ALCDTTM]",cat,3,3,No drink in last 12 months,No drink in last 12 months,N/A,3,No drink in the last 12 months,Drinker type (last 12 months),Type of drinker (last 12 months), -ALCDTTM,ALCDTTM_cat3_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ALCDVTTM, cchs2017_2018_p::ALCDVTTM, [ALCDTTM]",cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Drinker type (last 12 months),Type of drinker (last 12 months), -ALCDTTM,ALCDTTM_cat3_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ALCDVTTM, cchs2017_2018_p::ALCDVTTM, [ALCDTTM]",cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Drinker type (last 12 months),Type of drinker (last 12 months), -ALCDTTM,ALCDTTM_cat3_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::ALCDVTTM, cchs2017_2018_p::ALCDVTTM, [ALCDTTM]",cat,NA::b,3,missing,missing,N/A,else,else,Drinker type (last 12 months),Type of drinker (last 12 months), -ALCDTTM,ALCDTTM_cat3_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP",cat,1,3,Regular,Regular Drinker,N/A,1,Regular drinker,Drinker type (last 12 months),Type of drinker (last 12 months),"In CCHS cycles 2001, 2003, and 2005, ALCDTTM was derived from ALCDTYP in which former and never drinkers were combined into ""No drink in the last 12 months""" -ALCDTTM,ALCDTTM_cat3_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP",cat,2,3,Occasional,Occasional Drinker,N/A,2,Occasional drinker,Drinker type (last 12 months),Type of drinker (last 12 months), -ALCDTTM,ALCDTTM_cat3_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP",cat,3,3,No drink in last 12 months,No drink in last 12 months,N/A,3,Former drinker,Drinker type (last 12 months),Type of drinker (last 12 months), -ALCDTTM,ALCDTTM_cat3_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP",cat,3,3,No drink in last 12 months,No drink in last 12 months,N/A,4,Never drank,Drinker type (last 12 months),Type of drinker (last 12 months), -ALCDTTM,ALCDTTM_cat3_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP",cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Drinker type (last 12 months),Type of drinker (last 12 months), -ALCDTTM,ALCDTTM_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP",cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Drinker type (last 12 months),Type of drinker (last 12 months), -ALCDTTM,ALCDTTM_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP",cat,NA::b,3,missing,missing,N/A,else,else,Drinker type (last 12 months),Type of drinker (last 12 months), -ALCDTYP,ALCDTYP_cat4_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP, [ALNDTYP]",cat,1,4,Regular,Regular drinker,N/A,1,Regular drinker,DrinkerType,Type of drinker - (D), -ALCDTYP,ALCDTYP_cat4_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP, [ALNDTYP]",cat,2,4,Occasional,Occasional drinker,N/A,2,Occasional drinker,DrinkerType,Type of drinker - (D), -ALCDTYP,ALCDTYP_cat4_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP, [ALNDTYP]",cat,3,4,Former,Former drinker,N/A,3,Former drinker,DrinkerType,Type of drinker - (D), -ALCDTYP,ALCDTYP_cat4_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP, [ALNDTYP]",cat,4,4,Never drank,Never drank,N/A,4,Never drank,DrinkerType,Type of drinker - (D), -ALCDTYP,ALCDTYP_cat4_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP, [ALNDTYP]",cat,NA::a,4,Not applicable,not applicable,N/A,6,not applicable,DrinkerType,Type of drinker - (D), -ALCDTYP,ALCDTYP_cat4_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP, [ALNDTYP]",cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),DrinkerType,Type of drinker - (D),Don't know (7) and refusal (8) not included in 2001 CCHS -ALCDTYP,ALCDTYP_cat4_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP, [ALNDTYP]",cat,NA::b,4,missing,missing,N/A,else,else,DrinkerType,Type of drinker - (D), -ALW_1,ALW_1_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5, cchs2003_p::ALCC_5, cchs2005_p::ALCE_5, cchs2015_2016_p::ALW_005, cchs2017_2018_p::ALW_005, [ALW_1]",cat,1,2,yes,alcohol in the past week,N/A,1,"Past week, had any alcohol",dany,"Past week, had any alcohol", -ALW_1,ALW_1_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5, cchs2003_p::ALCC_5, cchs2005_p::ALCE_5, cchs2015_2016_p::ALW_005, cchs2017_2018_p::ALW_005, [ALW_1]",cat,2,2,no,no alcohol in past week,N/A,2,"Past week, had any alcohol",dany,"Past week, had any alcohol", -ALW_1,ALW_1_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5, cchs2003_p::ALCC_5, cchs2005_p::ALCE_5, cchs2015_2016_p::ALW_005, cchs2017_2018_p::ALW_005, [ALW_1]",cat,NA::a,2,not applicable,not applicable,N/A,6,Not applicable,dany,"Past week, had any alcohol", -ALW_1,ALW_1_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5, cchs2003_p::ALCC_5, cchs2005_p::ALCE_5, cchs2015_2016_p::ALW_005, cchs2017_2018_p::ALW_005, [ALW_1]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),dany,"Past week, had any alcohol", -ALW_1,ALW_1_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5, cchs2003_p::ALCC_5, cchs2005_p::ALCE_5, cchs2015_2016_p::ALW_005, cchs2017_2018_p::ALW_005, [ALW_1]",cat,NA::b,2,missing,missing,N/A,else,else,dany,"Past week, had any alcohol", -ALW_2A1,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A1, cchs2003_p::ALCC_5A1, cchs2005_p::ALCE_5A1, cchs2015_2016_p::ALW_010, cchs2017_2018_p::ALW_010, [ALW_2A1]",cont,copy,N/A,# of drinks - Sunday,Number of drinks on Sunday,drinks,"[0,50]",Number of drinks on Sunday,DailyConsumptionSunday,Number of drinks on Sunday, -ALW_2A1,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A1, cchs2003_p::ALCC_5A1, cchs2005_p::ALCE_5A1, cchs2015_2016_p::ALW_010, cchs2017_2018_p::ALW_010, [ALW_2A1]",cont,NA::a,N/A,not applicable,not applicable,drinks,996,not applicable,DailyConsumptionSunday,Number of drinks on Sunday, -ALW_2A1,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A1, cchs2003_p::ALCC_5A1, cchs2005_p::ALCE_5A1, cchs2015_2016_p::ALW_010, cchs2017_2018_p::ALW_010, [ALW_2A1]",cont,NA::b,N/A,missing,missing,drinks,"[997,999]",don't know (997); refusal (998); not stated (999),DailyConsumptionSunday,Number of drinks on Sunday, -ALW_2A1,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A1, cchs2003_p::ALCC_5A1, cchs2005_p::ALCE_5A1, cchs2015_2016_p::ALW_010, cchs2017_2018_p::ALW_010, [ALW_2A1]",cont,NA::b,N/A,missing,missing,drinks,else,else,DailyConsumptionSunday,Number of drinks on Sunday, -ALW_2A2,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A2, cchs2003_p::ALCC_5A2, cchs2005_p::ALCE_5A2, cchs2015_2016_p::ALW_015, cchs2017_2018_p::ALW_015, [ALW_2A2]",cont,copy,N/A,# of drinks - Monday,Number of drinks on Monday,drinks,"[0,50]",Number of drinks on Monday,DailyConsumptionMonday,Number of drinks on Monday, -ALW_2A2,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A2, cchs2003_p::ALCC_5A2, cchs2005_p::ALCE_5A2, cchs2015_2016_p::ALW_015, cchs2017_2018_p::ALW_015, [ALW_2A2]",cont,NA::a,N/A,not applicable,not applicable,drinks,996,not applicable,DailyConsumptionMonday,Number of drinks on Monday, -ALW_2A2,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A2, cchs2003_p::ALCC_5A2, cchs2005_p::ALCE_5A2, cchs2015_2016_p::ALW_015, cchs2017_2018_p::ALW_015, [ALW_2A2]",cont,NA::b,N/A,missing,missing,drinks,"[997,999]",don't know (997); refusal (998); not stated (999),DailyConsumptionMonday,Number of drinks on Monday, -ALW_2A2,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A2, cchs2003_p::ALCC_5A2, cchs2005_p::ALCE_5A2, cchs2015_2016_p::ALW_015, cchs2017_2018_p::ALW_015, [ALW_2A2]",cont,NA::b,N/A,missing,missing,drinks,else,else,DailyConsumptionMonday,Number of drinks on Monday, -ALW_2A3,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A3, cchs2003_p::ALCC_5A3, cchs2005_p::ALCE_5A3, cchs2015_2016_p::ALW_020, cchs2017_2018_p::ALW_020, [ALW_2A3]",cont,copy,N/A,# of drinks - Tuesday,Number of drinks on Tuesday,drinks,"[0,50]",Number of drinks on Tuesday,DailyConsumptionTuesday,Number of drinks on Tuesday, -ALW_2A3,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A3, cchs2003_p::ALCC_5A3, cchs2005_p::ALCE_5A3, cchs2015_2016_p::ALW_020, cchs2017_2018_p::ALW_020, [ALW_2A3]",cont,NA::a,N/A,not applicable,not applicable,drinks,996,not applicable,DailyConsumptionTuesday,Number of drinks on Tuesday, -ALW_2A3,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A3, cchs2003_p::ALCC_5A3, cchs2005_p::ALCE_5A3, cchs2015_2016_p::ALW_020, cchs2017_2018_p::ALW_020, [ALW_2A3]",cont,NA::b,N/A,missing,missing,drinks,"[997,999]",don't know (997); refusal (998); not stated (999),DailyConsumptionTuesday,Number of drinks on Tuesday, -ALW_2A3,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A3, cchs2003_p::ALCC_5A3, cchs2005_p::ALCE_5A3, cchs2015_2016_p::ALW_020, cchs2017_2018_p::ALW_020, [ALW_2A3]",cont,NA::b,N/A,missing,missing,drinks,else,else,DailyConsumptionTuesday,Number of drinks on Tuesday, -ALW_2A4,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A4, cchs2003_p::ALCC_5A4, cchs2005_p::ALCE_5A4, cchs2015_2016_p::ALW_025, cchs2017_2018_p::ALW_025, [ALW_2A4]",cont,copy,N/A,# of drinks - Wednesday,Number of drinks on Wednesday,drinks,"[0,50]",Number of drinks on Wednesday,DailyConsumptionWednesday,Number of drinks on Wednesday, -ALW_2A4,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A4, cchs2003_p::ALCC_5A4, cchs2005_p::ALCE_5A4, cchs2015_2016_p::ALW_025, cchs2017_2018_p::ALW_025, [ALW_2A4]",cont,NA::a,N/A,not applicable,not applicable,drinks,996,not applicable,DailyConsumptionWednesday,Number of drinks on Wednesday, -ALW_2A4,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A4, cchs2003_p::ALCC_5A4, cchs2005_p::ALCE_5A4, cchs2015_2016_p::ALW_025, cchs2017_2018_p::ALW_025, [ALW_2A4]",cont,NA::b,N/A,missing,missing,drinks,"[997,999]",don't know (997); refusal (998); not stated (999),DailyConsumptionWednesday,Number of drinks on Wednesday, -ALW_2A4,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A4, cchs2003_p::ALCC_5A4, cchs2005_p::ALCE_5A4, cchs2015_2016_p::ALW_025, cchs2017_2018_p::ALW_025, [ALW_2A4]",cont,NA::b,N/A,missing,missing,drinks,else,else,DailyConsumptionWednesday,Number of drinks on Wednesday, -ALW_2A5,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A5, cchs2003_p::ALCC_5A5, cchs2005_p::ALCE_5A5, cchs2015_2016_p::ALW_030, cchs2017_2018_p::ALW_030, [ALW_2A5]",cont,copy,N/A,# of drinks - Thursday,Number of drinks on Thursday,drinks,"[0,50]",Number of drinks on Thursday,DailyConsumptionThursday,Number of drinks on Thursday, -ALW_2A5,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A5, cchs2003_p::ALCC_5A5, cchs2005_p::ALCE_5A5, cchs2015_2016_p::ALW_030, cchs2017_2018_p::ALW_030, [ALW_2A5]",cont,NA::a,N/A,not applicable,not applicable,drinks,996,not applicable,DailyConsumptionThursday,Number of drinks on Thursday, -ALW_2A5,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A5, cchs2003_p::ALCC_5A5, cchs2005_p::ALCE_5A5, cchs2015_2016_p::ALW_030, cchs2017_2018_p::ALW_030, [ALW_2A5]",cont,NA::b,N/A,missing,missing,drinks,"[997,999]",don't know (997); refusal (998); not stated (999),DailyConsumptionThursday,Number of drinks on Thursday, -ALW_2A5,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A5, cchs2003_p::ALCC_5A5, cchs2005_p::ALCE_5A5, cchs2015_2016_p::ALW_030, cchs2017_2018_p::ALW_030, [ALW_2A5]",cont,NA::b,N/A,missing,missing,drinks,else,else,DailyConsumptionThursday,Number of drinks on Thursday, -ALW_2A6,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A6, cchs2003_p::ALCC_5A6, cchs2005_p::ALCE_5A6, cchs2015_2016_p::ALW_035, cchs2017_2018_p::ALW_035, [ALW_2A6]",cont,copy,N/A,# of drinks - Friday,Number of drinks on Friday,drinks,"[0,50]",Number of drinks on Friday,DailyConsumptionFriday,Number of drinks on Friday, -ALW_2A6,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A6, cchs2003_p::ALCC_5A6, cchs2005_p::ALCE_5A6, cchs2015_2016_p::ALW_035, cchs2017_2018_p::ALW_035, [ALW_2A6]",cont,NA::a,N/A,not applicable,not applicable,drinks,996,not applicable,DailyConsumptionFriday,Number of drinks on Friday, -ALW_2A6,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A6, cchs2003_p::ALCC_5A6, cchs2005_p::ALCE_5A6, cchs2015_2016_p::ALW_035, cchs2017_2018_p::ALW_035, [ALW_2A6]",cont,NA::b,N/A,missing,missing,drinks,"[997,999]",don't know (997); refusal (998); not stated (999),DailyConsumptionFriday,Number of drinks on Friday, -ALW_2A6,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A6, cchs2003_p::ALCC_5A6, cchs2005_p::ALCE_5A6, cchs2015_2016_p::ALW_035, cchs2017_2018_p::ALW_035, [ALW_2A6]",cont,NA::b,N/A,missing,missing,drinks,else,else,DailyConsumptionFriday,Number of drinks on Friday, -ALW_2A7,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A7, cchs2003_p::ALCC_5A7, cchs2005_p::ALCE_5A7, cchs2015_2016_p::ALW_040, cchs2017_2018_p::ALW_040, [ALW_2A7]",cont,copy,N/A,# of drinks - Saturday,Number of drinks on Saturday,drinks,"[0,50]",Number of drinks on Saturday,DailyConsumptionSaturday,Number of drinks on Saturday, -ALW_2A7,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A7, cchs2003_p::ALCC_5A7, cchs2005_p::ALCE_5A7, cchs2015_2016_p::ALW_040, cchs2017_2018_p::ALW_040, [ALW_2A7]",cont,NA::a,N/A,not applicable,not applicable,drinks,996,not applicable,DailyConsumptionSaturday,Number of drinks on Saturday, -ALW_2A7,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A7, cchs2003_p::ALCC_5A7, cchs2005_p::ALCE_5A7, cchs2015_2016_p::ALW_040, cchs2017_2018_p::ALW_040, [ALW_2A7]",cont,NA::b,N/A,missing,missing,drinks,"[997,999]",don't know (997); refusal (998); not stated (999),DailyConsumptionSaturday,Number of drinks on Saturday, -ALW_2A7,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCA_5A7, cchs2003_p::ALCC_5A7, cchs2005_p::ALCE_5A7, cchs2015_2016_p::ALW_040, cchs2017_2018_p::ALW_040, [ALW_2A7]",cont,NA::b,N/A,missing,missing,drinks,else,else,DailyConsumptionSaturday,Number of drinks on Saturday, -ALWDDLY,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCADDLY , cchs2003_p::ALCCDDLY , cchs2005_p::ALCEDDLY, cchs2015_2016_p::ALWDVDLY, cchs2017_2018_p::ALWDVDLY, [ALWDDLY]",cont,copy,N/A,drinks/day,drinks/day,drinks/day,"[0,40]",drinks per day,AverageDailyConsumption,Average daily alcohol consumption,"2007-08, 09-10, 2010, 2012 cycles are categorical" -ALWDDLY,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCADDLY , cchs2003_p::ALCCDDLY , cchs2005_p::ALCEDDLY, cchs2015_2016_p::ALWDVDLY, cchs2017_2018_p::ALWDVDLY, [ALWDDLY]",cont,NA::a,N/A,not applicable,not applicable,drinks/day,996,Not applicable,AverageDailyConsumption,Average daily alcohol consumption, -ALWDDLY,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCADDLY , cchs2003_p::ALCCDDLY , cchs2005_p::ALCEDDLY, cchs2015_2016_p::ALWDVDLY, cchs2017_2018_p::ALWDVDLY, [ALWDDLY]",cont,NA::b,N/A,missing,missing,drinks/day,"[997,999]",don't know (997); refusal (998); not stated (9),AverageDailyConsumption,Average daily alcohol consumption, -ALWDDLY,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCADDLY , cchs2003_p::ALCCDDLY , cchs2005_p::ALCEDDLY, cchs2015_2016_p::ALWDVDLY, cchs2017_2018_p::ALWDVDLY, [ALWDDLY]",cont,NA::b,N/A,missing,missing,drinks/day,else,else,AverageDailyConsumption,Average daily alcohol consumption, -ALWDWKY,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCADWKY, cchs2003_p::ALCCDWKY, cchs2005_p::ALCEDWKY, cchs2015_2016_p::ALWDVWKY, cchs2017_2018_p::ALWDVWKY, [ALWDWKY]",cont,copy,N/A,drinks/week,drinks/week,drinks/week,"[0,449]",drinks per week,drinks/week,Weekly consumption of alcohol,shown as categorical variable in CCHS 2014 cycle -ALWDWKY,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCADWKY, cchs2003_p::ALCCDWKY, cchs2005_p::ALCEDWKY, cchs2015_2016_p::ALWDVWKY, cchs2017_2018_p::ALWDVWKY, [ALWDWKY]",cont,NA::a,N/A,not applicable,not applicable,drinks/week,996,not applicable (996),drinks/week,Weekly consumption of alcohol, -ALWDWKY,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCADWKY, cchs2003_p::ALCCDWKY, cchs2005_p::ALCEDWKY, cchs2015_2016_p::ALWDVWKY, cchs2017_2018_p::ALWDVWKY, [ALWDWKY]",cont,NA::b,N/A,missing,missing,drinks/week,"[997,999]",don't know (997); refusal (998); not stated (999),drinks/week,Weekly consumption of alcohol, -ALWDWKY,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::ALCADWKY, cchs2003_p::ALCCDWKY, cchs2005_p::ALCEDWKY, cchs2015_2016_p::ALWDVWKY, cchs2017_2018_p::ALWDVWKY, [ALWDWKY]",cont,NA::b,N/A,missing,missing,drinks/week,else,else,drinks/week,Weekly consumption of alcohol, -ALWDVSTR_der,ALWDVSTR_der_catN/A_Func::low_drink_short_fun,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALWDWKY, ALC_1, ALW_1, ALW_2A1, ALW_2A2, ALW_2A3, ALW_2A4, ALW_2A5, ALW_2A6, ALW_2A7]",N/A,Func::low_drink_short_fun,N/A,N/A,N/A,N/A,N/A,N/A,Short Term Drinking Risk,Low drinking - Increased short term risks due to drinking,"Risk based on Canada's Low Risk Alcohol Drinking Guidelines. Refer to https://osf.io/ykau5/ . Derived from DHH_SEX, ALWDWKY, ALC_1, ALW_1, ALW_2A1, ALW_2A2, ALW_2A3, ALW_2A4, ALW_2A5, ALW_2A6, ALW_2A7." -ALWDVSTR_der,ALWDVSTR_der_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALWDWKY, ALC_1, ALW_1, ALW_2A1, ALW_2A2, ALW_2A3, ALW_2A4, ALW_2A5, ALW_2A6, ALW_2A7]",N/A,1,2,Increased short term health risk,Increased short term health risk due to drinking,N/A,1,Increased short term health risk due to drinking,Short Term Drinking Risk,Low drinking - Increased short term risks due to drinking, -ALWDVSTR_der,ALWDVSTR_der_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALWDWKY, ALC_1, ALW_1, ALW_2A1, ALW_2A2, ALW_2A3, ALW_2A4, ALW_2A5, ALW_2A6, ALW_2A7]",N/A,2,2,No increased short term health risk,No increased short term health risk due to drinking,N/A,2,No increased short term health risk due to drinking,Short Term Drinking Risk,Low drinking - Increased short term risks due to drinking, -ALWDVSTR_der,ALWDVSTR_der_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALWDWKY, ALC_1, ALW_1, ALW_2A1, ALW_2A2, ALW_2A3, ALW_2A4, ALW_2A5, ALW_2A6, ALW_2A7]",N/A,NA::b,2,missing,missing,N/A,N/A,missing,Short Term Drinking Risk,Low drinking - Increased short term risks due to drinking, -ALWDVLTR_der,ALWDVLTR_der_catN/A_Func::low_drink_long_fun,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALWDWKY, ALC_1, ALW_1, ALW_2A1, ALW_2A2, ALW_2A3, ALW_2A4, ALW_2A5, ALW_2A6, ALW_2A7]",N/A,Func::low_drink_long_fun,N/A,N/A,N/A,N/A,N/A,N/A,Long Term Drinking Risk,Low drinking - Increased long term risks due to drinking, -ALWDVLTR_der,ALWDVLTR_der_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALWDWKY, ALC_1, ALW_1, ALW_2A1, ALW_2A2, ALW_2A3, ALW_2A4, ALW_2A5, ALW_2A6, ALW_2A7]",N/A,1,2,Increased long term health risk,Increased long term health risk due to drinking,N/A,1,Increased long term health risk due to drinking,Long Term Drinking Risk,Low drinking - Increased long term risks due to drinking,"Risk based on Canada's Low Risk Alcohol Drinking Guidelines. Refer to https://osf.io/ykau5/ . Derived from DHH_SEX, ALWDWKY, ALC_1, ALW_1, ALW_2A1, ALW_2A2, ALW_2A3, ALW_2A4, ALW_2A5, ALW_2A6, ALW_2A7." -ALWDVLTR_der,ALWDVLTR_der_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALWDWKY, ALC_1, ALW_1, ALW_2A1, ALW_2A2, ALW_2A3, ALW_2A4, ALW_2A5, ALW_2A6, ALW_2A7]",N/A,2,2,No increased long term health risk,No increased long term health risk due to drinking,N/A,2,No increased long term health risk due to drinking,Long Term Drinking Risk,Low drinking - Increased long term risks due to drinking, -ALWDVLTR_der,ALWDVLTR_der_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALWDWKY, ALC_1, ALW_1, ALW_2A1, ALW_2A2, ALW_2A3, ALW_2A4, ALW_2A5, ALW_2A6, ALW_2A7]",N/A,NA::b,2,missing,missing,N/A,N/A,missing,Long Term Drinking Risk,Low drinking - Increased long term risks due to drinking, -binge_drinker,binge_drinker_catN/A_Func::binge_drinker_fun,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALW_1, ALW_2A1, ALW_2A2, ALW_2A3, ALW_2A4, ALW_2A5, ALW_2A6, ALW_2A7]",N/A,Func::binge_drinker_fun,N/A,N/A,N/A,N/A,N/A,N/A,Binge Drinker,Binge Drinker,"Derived from DHH_SEX, ALW_2A1, ALW_2A2, ALW_2A3, ALW_2A4, ALW_2A5, ALW_2A6, ALW_2A7" -binge_drinker,binge_drinker_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALW_1, ALW_2A1, ALW_2A2, ALW_2A3, ALW_2A4, ALW_2A5, ALW_2A6, ALW_2A7]",N/A,1,2,Binge drinker,Binge drinker,N/A,N/A,Binge drinker,Binge Drinker,Binge Drinker, -binge_drinker,binge_drinker_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALW_1, ALW_2A1, ALW_2A2, ALW_2A3, ALW_2A4, ALW_2A5, ALW_2A6, ALW_2A7]",N/A,2,2,Regular drinker,Regular drinker,N/A,N/A,Regular drinker,Binge Drinker,Binge Drinker, -binge_drinker,binge_drinker_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALW_1, ALW_2A1, ALW_2A2, ALW_2A3, ALW_2A4, ALW_2A5, ALW_2A6, ALW_2A7]",N/A,NA::a,2,Not applicable,Not applicable,N/A,N/A,Not applicable,Binge Drinker,Binge Drinker, -binge_drinker,binge_drinker_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALW_1, ALW_2A1, ALW_2A2, ALW_2A3, ALW_2A4, ALW_2A5, ALW_2A6, ALW_2A7]",N/A,NA::b,2,missing,missing,N/A,N/A,missing,Binge Drinker,Binge Drinker, -CCC_031,CCC_031_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_031, cchs2003_p::CCCC_031, cchs2005_p::CCCE_031, cchs2015_2016_p::CCC_015, cchs2017_2018_p::CCC_015, [CCC_031]",cat,1,2,Asthma,Asthma,N/A,1,Yes (Do you have asthma?),Asthma,Do you have asthma?, -CCC_031,CCC_031_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_031, cchs2003_p::CCCC_031, cchs2005_p::CCCE_031, cchs2015_2016_p::CCC_015, cchs2017_2018_p::CCC_015, [CCC_031]",cat,2,2,No asthma,No asthma,N/A,2,No (Do you have asthma?),Asthma,Do you have asthma?, -CCC_031,CCC_031_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_031, cchs2003_p::CCCC_031, cchs2005_p::CCCE_031, cchs2015_2016_p::CCC_015, cchs2017_2018_p::CCC_015, [CCC_031]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Asthma,Do you have asthma?, -CCC_031,CCC_031_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_031, cchs2003_p::CCCC_031, cchs2005_p::CCCE_031, cchs2015_2016_p::CCC_015, cchs2017_2018_p::CCC_015, [CCC_031]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Asthma,Do you have asthma?, -CCC_031,CCC_031_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_031, cchs2003_p::CCCC_031, cchs2005_p::CCCE_031, cchs2015_2016_p::CCC_015, cchs2017_2018_p::CCC_015, [CCC_031]",cat,NA::b,2,missing,missing,N/A,else,else,Asthma,Do you have asthma?, -CCC_041,CCC_041_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_041, cchs2003_p::CCCC_041, cchs2005_p::CCCE_041, cchs2015_2016_p::CCC_045, cchs2017_2018_p::CCC_045, [CCC_041]",cat,1,2,Fibromyalgia,Fibromyalgia,N/A,1,Yes (Do you have Fibromyalgia?),Fibromyalgia,Do you have Fibromyalgia?,Missing data 2007-2013/14 -CCC_041,CCC_041_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_041, cchs2003_p::CCCC_041, cchs2005_p::CCCE_041, cchs2015_2016_p::CCC_045, cchs2017_2018_p::CCC_045, [CCC_041]",cat,2,2,No Fibromyalgia,Fibromyalgia,N/A,2,No (Do you have Fibromyalgia?),Fibromyalgia,Do you have Fibromyalgia?,Missing data 2007-2013/15 -CCC_041,CCC_041_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_041, cchs2003_p::CCCC_041, cchs2005_p::CCCE_041, cchs2015_2016_p::CCC_045, cchs2017_2018_p::CCC_045, [CCC_041]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Fibromyalgia,Do you have Fibromyalgia?,Missing data 2007-2013/16 -CCC_041,CCC_041_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_041, cchs2003_p::CCCC_041, cchs2005_p::CCCE_041, cchs2015_2016_p::CCC_045, cchs2017_2018_p::CCC_045, [CCC_041]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Fibromyalgia,Do you have Fibromyalgia?,Missing data 2007-2013/17 -CCC_041,CCC_041_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_041, cchs2003_p::CCCC_041, cchs2005_p::CCCE_041, cchs2015_2016_p::CCC_045, cchs2017_2018_p::CCC_045, [CCC_041]",cat,NA::b,2,missing,missing,N/A,else,else,Fibromyalgia,Do you have Fibromyalgia?,Missing data 2007-2013/18 -CCC_051,CCC_051_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_051, cchs2003_p::CCCC_051, cchs2005_p::CCCE_051, cchs2015_2016_p::CCC_050, cchs2017_2018_p::CCC_050, [CCC_051]",cat,1,2,Yes,Arthritis/Rheumatism,N/A,1,Yes (Do you have arthritis or rheumatism?),Arthritis/Rheumatism,Do you have arthritis or rheumatism?, -CCC_051,CCC_051_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_051, cchs2003_p::CCCC_051, cchs2005_p::CCCE_051, cchs2015_2016_p::CCC_050, cchs2017_2018_p::CCC_050, [CCC_051]",cat,2,2,No,No Arthritis/Rheumatism,N/A,2,No (Do you have arthritis or rheumatism?),Arthritis/Rheumatism,Do you have arthritis or rheumatism?, -CCC_051,CCC_051_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_051, cchs2003_p::CCCC_051, cchs2005_p::CCCE_051, cchs2015_2016_p::CCC_050, cchs2017_2018_p::CCC_050, [CCC_051]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Arthritis/Rheumatism,Do you have arthritis or rheumatism?, -CCC_051,CCC_051_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_051, cchs2003_p::CCCC_051, cchs2005_p::CCCE_051, cchs2015_2016_p::CCC_050, cchs2017_2018_p::CCC_050, [CCC_051]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Arthritis/Rheumatism,Do you have arthritis or rheumatism?, -CCC_051,CCC_051_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_051, cchs2003_p::CCCC_051, cchs2005_p::CCCE_051, cchs2015_2016_p::CCC_050, cchs2017_2018_p::CCC_050, [CCC_051]",cat,NA::b,2,missing,missing,N/A,else,else,Arthritis/Rheumatism,Do you have arthritis or rheumatism?, -CCC_061,CCC_061_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_061, cchs2003_p::CCCC_061, cchs2005_p::CCCE_061, cchs2015_2016_p::CCC_055, cchs2017_2018_p::CCC_055, [CCC_061]",cat,1,2,Back Problems,Back Problems,N/A,1,Yes (Do you have back problems?),Back Problems,"Do you have back problems, excluding fibromyalgia and arthritis diagnosed by a health professional?", -CCC_061,CCC_061_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_061, cchs2003_p::CCCC_061, cchs2005_p::CCCE_061, cchs2015_2016_p::CCC_055, cchs2017_2018_p::CCC_055, [CCC_061]",cat,2,2,No Back Problems,No Back Problems,N/A,2,No (Do you have back problems?),Back Problems,"Do you have back problems, excluding fibromyalgia and arthritis diagnosed by a health professional?", -CCC_061,CCC_061_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_061, cchs2003_p::CCCC_061, cchs2005_p::CCCE_061, cchs2015_2016_p::CCC_055, cchs2017_2018_p::CCC_055, [CCC_061]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Back Problems,"Do you have back problems, excluding fibromyalgia and arthritis diagnosed by a health professional?", -CCC_061,CCC_061_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_061, cchs2003_p::CCCC_061, cchs2005_p::CCCE_061, cchs2015_2016_p::CCC_055, cchs2017_2018_p::CCC_055, [CCC_061]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Back Problems,"Do you have back problems, excluding fibromyalgia and arthritis diagnosed by a health professional?", -CCC_061,CCC_061_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_061, cchs2003_p::CCCC_061, cchs2005_p::CCCE_061, cchs2015_2016_p::CCC_055, cchs2017_2018_p::CCC_055, [CCC_061]",cat,NA::b,2,missing,missing,N/A,else,else,Back Problems,"Do you have back problems, excluding fibromyalgia and arthritis diagnosed by a health professional?", -CCC_071,CCC_071_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_071, cchs2003_p::CCCC_071, cchs2005_p::CCCE_071, cchs2015_2016_p::CCC_065, cchs2017_2018_p::CCC_065, [CCC_071]",cat,1,2,Yes,Hypertension,N/A,1,Yes (Do you have high blood pressure?),Hypertension,Do you have high blood pressure?, -CCC_071,CCC_071_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_071, cchs2003_p::CCCC_071, cchs2005_p::CCCE_071, cchs2015_2016_p::CCC_065, cchs2017_2018_p::CCC_065, [CCC_071]",cat,2,2,No,No Hypertension,N/A,2,No (Do you have high blood pressure?),Hypertension,Do you have high blood pressure?, -CCC_071,CCC_071_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_071, cchs2003_p::CCCC_071, cchs2005_p::CCCE_071, cchs2015_2016_p::CCC_065, cchs2017_2018_p::CCC_065, [CCC_071]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Hypertension,Do you have high blood pressure?, -CCC_071,CCC_071_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_071, cchs2003_p::CCCC_071, cchs2005_p::CCCE_071, cchs2015_2016_p::CCC_065, cchs2017_2018_p::CCC_065, [CCC_071]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Hypertension,Do you have high blood pressure?, -CCC_071,CCC_071_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_071, cchs2003_p::CCCC_071, cchs2005_p::CCCE_071, cchs2015_2016_p::CCC_065, cchs2017_2018_p::CCC_065, [CCC_071]",cat,NA::b,2,missing,missing,N/A,else,else,Hypertension,Do you have high blood pressure?, -CCC_072,CCC_072_cat2_1,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::CCCE_072, [CCC_072]",cat,1,2,Hypertension diagnosis,Hypertension diagnosis,N/A,1,Yes (Have you ever been diagnosed with high blood pressure?),Hypertension diagnosis,Have you ever been diagnosed with high blood pressure?, -CCC_072,CCC_072_cat2_2,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::CCCE_072, [CCC_072]",cat,2,2,No hypertension diagnosis,No hypertension diagnosis,N/A,2,No (Have you ever been diagnosed with high blood pressure?),Hypertension diagnosis,Have you ever been diagnosed with high blood pressure?, -CCC_072,CCC_072_cat2_NA::a,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::CCCE_072, [CCC_072]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Hypertension diagnosis,Have you ever been diagnosed with high blood pressure?, -CCC_072,CCC_072_cat2_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::CCCE_072, [CCC_072]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Hypertension diagnosis,Have you ever been diagnosed with high blood pressure?, -CCC_072,CCC_072_cat2_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::CCCE_072, [CCC_072]",cat,NA::b,2,missing,missing,N/A,else,else,Hypertension diagnosis,Have you ever been diagnosed with high blood pressure?, -CCC_073,CCC_073_cat2_1,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::CCCE_073, cchs2015_2016_p::CCC_070, cchs2017_2018_p::CCC_070, [CCC_073]",cat,1,2,Hypertension medication,Hypertension medication,N/A,1,Yes (In the past month have you taken any medicine for high blood pressure?),Hypertension medication,In the past month have you taken any medicine for high blood pressure?, -CCC_073,CCC_073_cat2_2,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::CCCE_073, cchs2015_2016_p::CCC_070, cchs2017_2018_p::CCC_070, [CCC_073]",cat,2,2,No hypertension medication,No hypertension medication,N/A,2,No (In the past month have you taken any medicine for high blood pressure?),Hypertension medication,In the past month have you taken any medicine for high blood pressure?, -CCC_073,CCC_073_cat2_NA::a,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::CCCE_073, cchs2015_2016_p::CCC_070, cchs2017_2018_p::CCC_070, [CCC_073]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Hypertension medication,In the past month have you taken any medicine for high blood pressure?, -CCC_073,CCC_073_cat2_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::CCCE_073, cchs2015_2016_p::CCC_070, cchs2017_2018_p::CCC_070, [CCC_073]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Hypertension medication,In the past month have you taken any medicine for high blood pressure?, -CCC_073,CCC_073_cat2_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::CCCE_073, cchs2015_2016_p::CCC_070, cchs2017_2018_p::CCC_070, [CCC_073]",cat,NA::b,2,missing,missing,N/A,else,else,Hypertension medication,In the past month have you taken any medicine for high blood pressure?, -CCC_081,CCC_081_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_081, cchs2003_p::CCCC_081, cchs2005_p::CCCE_081, cchs2015_2016_p::CCC_140, cchs2017_2018_p::CCC_140, [CCC_081]",cat,1,2,Migraine Headache,Migraine Headache,N/A,1,Yes (Do you have Migraine Headaches?),Migraine Headache,"Remember, we're interested in conditions diagnosed by a health professional. Do you have migraine headaches?","2011 onward asks, ""Remember, we are interested in conditions diagnosed by a health professional and that are expected to last or have already lasted 6 months or more. Do you have migraine headaches?""" -CCC_081,CCC_081_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_081, cchs2003_p::CCCC_081, cchs2005_p::CCCE_081, cchs2015_2016_p::CCC_140, cchs2017_2018_p::CCC_140, [CCC_081]",cat,2,2,No Migraine Headache,No Migraine Headache,N/A,2,No (Do you have Migraine Headaches?),Migraine Headache,"Remember, we're interested in conditions diagnosed by a health professional. Do you have migraine headaches?","2011 onward asks, ""Remember, we are interested in conditions diagnosed by a health professional and that are expected to last or have already lasted 6 months or more. Do you have migraine headaches?""" -CCC_081,CCC_081_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_081, cchs2003_p::CCCC_081, cchs2005_p::CCCE_081, cchs2015_2016_p::CCC_140, cchs2017_2018_p::CCC_140, [CCC_081]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Migraine Headache,"Remember, we're interested in conditions diagnosed by a health professional. Do you have migraine headaches?","2011 onward asks, ""Remember, we are interested in conditions diagnosed by a health professional and that are expected to last or have already lasted 6 months or more. Do you have migraine headaches?""" -CCC_081,CCC_081_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_081, cchs2003_p::CCCC_081, cchs2005_p::CCCE_081, cchs2015_2016_p::CCC_140, cchs2017_2018_p::CCC_140, [CCC_081]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Migraine Headache,"Remember, we're interested in conditions diagnosed by a health professional. Do you have migraine headaches?","2011 onward asks, ""Remember, we are interested in conditions diagnosed by a health professional and that are expected to last or have already lasted 6 months or more. Do you have migraine headaches?""" -CCC_081,CCC_081_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_081, cchs2003_p::CCCC_081, cchs2005_p::CCCE_081, cchs2015_2016_p::CCC_140, cchs2017_2018_p::CCC_140, [CCC_081]",cat,NA::b,2,missing,missing,N/A,else,else,Migraine Headache,"Remember, we're interested in conditions diagnosed by a health professional. Do you have migraine headaches?","2011 onward asks, ""Remember, we are interested in conditions diagnosed by a health professional and that are expected to last or have already lasted 6 months or more. Do you have migraine headaches?""" -CCC_091,CCC_091_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_91B, cchs2003_p::CCCC_91B, cchs2015_2016_p::CCC_030, cchs2017_2018_p::CCC_030, [CCC_091]",cat,1,2,COPD/emphysema/bronchitis,COPD/emphysema/bronchitis,N/A,1,"Yes (Do you have COPD(eg bronchitis,emphysema)?)",COPD/emphysema/bronchitis,"Do you have COPD (eg bronchitis,emphysema)?", -CCC_091,CCC_091_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_91B, cchs2003_p::CCCC_91B, cchs2015_2016_p::CCC_030, cchs2017_2018_p::CCC_030, [CCC_091]",cat,2,2,No COPD/emphysema/bronchitis,No COPD/emphysema/bronchitis,N/A,2,"No (Do you have COPD(eg bronchitis,emphysema)?)",COPD/emphysema/bronchitis,"Do you have COPD (eg bronchitis,emphysema)?", -CCC_091,CCC_091_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_91B, cchs2003_p::CCCC_91B, cchs2015_2016_p::CCC_030, cchs2017_2018_p::CCC_030, [CCC_091]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,COPD/emphysema/bronchitis,"Do you have COPD (eg bronchitis,emphysema)?", -CCC_091,CCC_091_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_91B, cchs2003_p::CCCC_91B, cchs2015_2016_p::CCC_030, cchs2017_2018_p::CCC_030, [CCC_091]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),COPD/emphysema/bronchitis,"Do you have COPD (eg bronchitis,emphysema)?", -CCC_091,CCC_091_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_91B, cchs2003_p::CCCC_91B, cchs2015_2016_p::CCC_030, cchs2017_2018_p::CCC_030, [CCC_091]",cat,NA::b,2,missing,missing,N/A,else,else,COPD/emphysema/bronchitis,"Do you have COPD (eg bronchitis,emphysema)?", -CCC_101,CCC_101_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_101, cchs2003_p::CCCC_101, cchs2005_p::CCCE_101, cchs2015_2016_p::CCC_095, cchs2017_2018_p::CCC_095, [CCC_101]",cat,1,2,Yes,Diabetes,N/A,1,Yes (Do you have diabetes?),Diabetes,Do you have diabetes?, -CCC_101,CCC_101_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_101, cchs2003_p::CCCC_101, cchs2005_p::CCCE_101, cchs2015_2016_p::CCC_095, cchs2017_2018_p::CCC_095, [CCC_101]",cat,2,2,No,No Diabetes,N/A,2,No (Do you have diabetes?),Diabetes,Do you have diabetes?, -CCC_101,CCC_101_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_101, cchs2003_p::CCCC_101, cchs2005_p::CCCE_101, cchs2015_2016_p::CCC_095, cchs2017_2018_p::CCC_095, [CCC_101]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Diabetes,Do you have diabetes?, -CCC_101,CCC_101_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_101, cchs2003_p::CCCC_101, cchs2005_p::CCCE_101, cchs2015_2016_p::CCC_095, cchs2017_2018_p::CCC_095, [CCC_101]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Diabetes,Do you have diabetes?, -CCC_101,CCC_101_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_101, cchs2003_p::CCCC_101, cchs2005_p::CCCE_101, cchs2015_2016_p::CCC_095, cchs2017_2018_p::CCC_095, [CCC_101]",cat,NA::b,2,missing,missing,N/A,else,else,Diabetes,Do you have diabetes?, -CCC_111,CCC_111_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::CCCA_111, cchs2003_p::CCCC_111, cchs2005_p::CCCE_111",cat,1,2,Epilepsy,Epilepsy,N/A,1,Yes (Do you have epilepsy?),Epilepsy,Do you have epilepsy?, -CCC_111,CCC_111_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::CCCA_111, cchs2003_p::CCCC_111, cchs2005_p::CCCE_111",cat,2,2,No Epilepsy,No Epilepsy,N/A,2,No (Do you have epilepsy?),Epilepsy,Do you have epilepsy?, -CCC_111,CCC_111_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::CCCA_111, cchs2003_p::CCCC_111, cchs2005_p::CCCE_111",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Epilepsy,Do you have epilepsy?, -CCC_111,CCC_111_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::CCCA_111, cchs2003_p::CCCC_111, cchs2005_p::CCCE_111",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Epilepsy,Do you have epilepsy?, -CCC_111,CCC_111_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::CCCA_111, cchs2003_p::CCCC_111, cchs2005_p::CCCE_111",cat,NA::b,2,missing,missing,N/A,else,else,Epilepsy,Do you have epilepsy?, -CCC_121,CCC_121_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_121, cchs2003_p::CCCC_121, cchs2005_p::CCCE_121, cchs2015_2016_p::CCC_085, cchs2017_2018_p::CCC_085, [CCC_121]",cat,1,2,Yes,Heart Disease,N/A,1,Yes (Do you have heart disease?),Heart Disease,Do you have heart disease?, -CCC_121,CCC_121_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_121, cchs2003_p::CCCC_121, cchs2005_p::CCCE_121, cchs2015_2016_p::CCC_085, cchs2017_2018_p::CCC_085, [CCC_121]",cat,2,2,No,No Heart Disease,N/A,2,No (Do you have heart disease?),Heart Disease,Do you have heart disease?, -CCC_121,CCC_121_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_121, cchs2003_p::CCCC_121, cchs2005_p::CCCE_121, cchs2015_2016_p::CCC_085, cchs2017_2018_p::CCC_085, [CCC_121]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Heart Disease,Do you have heart disease?, -CCC_121,CCC_121_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_121, cchs2003_p::CCCC_121, cchs2005_p::CCCE_121, cchs2015_2016_p::CCC_085, cchs2017_2018_p::CCC_085, [CCC_121]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Heart Disease,Do you have heart disease?, -CCC_121,CCC_121_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_121, cchs2003_p::CCCC_121, cchs2005_p::CCCE_121, cchs2015_2016_p::CCC_085, cchs2017_2018_p::CCC_085, [CCC_121]",cat,NA::b,2,missing,missing,N/A,else,else,Heart Disease,Do you have heart disease?, -CCC_131,CCC_131_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_131, cchs2003_p::CCCC_131, cchs2005_p::CCCE_131, cchs2015_2016_p::CCC_130, cchs2017_2018_p::CCC_130, [CCC_131]",cat,1,2,Yes,Cancer,N/A,1,Yes (Do you have cancer?),Cancer,Do you have cancer?, -CCC_131,CCC_131_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_131, cchs2003_p::CCCC_131, cchs2005_p::CCCE_131, cchs2015_2016_p::CCC_130, cchs2017_2018_p::CCC_130, [CCC_131]",cat,2,2,No,No Cancer,N/A,2,No (Do you have cancer?),Cancer,Do you have cancer?, -CCC_131,CCC_131_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_131, cchs2003_p::CCCC_131, cchs2005_p::CCCE_131, cchs2015_2016_p::CCC_130, cchs2017_2018_p::CCC_130, [CCC_131]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Cancer,Do you have cancer?, -CCC_131,CCC_131_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_131, cchs2003_p::CCCC_131, cchs2005_p::CCCE_131, cchs2015_2016_p::CCC_130, cchs2017_2018_p::CCC_130, [CCC_131]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Cancer,Do you have cancer?, -CCC_131,CCC_131_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_131, cchs2003_p::CCCC_131, cchs2005_p::CCCE_131, cchs2015_2016_p::CCC_130, cchs2017_2018_p::CCC_130, [CCC_131]",cat,NA::b,2,missing,missing,N/A,else,else,Cancer,Do you have cancer?, -CCC_151,CCC_151_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_151, cchs2003_p::CCCC_151, cchs2005_p::CCCE_151, cchs2015_2016_p::CCC_090, cchs2017_2018_p::CCC_090, [CCC_151]",cat,1,2,Yes,Stroke,N/A,1,Yes (Do you suffer from the effects of stroke?),Stroke,Do you suffer from effects of stroke?, -CCC_151,CCC_151_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_151, cchs2003_p::CCCC_151, cchs2005_p::CCCE_151, cchs2015_2016_p::CCC_090, cchs2017_2018_p::CCC_090, [CCC_151]",cat,2,2,No,No Stroke,N/A,2,No (Do you suffer from the effects of stroke?),Stroke,Do you suffer from effects of stroke?, -CCC_151,CCC_151_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_151, cchs2003_p::CCCC_151, cchs2005_p::CCCE_151, cchs2015_2016_p::CCC_090, cchs2017_2018_p::CCC_090, [CCC_151]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Stroke,Do you suffer from effects of stroke?, -CCC_151,CCC_151_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_151, cchs2003_p::CCCC_151, cchs2005_p::CCCE_151, cchs2015_2016_p::CCC_090, cchs2017_2018_p::CCC_090, [CCC_151]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Stroke,Do you suffer from effects of stroke?, -CCC_151,CCC_151_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::CCCA_151, cchs2003_p::CCCC_151, cchs2005_p::CCCE_151, cchs2015_2016_p::CCC_090, cchs2017_2018_p::CCC_090, [CCC_151]",cat,NA::b,2,missing,missing,N/A,else,else,Stroke,Do you suffer from effects of stroke?, -CCC_171,CCC_171_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::CCCA_171, cchs2003_p::CCCC_171, cchs2005_p::CCCE_171, [CCC_171]",cat,1,2,Yes,Bowel disorder,N/A,1,Yes (Do you have a bowel disorder?),Bowel disorder,Do you have a bowel disorder such as Crohn's Disease or colitis?, -CCC_171,CCC_171_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::CCCA_171, cchs2003_p::CCCC_171, cchs2005_p::CCCE_171, [CCC_171]",cat,2,2,No,No bowel disorder,N/A,2,No (Do you have a bowel disorder?),Bowel disorder,Do you have a bowel disorder such as Crohn's Disease or colitis?, -CCC_171,CCC_171_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::CCCA_171, cchs2003_p::CCCC_171, cchs2005_p::CCCE_171, [CCC_171]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Bowel disorder,Do you have a bowel disorder such as Crohn's Disease or colitis?, -CCC_171,CCC_171_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::CCCA_171, cchs2003_p::CCCC_171, cchs2005_p::CCCE_171, [CCC_171]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Bowel disorder,Do you have a bowel disorder such as Crohn's Disease or colitis?, -CCC_171,CCC_171_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::CCCA_171, cchs2003_p::CCCC_171, cchs2005_p::CCCE_171, [CCC_171]",cat,NA::b,2,missing,missing,N/A,else,else,Bowel disorder,Do you have a bowel disorder such as Crohn's Disease or colitis?, -CCC_251,CCC_251_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2010_p, cchs2014_p","cchs2001_p::CCCA_251, cchs2003_p::CCCC_251, cchs2005_p::CCCE_251, [CCC_251]",cat,1,2,Yes,Chronic fatigue,N/A,1,Yes (Do you have chronic fatigue syndrome?),Chronic fatigue syndrome,Do you have chronic fatigue syndrome?, -CCC_251,CCC_251_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2010_p, cchs2014_p","cchs2001_p::CCCA_251, cchs2003_p::CCCC_251, cchs2005_p::CCCE_251, [CCC_251]",cat,2,2,No,No chronic fatigue,N/A,2,No (Do you have chronic fatigue syndrome?),Chronic fatigue syndrome,Do you have chronic fatigue syndrome?, -CCC_251,CCC_251_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2010_p, cchs2014_p","cchs2001_p::CCCA_251, cchs2003_p::CCCC_251, cchs2005_p::CCCE_251, [CCC_251]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Chronic fatigue syndrome,Do you have chronic fatigue syndrome?, -CCC_251,CCC_251_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2010_p, cchs2014_p","cchs2001_p::CCCA_251, cchs2003_p::CCCC_251, cchs2005_p::CCCE_251, [CCC_251]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Chronic fatigue syndrome,Do you have chronic fatigue syndrome?, -CCC_251,CCC_251_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2010_p, cchs2014_p","cchs2001_p::CCCA_251, cchs2003_p::CCCC_251, cchs2005_p::CCCE_251, [CCC_251]",cat,NA::b,2,missing,missing,N/A,else,else,Chronic fatigue syndrome,Do you have chronic fatigue syndrome?, -CCC_280,CCC_280_cat2_1,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::CCCC_280, cchs2005_p::CCCE_280, cchs2015_2016_p::CCC_195, cchs2017_2018_p::CCC_195, [CCC_280]",cat,1,2,Yes,Has a mood disorder,N/A,1,Yes (Do you have a mood disorder?),Mood disorder,Do you have a mood disorder?, -CCC_280,CCC_280_cat2_2,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::CCCC_280, cchs2005_p::CCCE_280, cchs2015_2016_p::CCC_195, cchs2017_2018_p::CCC_195, [CCC_280]",cat,2,2,No,Does not have a mood disorder,N/A,2,No (Do you have a mood disorder?),Mood disorder,Do you have a mood disorder?, -CCC_280,CCC_280_cat2_NA::a,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::CCCC_280, cchs2005_p::CCCE_280, cchs2015_2016_p::CCC_195, cchs2017_2018_p::CCC_195, [CCC_280]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Mood disorder,Do you have a mood disorder?, -CCC_280,CCC_280_cat2_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::CCCC_280, cchs2005_p::CCCE_280, cchs2015_2016_p::CCC_195, cchs2017_2018_p::CCC_195, [CCC_280]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Mood disorder,Do you have a mood disorder?, -CCC_280,CCC_280_cat2_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::CCCC_280, cchs2005_p::CCCE_280, cchs2015_2016_p::CCC_195, cchs2017_2018_p::CCC_195, [CCC_280]",cat,NA::b,2,missing,missing,N/A,else,else,Mood disorder,Do you have a mood disorder?, -CCC_290,CCC_290_cat2_1,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::CCCC_290, cchs2005_p::CCCE_290, cchs2015_2016_p::CCC_200, cchs2017_2018_p::CCC_200, [CCC_290]",cat,1,2,Has an anxiety disorder,Has an anxiety disorder,N/A,1,Yes (Do you have an anxiety disorder?),Anxiety Disorder,Do you have an anxiety disorder?, -CCC_290,CCC_290_cat2_2,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::CCCC_290, cchs2005_p::CCCE_290, cchs2015_2016_p::CCC_200, cchs2017_2018_p::CCC_200, [CCC_290]",cat,2,2,Does not have an anxiety disorder,Does not have an anxiety disorder,N/A,2,No (Do you have an anxiety disorder?),Anxiety Disorder,Do you have an anxiety disorder?, -CCC_290,CCC_290_cat2_NA::a,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::CCCC_290, cchs2005_p::CCCE_290, cchs2015_2016_p::CCC_200, cchs2017_2018_p::CCC_200, [CCC_290]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Anxiety Disorder,Do you have an anxiety disorder?, -CCC_290,CCC_290_cat2_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::CCCC_290, cchs2005_p::CCCE_290, cchs2015_2016_p::CCC_200, cchs2017_2018_p::CCC_200, [CCC_290]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Anxiety Disorder,Do you have an anxiety disorder?, -CCC_290,CCC_290_cat2_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::CCCC_290, cchs2005_p::CCCE_290, cchs2015_2016_p::CCC_200, cchs2017_2018_p::CCC_200, [CCC_290]",cat,NA::b,2,missing,missing,N/A,else,else,Anxiety Disorder,Do you have an anxiety disorder?, -CCC_31A,CCC_31A_cat2_1,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::CCCE_31A, cchs2015_2016_p::CCC_135, cchs2017_2018_p::CCC_135, [CCC_31A]",cat,1,2,Cancer diagnosis,Cancer diagnosis,N/A,1,Yes (Have you ever been diagnosed with cancer?),Cancer Diagnosis,Have you ever been diagnosed with cancer?, -CCC_31A,CCC_31A_cat2_2,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::CCCE_31A, cchs2015_2016_p::CCC_135, cchs2017_2018_p::CCC_135, [CCC_31A]",cat,2,2,No cancer diagnosis,No cancer diagnosis,N/A,2,Yes (Have you ever been diagnosed with cancer?),Cancer Diagnosis,Have you ever been diagnosed with cancer?, -CCC_31A,CCC_31A_cat2_NA::a,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::CCCE_31A, cchs2015_2016_p::CCC_135, cchs2017_2018_p::CCC_135, [CCC_31A]",cat,NA::a,2,not applicable,not applicable,N/A,6,Yes (Have you ever been diagnosed with cancer?),Cancer Diagnosis,Have you ever been diagnosed with cancer?, -CCC_31A,CCC_31A_cat2_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::CCCE_31A, cchs2015_2016_p::CCC_135, cchs2017_2018_p::CCC_135, [CCC_31A]",cat,NA::b,2,missing,missing,N/A,"[7,9]",Yes (Have you ever been diagnosed with cancer?),Cancer Diagnosis,Have you ever been diagnosed with cancer?, -CCC_31A,CCC_31A_cat2_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::CCCE_31A, cchs2015_2016_p::CCC_135, cchs2017_2018_p::CCC_135, [CCC_31A]",cat,NA::b,2,missing,missing,N/A,else,Yes (Have you ever been diagnosed with cancer?),Cancer Diagnosis,Have you ever been diagnosed with cancer?, -CCC_91A,CCC_91A_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2001_p::CCCA_91A, cchs2003_p::CCCC_91A, cchs2005_p::CCCE_91A, [CCC_91A]",cat,1,2,Bronchitis,Chronic bronchitis,N/A,1,Yes (Do you have chronic bronchitis?),Bronchitis,Do you have chronic bronchitis?, -CCC_91A,CCC_91A_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2001_p::CCCA_91A, cchs2003_p::CCCC_91A, cchs2005_p::CCCE_91A, [CCC_91A]",cat,2,2,No bronchitis,No chronic bronchitis,N/A,2,No (Do you have chronic bronchitis?),Bronchitis,Do you have chronic bronchitis?, -CCC_91A,CCC_91A_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2001_p::CCCA_91A, cchs2003_p::CCCC_91A, cchs2005_p::CCCE_91A, [CCC_91A]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Bronchitis,Do you have chronic bronchitis?, -CCC_91A,CCC_91A_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2001_p::CCCA_91A, cchs2003_p::CCCC_91A, cchs2005_p::CCCE_91A, [CCC_91A]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Bronchitis,Do you have chronic bronchitis?, -CCC_91A,CCC_91A_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2001_p::CCCA_91A, cchs2003_p::CCCC_91A, cchs2005_p::CCCE_91A, [CCC_91A]",cat,NA::b,2,missing,missing,N/A,else,else,Bronchitis,Do you have chronic bronchitis?, -CCC_91E,CCC_91E_cat2_1,cat,"cchs2005_p, cchs2007_2008_p","cchs2005_p::CCCE_91E, cchs2007_2008_p::CCC_91E",cat,1,2,Emphysema,Emphysema,N/A,1,Yes (Do you have emphysema?),emphysema,Do you have emphysema?, -CCC_91E,CCC_91E_cat2_2,cat,"cchs2005_p, cchs2007_2008_p","cchs2005_p::CCCE_91E, cchs2007_2008_p::CCC_91E",cat,2,2,No emphysema,No emphysema,N/A,2,No (Do you have emphysema?),emphysema,Do you have emphysema?, -CCC_91E,CCC_91E_cat2_NA::a,cat,"cchs2005_p, cchs2007_2008_p","cchs2005_p::CCCE_91E, cchs2007_2008_p::CCC_91E",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,emphysema,Do you have emphysema?, -CCC_91E,CCC_91E_cat2_NA::b,cat,"cchs2005_p, cchs2007_2008_p","cchs2005_p::CCCE_91E, cchs2007_2008_p::CCC_91E",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),emphysema,Do you have emphysema?, -CCC_91E,CCC_91E_cat2_NA::b,cat,"cchs2005_p, cchs2007_2008_p","cchs2005_p::CCCE_91E, cchs2007_2008_p::CCC_91E",cat,NA::b,2,missing,missing,N/A,else,else,emphysema,Do you have emphysema?, -CCC_91F,CCC_91F_cat2_1,cat,"cchs2005_p, cchs2007_2008_p","cchs2005_p::CCCE_91F, cchs2007_2008_p::CCC_91F",cat,1,2,COPD,COPD,N/A,1,Yes (Do you have COPD?),COPD,Do you have COPD?, -CCC_91F,CCC_91F_cat2_2,cat,"cchs2005_p, cchs2007_2008_p","cchs2005_p::CCCE_91F, cchs2007_2008_p::CCC_91F",cat,2,2,No COPD,No COPD,N/A,2,No (Do you have COPD?),COPD,Do you have COPD?, -CCC_91F,CCC_91F_cat2_NA::a,cat,"cchs2005_p, cchs2007_2008_p","cchs2005_p::CCCE_91F, cchs2007_2008_p::CCC_91F",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,COPD,Do you have COPD?, -CCC_91F,CCC_91F_cat2_NA::b,cat,"cchs2005_p, cchs2007_2008_p","cchs2005_p::CCCE_91F, cchs2007_2008_p::CCC_91F",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),COPD,Do you have COPD?, -CCC_91F,CCC_91F_cat2_NA::b,cat,"cchs2005_p, cchs2007_2008_p","cchs2005_p::CCCE_91F, cchs2007_2008_p::CCC_91F",cat,NA::b,2,missing,missing,N/A,else,else,COPD,Do you have COPD?, -CCC_075,CCC_075_cat2_1,cat,"cchs2015_2016_p, cchs2017_2018_p",[CCC_075],cat,1,2,High blood cholesterol,High blood cholesterol,N/A,1,High blood cholesterol,Blood cholesterol,Do you have high blood cholesterol or lipids?,Respondent are 18+ years old to answer this question in CCHS 2015-2018 -CCC_075,CCC_075_cat2_2,cat,"cchs2015_2016_p, cchs2017_2018_p",[CCC_075],cat,2,2,No high blood cholesterol,No high blood cholesterol,N/A,2,No high blood cholesterol,Blood cholesterol,Do you have high blood cholesterol or lipids?, -CCC_075,CCC_075_cat2_NA::a,cat,"cchs2015_2016_p, cchs2017_2018_p",[CCC_075],cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Blood cholesterol,Do you have high blood cholesterol or lipids?, -CCC_075,CCC_075_cat2_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p",[CCC_075],cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Blood cholesterol,Do you have high blood cholesterol or lipids?, -CCC_075,CCC_075_cat2_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p",[CCC_075],cat,NA::b,2,missing,missing,N/A,else,else,Blood cholesterol,Do you have high blood cholesterol or lipids?, -COPD_Emph_der,COPD_Emph_der_catN/A_Func::COPD_Emph_der_fun1,cat,"cchs2005_p, cchs2007_2008_p","DerivedVar::[DHHGAGE_cont, CCC_91E, CCC_91F]",N/A,Func::COPD_Emph_der_fun1,N/A,N/A,N/A,N/A,N/A,N/A,Respiratory Condition,Respiratory Condition,Derived from COPD and Emphysema variables -COPD_Emph_der,COPD_Emph_der_catN/A_Func::COPD_Emph_der_fun2,cat,"cchs2001_p, cchs2003_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","DerivedVar::[DHHGAGE_cont, CCC_091]",N/A,Func::COPD_Emph_der_fun2,N/A,N/A,N/A,N/A,N/A,N/A,Respiratory Condition,Respiratory Condition,Derived from COPD and Emphysema variables -COPD_Emph_der,COPD_Emph_der_cat3_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHHGAGE_cont, CCC_091]",N/A,1,3,Over 35 years with condition,Age over 35 years with condition,N/A,N/A,Respiratory Condition,Respiratory Condition,Respiratory Condition, -COPD_Emph_der,COPD_Emph_der_cat3_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHHGAGE_cont, CCC_91E, CCC_91F, CCC_091]",N/A,2,3,Under 35 years with condition,Age under 35 years with condition,N/A,N/A,Respiratory Condition,Respiratory Condition,Respiratory Condition, -COPD_Emph_der,COPD_Emph_der_cat3_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHHGAGE_cont, CCC_91E, CCC_91F, CCC_091]",N/A,3,3,No condition,No condition,N/A,N/A,Respiratory Condition,Respiratory Condition,Respiratory Condition, -COPD_Emph_der,COPD_Emph_der_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHHGAGE_cont, CCC_91E, CCC_91F, CCC_091]",N/A,NA::b,3,missing,missing,N/A,N/A,Respiratory Condition,Respiratory Condition,Respiratory Condition, -DHH_OWN,DHH_OWN_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::DHHA_OWN, cchs2003_p::DHHC_OWN, cchs2005_p::DHHE_OWN, [DHH_OWN]",cat,1,2,Yes,Yes,N/A,1,Yes,Dwelling - owned by a member of hsld,Is this dwelling owned by a member of this household?,"Prior to 2009, CCHS restricted this variable to participants who were not living in an institution. In 2011, CCHS changed wording of responses to (1) owner and (2) renter" -DHH_OWN,DHH_OWN_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::DHHA_OWN, cchs2003_p::DHHC_OWN, cchs2005_p::DHHE_OWN, [DHH_OWN]",cat,2,2,No,No,N/A,2,No,Dwelling - owned by a member of hsld,Is this dwelling owned by a member of this household?, -DHH_OWN,DHH_OWN_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::DHHA_OWN, cchs2003_p::DHHC_OWN, cchs2005_p::DHHE_OWN, [DHH_OWN]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Dwelling - owned by a member of hsld,Is this dwelling owned by a member of this household?, -DHH_OWN,DHH_OWN_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::DHHA_OWN, cchs2003_p::DHHC_OWN, cchs2005_p::DHHE_OWN, [DHH_OWN]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Dwelling - owned by a member of hsld,Is this dwelling owned by a member of this household?, -DHH_OWN,DHH_OWN_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::DHHA_OWN, cchs2003_p::DHHC_OWN, cchs2005_p::DHHE_OWN, [DHH_OWN]",cat,NA::b,2,missing,missing,N/A,else,else,Dwelling - owned by a member of hsld,Is this dwelling owned by a member of this household?, -DHH_SEX,DHH_SEX_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::DHHA_SEX, cchs2003_p::DHHC_SEX, cchs2005_p::DHHE_SEX, [DHH_SEX]",cat,1,2,Male,Male,N/A,1,Male,Sex,Sex, -DHH_SEX,DHH_SEX_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::DHHA_SEX, cchs2003_p::DHHC_SEX, cchs2005_p::DHHE_SEX, [DHH_SEX]",cat,2,2,Female,Female,N/A,2,Female,Sex,Sex, -DHH_SEX,DHH_SEX_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::DHHA_SEX, cchs2003_p::DHHC_SEX, cchs2005_p::DHHE_SEX, [DHH_SEX]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Sex,Sex, -DHH_SEX,DHH_SEX_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::DHHA_SEX, cchs2003_p::DHHC_SEX, cchs2005_p::DHHE_SEX, [DHH_SEX]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Sex,Sex, -DHH_SEX,DHH_SEX_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::DHHA_SEX, cchs2003_p::DHHC_SEX, cchs2005_p::DHHE_SEX, [DHH_SEX]",cat,NA::b,2,missing,missing,N/A,else,else,Sex,Sex, -DHHGAGE_5,DHHGAGE_5_cat5_1,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,1,5,age (12 to 19),age (12 to 19),years,"[1,3]",12 To 14 Years (1); 15 To 17 Years (2); 18 To 19 Years (3),Age,Categorical age, -DHHGAGE_5,DHHGAGE_5_cat5_2,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,2,5,age (20 to 39),age (20 to 39),years,"[4,7]",20 To 24 Years (4); 25 To 29 Years (5); 30 To 34 Years (6); 35 To 39 Years (7),Age,Categorical age, -DHHGAGE_5,DHHGAGE_5_cat5_3,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,3,5,age (40 to 59),age (40 to 59),years,"[8,11]",40 To 44 Years (8); 45 To 49 Years (9); 50 To 54 Years (10); 55 To 59 Years (11),Age,Categorical age, -DHHGAGE_5,DHHGAGE_5_cat5_4,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,4,5,age (60 to 79),age (60 to 79),years,"[12,15]",60 To 64 Years (12); 65 To 69 Years (13); 70 To 74 Years (14); 75 To 79 Years (15),Age,Categorical age, -DHHGAGE_5,DHHGAGE_5_cat5_5,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,5,5,age (80 plus),age (80 plus),years,16,80 Years or more,Age,Categorical age, -DHHGAGE_5,DHHGAGE_5_cat8_NA::a,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,NA::a,8,not applicable,not applicable,years,96,not applicable,Age,Categorical age, -DHHGAGE_5,DHHGAGE_5_cat8_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,NA::b,8,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),Age,Categorical age, -DHHGAGE_5,DHHGAGE_5_cat8_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,NA::b,8,else,else,years,else,else,Age,Categorical age, -DHHGAGE_5,DHHGAGE_5_cat5_1,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,1,5,age (12 to 19),age (12 to 19),years,"[1,2]",12 To 14 Years (1); 15 To 19 Years (2),Age,Categorical age, -DHHGAGE_5,DHHGAGE_5_cat5_2,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,2,5,age (20 to 39),age (20 to 39),years,"[3,6]",20 To 24 Years (3); 25 To 29 Years (4); 30 To 34 Years (5); 35 To 39 Years (6),Age,Categorical age, -DHHGAGE_5,DHHGAGE_5_cat5_3,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,3,5,age (40 to 59),age (40 to 59),years,"[7,10]",40 To 44 Years (7); 45 To 49 Years (8); 50 To 54 Years (9); 55 To 59 Years (10),Age,Categorical age, -DHHGAGE_5,DHHGAGE_5_cat5_4,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,4,5,age (60 to 79),age (60 to 79),years,"[11,14]",60 To 64 Years (11); 65 To 69 Years (12); 70 To 74 Years (13); 75 To 79 Years (14),Age,Categorical age, -DHHGAGE_5,DHHGAGE_5_cat5_5,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,5,5,age (80 plus),age (80 plus),years,15,80 Years or more (15),Age,Categorical age, -DHHGAGE_5,DHHGAGE_5_cat8_NA::a,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,NA::a,8,not applicable,not applicable,years,96,not applicable,Age,Categorical age, -DHHGAGE_5,DHHGAGE_5_cat8_NA::b,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,NA::b,8,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),Age,Categorical age, -DHHGAGE_5,DHHGAGE_5_cat8_NA::b,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,NA::b,8,else,else,years,else,else,Age,Categorical age, -DHHGAGE_A,DHHGAGE_A_cat15_1,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,1,15,age (12 to 14),age (12 to 14),years,1,12 to 14 years,Age,Age - (G), -DHHGAGE_A,DHHGAGE_A_cat15_2,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,2,15,age (15 to 19),age (15 to 19),years,2,15 to 19 years,Age,Age - (G), -DHHGAGE_A,DHHGAGE_A_cat15_3,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,3,15,age (20 to 24),age (20 to 24),years,3,20 To 24 Years,Age,Age - (G), -DHHGAGE_A,DHHGAGE_A_cat15_4,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,4,15,age (25 to 29),age (25 to 29),years,4,25 To 29 Years,Age,Age - (G), -DHHGAGE_A,DHHGAGE_A_cat15_5,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,5,15,age (30 to 34),age (30 to 34),years,5,30 To 34 Years,Age,Age - (G), -DHHGAGE_A,DHHGAGE_A_cat15_6,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,6,15,age (35 to 39),age (35 to 39),years,6,35 To 39 Years,Age,Age - (G), -DHHGAGE_A,DHHGAGE_A_cat15_7,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,7,15,age (40 to 44),age (40 to 44),years,7,40 To 44 Years,Age,Age - (G), -DHHGAGE_A,DHHGAGE_A_cat15_8,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,8,15,age (45 to 49),age (45 to 49),years,8,45 To 49 Years,Age,Age - (G), -DHHGAGE_A,DHHGAGE_A_cat15_9,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,9,15,age (50 to 54),age (50 to 54),years,9,50 To 54 Years,Age,Age - (G), -DHHGAGE_A,DHHGAGE_A_cat15_10,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,10,15,age (55 to 59),age (55 to 59),years,10,55 To 59 Years,Age,Age - (G), -DHHGAGE_A,DHHGAGE_A_cat15_11,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,11,15,age (60 to 64),age (60 to 64),years,11,60 To 64 Years,Age,Age - (G), -DHHGAGE_A,DHHGAGE_A_cat15_12,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,12,15,age (65 to 69),age (65 to 69),years,12,65 To 69 Years,Age,Age - (G), -DHHGAGE_A,DHHGAGE_A_cat15_13,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,13,15,age (70 to 74),age (70 to 74),years,13,70 To 74 Years,Age,Age - (G), -DHHGAGE_A,DHHGAGE_A_cat15_14,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,14,15,age (75 to 79),age (75 to 79),years,14,75 To 79 Years,Age,Age - (G), -DHHGAGE_A,DHHGAGE_A_cat15_15,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,15,15,age (80 plus),age (80 plus),years,15,80 Years or more,Age,Age - (G), -DHHGAGE_A,DHHGAGE_A_cat15_NA::a,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,NA::a,15,not applicable,not applicable,years,96,not applicable,Age,Age - (G), -DHHGAGE_A,DHHGAGE_A_cat15_NA::b,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,NA::b,15,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),Age,Age - (G),"Not applicable, don't know, refusal, not stated (96-99) were options only in CCHS 2003, but had zero responses" -DHHGAGE_A,DHHGAGE_A_cat15_NA::b,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,NA::b,15,missing,missing,years,else,else,Age,Age - (G), -DHHGAGE_B,DHHGAGE_B_cat16_1,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,1,16,age (12 to 14),age (12 to 14),years,1,12 To 14 Years,Age,Age - (G), -DHHGAGE_B,DHHGAGE_B_cat16_2,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,2,16,age (15 to 17),age (15 to 17),years,2,15 To 17 Years,Age,Age - (G), -DHHGAGE_B,DHHGAGE_B_cat16_3,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,3,16,age (18 to 19),age (18 to 19),years,3,18 To 19 Years,Age,Age - (G), -DHHGAGE_B,DHHGAGE_B_cat16_4,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,4,16,age (20 to 24),age (20 to 24),years,4,20 To 24 Years,Age,Age - (G), -DHHGAGE_B,DHHGAGE_B_cat16_5,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,5,16,age (25 to 29),age (25 to 29),years,5,25 To 29 Years,Age,Age - (G), -DHHGAGE_B,DHHGAGE_B_cat16_6,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,6,16,age (30 to 34),age (30 to 34),years,6,30 To 34 Years,Age,Age - (G), -DHHGAGE_B,DHHGAGE_B_cat16_7,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,7,16,age (35 to 39),age (35 to 39),years,7,35 To 39 Years,Age,Age - (G), -DHHGAGE_B,DHHGAGE_B_cat16_8,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,8,16,age (40 to 44),age (40 to 44),years,8,40 To 44 Years,Age,Age - (G), -DHHGAGE_B,DHHGAGE_B_cat16_9,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,9,16,age (45 to 49),age (45 to 49),years,9,45 To 49 Years,Age,Age - (G), -DHHGAGE_B,DHHGAGE_B_cat16_10,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,10,16,age (50 to 54),age (50 to 54),years,10,50 To 54 Years,Age,Age - (G), -DHHGAGE_B,DHHGAGE_B_cat16_11,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,11,16,age (55 to 59),age (55 to 59),years,11,55 To 59 Years,Age,Age - (G), -DHHGAGE_B,DHHGAGE_B_cat16_12,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,12,16,age (60 to 64),age (60 to 64),years,12,60 To 64 Years,Age,Age - (G), -DHHGAGE_B,DHHGAGE_B_cat16_13,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,13,16,age (65 to 69),age (65 to 69),years,13,65 To 69 Years,Age,Age - (G), -DHHGAGE_B,DHHGAGE_B_cat16_14,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,14,16,age (70 to 74),age (70 to 74),years,14,70 To 74 Years,Age,Age - (G), -DHHGAGE_B,DHHGAGE_B_cat16_15,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,15,16,age (75 to 79),age (75 to 79),years,15,75 To 79 Years,Age,Age - (G), -DHHGAGE_B,DHHGAGE_B_cat16_16,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,16,16,age (80 plus),age (80 plus),years,16,80 Years or more,Age,Age - (G), -DHHGAGE_B,DHHGAGE_B_cat16_NA::a,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,NA::a,16,not applicable,not applicable,years,96,not applicable,Age,Age - (G), -DHHGAGE_B,DHHGAGE_B_cat16_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,NA::b,16,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),Age,Age - (G), -DHHGAGE_B,DHHGAGE_B_cat16_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,NA::b,16,missing,missing,years,else,else,Age,Age - (G), -DHHGAGE_C,DHHGAGE_C_catN/A_Func::age_cat_fun,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[DHHGAGE_cont],N/A,Func::age_cat_fun,N/A,N/A,N/A,years,N/A,N/A,Age,Categorical age,This variable is derived from DHHGAGE_cont -DHHGAGE_C,DHHGAGE_C_cat16_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[DHHGAGE_cont],N/A,1,16,age (12 to 14),age (12 to 14),years,N/A,12 To 14 Years,Age,Categorical age, -DHHGAGE_C,DHHGAGE_C_cat16_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[DHHGAGE_cont],N/A,2,16,age (15 to 17),age (15 to 17),years,N/A,15 To 17 Years,Age,Categorical age, -DHHGAGE_C,DHHGAGE_C_cat16_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[DHHGAGE_cont],N/A,3,16,age (18 to 19),age (18 to 19),years,N/A,18 To 19 Years,Age,Categorical age, -DHHGAGE_C,DHHGAGE_C_cat16_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[DHHGAGE_cont],N/A,4,16,age (20 to 24),age (20 to 24),years,N/A,20 To 24 Years,Age,Categorical age, -DHHGAGE_C,DHHGAGE_C_cat16_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[DHHGAGE_cont],N/A,5,16,age (25 to 29),age (25 to 29),years,N/A,25 To 29 Years,Age,Categorical age, -DHHGAGE_C,DHHGAGE_C_cat16_6,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[DHHGAGE_cont],N/A,6,16,age (30 to 34),age (30 to 34),years,N/A,30 To 34 Years,Age,Categorical age, -DHHGAGE_C,DHHGAGE_C_cat16_7,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[DHHGAGE_cont],N/A,7,16,age (35 to 39),age (35 to 39),years,N/A,35 To 39 Years,Age,Categorical age, -DHHGAGE_C,DHHGAGE_C_cat16_8,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[DHHGAGE_cont],N/A,8,16,age (40 to 44),age (40 to 44),years,N/A,40 To 44 Years,Age,Categorical age, -DHHGAGE_C,DHHGAGE_C_cat16_9,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[DHHGAGE_cont],N/A,9,16,age (45 to 49),age (45 to 49),years,N/A,45 To 49 Years,Age,Categorical age, -DHHGAGE_C,DHHGAGE_C_cat16_10,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[DHHGAGE_cont],N/A,10,16,age (50 to 54),age (50 to 54),years,N/A,50 To 54 Years,Age,Categorical age, -DHHGAGE_C,DHHGAGE_C_cat16_11,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[DHHGAGE_cont],N/A,11,16,age (55 to 59),age (55 to 59),years,N/A,55 To 59 Years,Age,Categorical age, -DHHGAGE_C,DHHGAGE_C_cat16_12,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[DHHGAGE_cont],N/A,12,16,age (60 to 64),age (60 to 64),years,N/A,60 To 64 Years,Age,Categorical age, -DHHGAGE_C,DHHGAGE_C_cat16_13,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[DHHGAGE_cont],N/A,13,16,age (65 to 69),age (65 to 69),years,N/A,65 To 69 Years,Age,Categorical age, -DHHGAGE_C,DHHGAGE_C_cat16_14,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[DHHGAGE_cont],N/A,14,16,age (70 to 74),age (70 to 74),years,N/A,70 To 74 Years,Age,Categorical age, -DHHGAGE_C,DHHGAGE_C_cat16_15,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[DHHGAGE_cont],N/A,15,16,age (75 to 79),age (75 to 79),years,N/A,75 To 79 Years,Age,Categorical age, -DHHGAGE_C,DHHGAGE_C_cat16_16,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[DHHGAGE_cont],N/A,16,16,age (80 plus),age (80 plus),years,N/A,80 Years or more,Age,Categorical age, -DHHGAGE_C,DHHGAGE_C_cat16_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[DHHGAGE_cont],N/A,NA::a,16,not applicable,not applicable,years,N/A,not applicable,Age,Categorical age, -DHHGAGE_C,DHHGAGE_C_cat16_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[DHHGAGE_cont],N/A,NA::b,16,missing,missing,years,N/A,missing,Age,Categorical age, -DHHGAGE_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,13,N/A,Age,converted categorical age (12 to 14),years,1,12 to 14 years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,17,N/A,Age,converted categorical age (15 to 19),years,2,15 to 19 years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,22,N/A,Age,converted categorical age (20 to 24),years,3,20 To 24 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,27,N/A,Age,converted categorical age (25 to 29),years,4,25 To 29 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,32,N/A,Age,converted categorical age (30 to 34),years,5,30 To 34 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,37,N/A,Age,converted categorical age (35 to 39),years,6,35 To 39 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,42,N/A,Age,converted categorical age (40 to 44),years,7,40 To 44 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,47,N/A,Age,converted categorical age (45 to 49),years,8,45 To 49 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,52,N/A,Age,converted categorical age (50 to 54),years,9,50 To 54 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,57,N/A,Age,converted categorical age (55 to 59),years,10,55 To 59 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,62,N/A,Age,converted categorical age (60 to 64),years,11,60 To 64 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,67,N/A,Age,converted categorical age (65 to 69),years,12,65 To 69 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,72,N/A,Age,converted categorical age (70 to 74),years,13,70 To 74 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,77,N/A,Age,converted categorical age (75 to 79),years,14,75 To 79 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,85,N/A,Age,converted categorical age (80 plus),years,15,80 Years or more,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,NA::a,N/A,not applicable,not applicable,years,96,not applicable,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,NA::b,N/A,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),Age,Age - (G),"Not applicable, don't know, refusal, not stated (96-99) were options in CCHS 2003, but had zero responses" -DHHGAGE_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,NA::b,N/A,missing,missing,years,else,else,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,13,N/A,Age,converted categorical age (12 to 14),years,1,12 To 14 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,16,N/A,Age,converted categorical age (15 to 17),years,2,15 To 17 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,18.5,N/A,Age,converted categorical age (18 to 19),years,3,18 To 19 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,22,N/A,Age,converted categorical age (20 to 24),years,4,20 To 24 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,27,N/A,Age,converted categorical age (25 to 29),years,5,25 To 29 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,32,N/A,Age,converted categorical age (30 to 34),years,6,30 To 34 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,37,N/A,Age,converted categorical age (35 to 39),years,7,35 To 39 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,42,N/A,Age,converted categorical age (40 to 44),years,8,40 To 44 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,47,N/A,Age,converted categorical age (45 to 49),years,9,45 To 49 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,52,N/A,Age,converted categorical age (50 to 54),years,10,50 To 54 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,57,N/A,Age,converted categorical age (55 to 59),years,11,55 To 59 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,62,N/A,Age,converted categorical age (60 to 64),years,12,60 To 64 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,67,N/A,Age,converted categorical age (65 to 69),years,13,65 To 69 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,72,N/A,Age,converted categorical age (70 to 74),years,14,70 To 74 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,77,N/A,Age,converted categorical age (75 to 79),years,15,75 To 79 Years,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,85,N/A,Age,converted categorical age (80 plus),years,16,80 Years or more,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,NA::a,N/A,not applicable,not applicable,years,96,not applicable,Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,NA::b,N/A,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),Age,Age - (G), -DHHGAGE_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,NA::b,N/A,missing,missing,years,else,else,Age,Age - (G), -DHHGAGE_D,DHHGAGE_D_cat8_1,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,1,8,age (12 to 19),age (12 to 19),years,"[1,3]",12 To 14 Years (1); 15 To 17 Years (2); 18 To 19 Years (3),Age,Age - (G), -DHHGAGE_D,DHHGAGE_D_cat8_2,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,2,8,age (20 to 29),age (20 to 29),years,"[4,5]",20 to 24 Years (4); 25 To 29 Years (5),Age,Age - (G), -DHHGAGE_D,DHHGAGE_D_cat8_3,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,3,8,age (30 to 39),age (30 to 39),years,"[6,7]",30 To 34 Years (6); 35 To 39 Years (7),Age,Age - (G), -DHHGAGE_D,DHHGAGE_D_cat8_4,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,4,8,age (40 to 49),age (40 to 49),years,"[8,9]",40 To 44 Years (8); 45 To 49 Years (9),Age,Age - (G), -DHHGAGE_D,DHHGAGE_D_cat8_5,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,5,8,age (50 to 59),age (50 to 59),years,"[10,11]",50 To 54 Years (10); 55 To 59 Years (11),Age,Age - (G), -DHHGAGE_D,DHHGAGE_D_cat8_6,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,6,8,age (60 to 69),age (60 to 69),years,"[12,13]",60 To 64 Years (12); 65 To 69 Years (13),Age,Age - (G), -DHHGAGE_D,DHHGAGE_D_cat8_7,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,7,8,age (70 to 79),age (70 to 79),years,"[14,15]",70 To 74 Years (14); 75 To 79 Years (15),Age,Age - (G), -DHHGAGE_D,DHHGAGE_D_cat8_8,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,8,8,age (80 plus),age (80 plus),years,16,80 Years or more,Age,Age - (G), -DHHGAGE_D,DHHGAGE_D_cat8_NA::a,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,NA::a,8,not applicable,not applicable,years,96,not applicable,Age,Age - (G), -DHHGAGE_D,DHHGAGE_D_cat8_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,NA::b,8,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),Age,Age - (G), -DHHGAGE_D,DHHGAGE_D_cat8_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::DHHEGAGE, [DHHGAGE]",cat,NA::b,8,else,else,years,else,else,Age,Age - (G), -DHHGAGE_D,DHHGAGE_D_cat8_1,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,1,8,age (12 to 19),age (12 to 19),years,"[1,2]",12 To 14 Years (1); 15 To 19 Years (2),Age,Age - (G), -DHHGAGE_D,DHHGAGE_D_cat8_2,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,2,8,age (20 to 29),age (20 to 29),years,"[3,4]",20 to 24 Years (3); 25 To 29 Years (4),Age,Age - (G), -DHHGAGE_D,DHHGAGE_D_cat8_3,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,3,8,age (30 to 39),age (30 to 39),years,"[5,6]",30 To 34 Years (5); 35 To 39 Years (6),Age,Age - (G), -DHHGAGE_D,DHHGAGE_D_cat8_4,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,4,8,age (40 to 49),age (40 to 49),years,"[7,8]",40 To 44 Years (7); 45 To 49 Years (8),Age,Age - (G), -DHHGAGE_D,DHHGAGE_D_cat8_5,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,5,8,age (50 to 59),age (50 to 59),years,"[9,10]",50 To 54 Years (9); 55 To 59 Years (10),Age,Age - (G), -DHHGAGE_D,DHHGAGE_D_cat8_6,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,6,8,age (60 to 69),age (60 to 69),years,"[11,12]",60 To 64 Years (11); 65 To 69 Years (12),Age,Age - (G), -DHHGAGE_D,DHHGAGE_D_cat8_7,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,7,8,age (70 to 79),age (70 to 79),years,"[13,14]",70 To 74 Years (13); 75 To 79 Years (14),Age,Age - (G), -DHHGAGE_D,DHHGAGE_D_cat8_8,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,8,8,age (80 plus),age (80 plus),years,15,80 plus Years,Age,Age - (G), -DHHGAGE_D,DHHGAGE_D_cat8_NA::a,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,NA::a,8,not applicable,not applicable,years,96,not applicable,Age,Age - (G), -DHHGAGE_D,DHHGAGE_D_cat8_NA::b,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,NA::b,8,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),Age,Age - (G), -DHHGAGE_D,DHHGAGE_D_cat8_NA::b,cat,"cchs2001_p, cchs2003_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE",cat,NA::b,8,else,else,years,else,else,Age,Age - (G), -DHHGHSZ,DHHGHSZ_cat5_1,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::DHHCGHSZ, cchs2005_p::DHHEGHSZ, cchs2015_2016_p::DHHDGHSZ, cchs2017_2018_p::DHHDGHSZ, [DHHGHSZ]",cat,1,5,1 person,1 person,N/A,1,1 person,Household size,Household size - (G), -DHHGHSZ,DHHGHSZ_cat5_2,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::DHHCGHSZ, cchs2005_p::DHHEGHSZ, cchs2015_2016_p::DHHDGHSZ, cchs2017_2018_p::DHHDGHSZ, [DHHGHSZ]",cat,2,5,2 persons,2 persons,N/A,2,2 persons,Household size,Household size - (G), -DHHGHSZ,DHHGHSZ_cat5_3,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::DHHCGHSZ, cchs2005_p::DHHEGHSZ, cchs2015_2016_p::DHHDGHSZ, cchs2017_2018_p::DHHDGHSZ, [DHHGHSZ]",cat,3,5,3 persons,3 persons,N/A,3,3 persons,Household size,Household size - (G), -DHHGHSZ,DHHGHSZ_cat5_4,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::DHHCGHSZ, cchs2005_p::DHHEGHSZ, cchs2015_2016_p::DHHDGHSZ, cchs2017_2018_p::DHHDGHSZ, [DHHGHSZ]",cat,4,5,4 persons,4 persons,N/A,4,4 persons,Household size,Household size - (G), -DHHGHSZ,DHHGHSZ_cat5_5,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::DHHCGHSZ, cchs2005_p::DHHEGHSZ, cchs2015_2016_p::DHHDGHSZ, cchs2017_2018_p::DHHDGHSZ, [DHHGHSZ]",cat,5,5,5+ persons,5 or more persons,N/A,5,5 or more persons,Household size,Household size - (G), -DHHGHSZ,DHHGHSZ_cat5_NA::a,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::DHHCGHSZ, cchs2005_p::DHHEGHSZ, cchs2015_2016_p::DHHDGHSZ, cchs2017_2018_p::DHHDGHSZ, [DHHGHSZ]",cat,NA::a,5,not applicable,not applicable,N/A,6,not applicable,Household size,Household size - (G), -DHHGHSZ,DHHGHSZ_cat5_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::DHHCGHSZ, cchs2005_p::DHHEGHSZ, cchs2015_2016_p::DHHDGHSZ, cchs2017_2018_p::DHHDGHSZ, [DHHGHSZ]",cat,NA::b,5,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Household size,Household size - (G), -DHHGHSZ,DHHGHSZ_cat5_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::DHHCGHSZ, cchs2005_p::DHHEGHSZ, cchs2015_2016_p::DHHDGHSZ, cchs2017_2018_p::DHHDGHSZ, [DHHGHSZ]",cat,NA::b,5,missing,missing,N/A,else,else,Household size,Household size - (G), -DHHGMS,DHHGMS_cat4_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::DHHAGMS, cchs2003_p::DHHCGMS, cchs2005_p::DHHEGMS, [DHHGMS]",cat,1,4,Married,Married,N/A,1,Married,Marital Status,Marital status - (G), -DHHGMS,DHHGMS_cat4_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::DHHAGMS, cchs2003_p::DHHCGMS, cchs2005_p::DHHEGMS, [DHHGMS]",cat,2,4,Common-law,Common-law,N/A,2,Common-law,Marital Status,Marital status - (G), -DHHGMS,DHHGMS_cat4_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::DHHAGMS, cchs2003_p::DHHCGMS, cchs2005_p::DHHEGMS, [DHHGMS]",cat,3,4,Widow/Seperated/Divorced,Widow/Sep/Div,N/A,3,Widow/separated/divorced,Marital Status,Marital status - (G), -DHHGMS,DHHGMS_cat4_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::DHHAGMS, cchs2003_p::DHHCGMS, cchs2005_p::DHHEGMS, [DHHGMS]",cat,4,4,Single/Never married,Single,N/A,4,Single/never married,Marital Status,Marital status - (G), -DHHGMS,DHHGMS_cat4_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::DHHAGMS, cchs2003_p::DHHCGMS, cchs2005_p::DHHEGMS, [DHHGMS]",cat,NA::a,4,not applicable,not applicable,N/A,6,not applicable,Marital Status,Marital status - (G), -DHHGMS,DHHGMS_cat4_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::DHHAGMS, cchs2003_p::DHHCGMS, cchs2005_p::DHHEGMS, [DHHGMS]",cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Marital Status,Marital status - (G), -DHHGMS,DHHGMS_cat4_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::DHHAGMS, cchs2003_p::DHHCGMS, cchs2005_p::DHHEGMS, [DHHGMS]",cat,NA::b,4,missing,missing,N/A,else,else,Marital Status,Marital status - (G), -diet_score,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[FVCDFRU, FVCDSAL, FVCDPOT, FVCDCAR, FVCDVEG, FVCDJUI, DHH_SEX]",N/A,Func::diet_score_fun,N/A,N/A,N/A,N/A,N/A,Diet score ,Diet score ,"Diet score (0 to 10) based on daily consumption of fruit, vegetables and fruit juice", -diet_score,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[FVCDFRU, FVCDSAL, FVCDPOT, FVCDCAR, FVCDVEG, FVCDJUI, DHH_SEX]",N/A,NA::b,N/A,missing,missing,N/A,N/A,Diet score ,Diet score ,"Diet score (0 to 10) based on daily consumption of fruit, vegetables and fruit juice", -diet_score_cat3,diet_score_cat3N/A_Func::diet_score_fun_cat,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[diet_score],N/A,Func::diet_score_fun_cat,N/A,N/A,N/A,N/A,N/A,N/A,Categorical diet score,Categorical diet score, -diet_score_cat3,diet_score_cat3_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[diet_score],N/A,1,3,Poor diet,Poor diet,N/A,1,Poor diet,Categorical diet score,Categorical diet score, -diet_score_cat3,diet_score_cat3_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[diet_score],N/A,2,3,Fair diet,Fair diet,N/A,2,Fair diet,Categorical diet score,Categorical diet score, -diet_score_cat3,diet_score_cat3_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[diet_score],N/A,3,3,Adequate diet,Adequate diet,N/A,3,Adequate diet,Categorical diet score,Categorical diet score, -diet_score_cat3,diet_score_cat3_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[diet_score],N/A,NA::a,3,not applicable,not applicable,N/A,NA::a,not applicable,Categorical diet score,Categorical diet score, -diet_score_cat3,diet_score_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[diet_score],N/A,NA::b,3,missing,missing,N/A,NA::b,missing,Categorical diet score,Categorical diet score, -DIS_10G,DIS_10G_cat5_1,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2017_2018_p","cchs2005_p::DISE_10G, cchs2017_2018_p::DIS_035, [DIS_10G]",cat,1,5,All of the time,All of the time,N/A,1,All of the time,Frequency - distress: felt sad / depressed - past month,"(During the past month, about how often did you feel) sad or depressed?", -DIS_10G,DIS_10G_cat5_2,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2017_2018_p","cchs2005_p::DISE_10G, cchs2017_2018_p::DIS_035, [DIS_10G]",cat,2,5,Most of the time,Most of the time,N/A,2,Most of the time,Frequency - distress: felt sad / depressed - past month,"(During the past month, about how often did you feel) sad or depressed?", -DIS_10G,DIS_10G_cat5_3,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2017_2018_p","cchs2005_p::DISE_10G, cchs2017_2018_p::DIS_035, [DIS_10G]",cat,3,5,Some of the time,Some of the time,N/A,3,Some of the time,Frequency - distress: felt sad / depressed - past month,"(During the past month, about how often did you feel) sad or depressed?", -DIS_10G,DIS_10G_cat5_4,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2017_2018_p","cchs2005_p::DISE_10G, cchs2017_2018_p::DIS_035, [DIS_10G]",cat,4,5,A little of the time,A little of the time,N/A,4,A little of the time,Frequency - distress: felt sad / depressed - past month,"(During the past month, about how often did you feel) sad or depressed?", -DIS_10G,DIS_10G_cat5_5,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2017_2018_p","cchs2005_p::DISE_10G, cchs2017_2018_p::DIS_035, [DIS_10G]",cat,5,5,None of the time,None of the time,N/A,5,None of the time,Frequency - distress: felt sad / depressed - past month,"(During the past month, about how often did you feel) sad or depressed?", -DIS_10G,DIS_10G_cat5_NA::a,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2017_2018_p","cchs2005_p::DISE_10G, cchs2017_2018_p::DIS_035, [DIS_10G]",cat,NA::a,5,not applicable,not applicable,N/A,6,not applicable,Frequency - distress: felt sad / depressed - past month,"(During the past month, about how often did you feel) sad or depressed?", -DIS_10G,DIS_10G_cat5_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2017_2018_p","cchs2005_p::DISE_10G, cchs2017_2018_p::DIS_035, [DIS_10G]",cat,NA::b,5,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Frequency - distress: felt sad / depressed - past month,"(During the past month, about how often did you feel) sad or depressed?", -DIS_10G,DIS_10G_cat5_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2017_2018_p","cchs2005_p::DISE_10G, cchs2017_2018_p::DIS_035, [DIS_10G]",cat,NA::b,5,missing,missing,N/A,else,else,Frequency - distress: felt sad / depressed - past month,"(During the past month, about how often did you feel) sad or depressed?", -DIS_10H,DIS_10H_cat5_1,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2017_2018_p","cchs2005_p::DISE_10H, cchs2017_2018_p::DIS_040, [DIS_10H]",cat,1,5,All of the time,All of the time,N/A,1,All of the time,Frequency - distress: depressed/nothing cheers - past month,"(During the past month, about how often did you feel) so depressed that nothing could cheer you up?", -DIS_10H,DIS_10H_cat5_2,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2017_2018_p","cchs2005_p::DISE_10H, cchs2017_2018_p::DIS_040, [DIS_10H]",cat,2,5,Most of the time,Most of the time,N/A,2,Most of the time,Frequency - distress: depressed/nothing cheers - past month,"(During the past month, about how often did you feel) so depressed that nothing could cheer you up?", -DIS_10H,DIS_10H_cat5_3,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2017_2018_p","cchs2005_p::DISE_10H, cchs2017_2018_p::DIS_040, [DIS_10H]",cat,3,5,Some of the time,Some of the time,N/A,3,Some of the time,Frequency - distress: depressed/nothing cheers - past month,"(During the past month, about how often did you feel) so depressed that nothing could cheer you up?", -DIS_10H,DIS_10H_cat5_4,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2017_2018_p","cchs2005_p::DISE_10H, cchs2017_2018_p::DIS_040, [DIS_10H]",cat,4,5,A little of the time,A little of the time,N/A,4,A little of the time,Frequency - distress: depressed/nothing cheers - past month,"(During the past month, about how often did you feel) so depressed that nothing could cheer you up?", -DIS_10H,DIS_10H_cat5_5,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2017_2018_p","cchs2005_p::DISE_10H, cchs2017_2018_p::DIS_040, [DIS_10H]",cat,5,5,None of the time,None of the time,N/A,5,None of the time,Frequency - distress: depressed/nothing cheers - past month,"(During the past month, about how often did you feel) so depressed that nothing could cheer you up?", -DIS_10H,DIS_10H_cat5_NA::a,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2017_2018_p","cchs2005_p::DISE_10H, cchs2017_2018_p::DIS_040, [DIS_10H]",cat,NA::a,5,not applicable,not applicable,N/A,6,not applicable,Frequency - distress: depressed/nothing cheers - past month,"(During the past month, about how often did you feel) so depressed that nothing could cheer you up?", -DIS_10H,DIS_10H_cat5_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2017_2018_p","cchs2005_p::DISE_10H, cchs2017_2018_p::DIS_040, [DIS_10H]",cat,NA::b,5,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Frequency - distress: depressed/nothing cheers - past month,"(During the past month, about how often did you feel) so depressed that nothing could cheer you up?", -DIS_10H,DIS_10H_cat5_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2017_2018_p","cchs2005_p::DISE_10H, cchs2017_2018_p::DIS_040, [DIS_10H]",cat,NA::b,5,missing,missing,N/A,else,else,Frequency - distress: depressed/nothing cheers - past month,"(During the past month, about how often did you feel) so depressed that nothing could cheer you up?", -DPS_02,DPS_02_cat2_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_02],cat,1,2,Yes,Yes,N/A,1,Yes,Felt sad/blue/depressed - 2 weeks or more - 12 mo,"During the past 12 months, was there ever a time when you felt sad, blue, or depressed for 2 weeks or more in a row?", -DPS_02,DPS_02_cat2_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_02],cat,2,2,No,No,N/A,2,No,Felt sad/blue/depressed - 2 weeks or more - 12 mo,"During the past 12 months, was there ever a time when you felt sad, blue, or depressed for 2 weeks or more in a row?", -DPS_02,DPS_02_cat2_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_02],cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Felt sad/blue/depressed - 2 weeks or more - 12 mo,"During the past 12 months, was there ever a time when you felt sad, blue, or depressed for 2 weeks or more in a row?", -DPS_02,DPS_02_cat2_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_02],cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Felt sad/blue/depressed - 2 weeks or more - 12 mo,"During the past 12 months, was there ever a time when you felt sad, blue, or depressed for 2 weeks or more in a row?", -DPS_02,DPS_02_cat2_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_02],cat,NA::b,2,missing,missing,N/A,else,else,Felt sad/blue/depressed - 2 weeks or more - 12 mo,"During the past 12 months, was there ever a time when you felt sad, blue, or depressed for 2 weeks or more in a row?", -DPS_03,DPS_03_cat4_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_03],cat,1,4,All day long,All day long,N/A,1,All day long,Sad/depressed - length feelings lasted - 2 wk,"Think of the 2-week period during the past 12 months when these feelings were the worst. During that time, how long did these feelings usually last: (all day long, most of the day, about half of the day, or less than half of a day)?", -DPS_03,DPS_03_cat4_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_03],cat,2,4,Most of the day,Most of the day,N/A,2,Most of the day,Sad/depressed - length feelings lasted - 2 wk,"Think of the 2-week period during the past 12 months when these feelings were the worst. During that time, how long did these feelings usually last: (all day long, most of the day, about half of the day, or less than half of a day)?", -DPS_03,DPS_03_cat4_3,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_03],cat,3,4,About half of the day,About half of the day,N/A,3,About half of the day,Sad/depressed - length feelings lasted - 2 wk,"Think of the 2-week period during the past 12 months when these feelings were the worst. During that time, how long did these feelings usually last: (all day long, most of the day, about half of the day, or less than half of a day)?", -DPS_03,DPS_03_cat4_4,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_03],cat,4,4,Less than half of a day,Less than half of a day,N/A,4,Less than half of a day,Sad/depressed - length feelings lasted - 2 wk,"Think of the 2-week period during the past 12 months when these feelings were the worst. During that time, how long did these feelings usually last: (all day long, most of the day, about half of the day, or less than half of a day)?", -DPS_03,DPS_03_cat4_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_03],cat,NA::a,4,not applicable,not applicable,N/A,6,not applicable,Sad/depressed - length feelings lasted - 2 wk,"Think of the 2-week period during the past 12 months when these feelings were the worst. During that time, how long did these feelings usually last: (all day long, most of the day, about half of the day, or less than half of a day)?", -DPS_03,DPS_03_cat4_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_03],cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Sad/depressed - length feelings lasted - 2 wk,"Think of the 2-week period during the past 12 months when these feelings were the worst. During that time, how long did these feelings usually last: (all day long, most of the day, about half of the day, or less than half of a day)?", -DPS_03,DPS_03_cat4_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_03],cat,NA::b,4,missing,missing,N/A,else,else,Sad/depressed - length feelings lasted - 2 wk,"Think of the 2-week period during the past 12 months when these feelings were the worst. During that time, how long did these feelings usually last: (all day long, most of the day, about half of the day, or less than half of a day)?", -DPS_04,DPS_04_cat3_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_04],cat,1,3,Every day,Every day,N/A,1,Every day,Sad/depressed - frequency - 2 wk,"How often did you feel this way during those 2 weeks: (every day, almost every day, or less often)?", -DPS_04,DPS_04_cat3_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_04],cat,2,3,Almost every day,Almost every day,N/A,2,Almost every day,Sad/depressed - frequency - 2 wk,"How often did you feel this way during those 2 weeks: (every day, almost every day, or less often)?", -DPS_04,DPS_04_cat3_3,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_04],cat,3,3,Less often,Less often,N/A,3,Less often,Sad/depressed - frequency - 2 wk,"How often did you feel this way during those 2 weeks: (every day, almost every day, or less often)?", -DPS_04,DPS_04_cat3_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_04],cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Sad/depressed - frequency - 2 wk,"How often did you feel this way during those 2 weeks: (every day, almost every day, or less often)?", -DPS_04,DPS_04_cat3_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_04],cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Sad/depressed - frequency - 2 wk,"How often did you feel this way during those 2 weeks: (every day, almost every day, or less often)?", -DPS_04,DPS_04_cat3_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_04],cat,NA::b,3,missing,missing,N/A,else,else,Sad/depressed - frequency - 2 wk,"How often did you feel this way during those 2 weeks: (every day, almost every day, or less often)?", -DPS_05,DPS_05_cat2_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_05],cat,1,2,Yes,Yes,N/A,1,Yes,Sad/depressed - lose interest in things - 2 wk,During those 2 weeks did you lose interest in most things?, -DPS_05,DPS_05_cat2_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_05],cat,2,2,No,No,N/A,2,No,Sad/depressed - lose interest in things - 2 wk,During those 2 weeks did you lose interest in most things?, -DPS_05,DPS_05_cat2_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_05],cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Sad/depressed - lose interest in things - 2 wk,During those 2 weeks did you lose interest in most things?, -DPS_05,DPS_05_cat2_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_05],cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Sad/depressed - lose interest in things - 2 wk,During those 2 weeks did you lose interest in most things?, -DPS_05,DPS_05_cat2_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_05],cat,NA::b,2,missing,missing,N/A,else,else,Sad/depressed - lose interest in things - 2 wk,During those 2 weeks did you lose interest in most things?, -DPS_06,DPS_06_cat2_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_06],cat,1,2,Yes,Yes,N/A,1,Yes,Sad/depressed - felt tired out / low on energy - 2 wk,Did you feel tired out or low on energy all of the time?, -DPS_06,DPS_06_cat2_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_06],cat,2,2,No,No,N/A,2,No,Sad/depressed - felt tired out / low on energy - 2 wk,Did you feel tired out or low on energy all of the time?, -DPS_06,DPS_06_cat2_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_06],cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Sad/depressed - felt tired out / low on energy - 2 wk,Did you feel tired out or low on energy all of the time?, -DPS_06,DPS_06_cat2_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_06],cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Sad/depressed - felt tired out / low on energy - 2 wk,Did you feel tired out or low on energy all of the time?, -DPS_06,DPS_06_cat2_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_06],cat,NA::b,2,missing,missing,N/A,else,else,Sad/depressed - felt tired out / low on energy - 2 wk,Did you feel tired out or low on energy all of the time?, -DPS_07,DPS_07_cat4_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_07],cat,1,4,Gained weight,Gained weight,N/A,1,Gained weight,Sad/depressed - weight change - 2 wk,"Did you gain weight, lose weight or stay about the same?", -DPS_07,DPS_07_cat4_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_07],cat,2,4,Lost weight,Lost weight,N/A,2,Lost weight,Sad/depressed - weight change - 2 wk,"Did you gain weight, lose weight or stay about the same?", -DPS_07,DPS_07_cat4_3,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_07],cat,3,4,Stayed about the same,Stayed about the same,N/A,3,Stayed about the same,Sad/depressed - weight change - 2 wk,"Did you gain weight, lose weight or stay about the same?", -DPS_07,DPS_07_cat4_4,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_07],cat,4,4,Was on a diet,Was on a diet,N/A,4,Was on a diet,Sad/depressed - weight change - 2 wk,"Did you gain weight, lose weight or stay about the same?", -DPS_07,DPS_07_cat4_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_07],cat,NA::a,4,not applicable,not applicable,N/A,6,not applicable,Sad/depressed - weight change - 2 wk,"Did you gain weight, lose weight or stay about the same?", -DPS_07,DPS_07_cat4_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_07],cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Sad/depressed - weight change - 2 wk,"Did you gain weight, lose weight or stay about the same?", -DPS_07,DPS_07_cat4_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_07],cat,NA::b,4,missing,missing,N/A,else,else,Sad/depressed - weight change - 2 wk,"Did you gain weight, lose weight or stay about the same?", -DPS_08A,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_08A],cont,copy,N/A,Weight,Weight,N/A,"[1,90]",Weight,Sad/depressed - weight change (amount) - 2 wk,About how much did you gain/lose?, -DPS_08A,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_08A],cont,NA::a,N/A,not applicable,not applicable,N/A,996,not applicable,Sad/depressed - weight change (amount) - 2 wk,About how much did you gain/lose?, -DPS_08A,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_08A],cont,NA::b,N/A,missing,missing,N/A,"[997,999]",don't know (999.7); refusal (999.8); not stated (999.9),Sad/depressed - weight change (amount) - 2 wk,About how much did you gain/lose?, -DPS_08A,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_08A],cont,NA::b,N/A,missing,missing,N/A,else,else,Sad/depressed - weight change (amount) - 2 wk,About how much did you gain/lose?, -DPS_08B,DPS_08B_cat2_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_08B],cat,1,2,Pounds,Pounds,N/A,1,Pounds,Sad/depressed - weight change (lb/kg) - 2 wk,Interviewer: Was that in pounds or in kilograms?, -DPS_08B,DPS_08B_cat2_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_08B],cat,2,2,Kilograms,Kilograms,N/A,2,Kilograms,Sad/depressed - weight change (lb/kg) - 2 wk,Interviewer: Was that in pounds or in kilograms?, -DPS_08B,DPS_08B_cat2_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_08B],cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Sad/depressed - weight change (lb/kg) - 2 wk,Interviewer: Was that in pounds or in kilograms?, -DPS_08B,DPS_08B_cat2_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_08B],cat,NA::b,2,missing,missing,N/A,9,not stated,Sad/depressed - weight change (lb/kg) - 2 wk,Interviewer: Was that in pounds or in kilograms?, -DPS_08B,DPS_08B_cat2_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_08B],cat,NA::b,2,missing,missing,N/A,else,else,Sad/depressed - weight change (lb/kg) - 2 wk,Interviewer: Was that in pounds or in kilograms?, -DPS_09,DPS_09_cat2_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_09],cat,1,2,Yes,Yes,N/A,1,Yes,Sad/depressed - trouble falling asleep - 2 wk,Did you have more trouble falling asleep than you usually do?, -DPS_09,DPS_09_cat2_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_09],cat,2,2,No,No,N/A,2,No,Sad/depressed - trouble falling asleep - 2 wk,Did you have more trouble falling asleep than you usually do?, -DPS_09,DPS_09_cat2_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_09],cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Sad/depressed - trouble falling asleep - 2 wk,Did you have more trouble falling asleep than you usually do?, -DPS_09,DPS_09_cat2_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_09],cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Sad/depressed - trouble falling asleep - 2 wk,Did you have more trouble falling asleep than you usually do?, -DPS_09,DPS_09_cat2_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_09],cat,NA::b,2,missing,missing,N/A,else,else,Sad/depressed - trouble falling asleep - 2 wk,Did you have more trouble falling asleep than you usually do?, -DPS_10,DPS_10_cat3_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_10],cat,1,3,Every night,Every night,N/A,1,Every night,Sad/depressed trouble falling asleep - frequency - 2 wk,"How often did that happen: (every night, nearly every night, or less often)?", -DPS_10,DPS_10_cat3_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_10],cat,2,3,Nearly every night,Nearly every night,N/A,2,Nearly every night,Sad/depressed trouble falling asleep - frequency - 2 wk,"How often did that happen: (every night, nearly every night, or less often)?", -DPS_10,DPS_10_cat3_3,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_10],cat,3,3,Less often,Less often,N/A,3,Less often,Sad/depressed trouble falling asleep - frequency - 2 wk,"How often did that happen: (every night, nearly every night, or less often)?", -DPS_10,DPS_10_cat3_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_10],cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Sad/depressed trouble falling asleep - frequency - 2 wk,"How often did that happen: (every night, nearly every night, or less often)?", -DPS_10,DPS_10_cat3_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_10],cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Sad/depressed trouble falling asleep - frequency - 2 wk,"How often did that happen: (every night, nearly every night, or less often)?", -DPS_10,DPS_10_cat3_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_10],cat,NA::b,3,missing,missing,N/A,else,else,Sad/depressed trouble falling asleep - frequency - 2 wk,"How often did that happen: (every night, nearly every night, or less often)?", -DPS_11,DPS_11_cat2_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_11],cat,1,2,Yes,Yes,N/A,1,Yes,Sad/depressed - trouble concentrating - 2 wk,Did you have a lot more trouble concentrating than usual?, -DPS_11,DPS_11_cat2_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_11],cat,2,2,No,No,N/A,2,No,Sad/depressed - trouble concentrating - 2 wk,Did you have a lot more trouble concentrating than usual?, -DPS_11,DPS_11_cat2_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_11],cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Sad/depressed - trouble concentrating - 2 wk,Did you have a lot more trouble concentrating than usual?, -DPS_11,DPS_11_cat2_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_11],cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Sad/depressed - trouble concentrating - 2 wk,Did you have a lot more trouble concentrating than usual?, -DPS_11,DPS_11_cat2_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_11],cat,NA::b,2,missing,missing,N/A,else,else,Sad/depressed - trouble concentrating - 2 wk,Did you have a lot more trouble concentrating than usual?, -DPS_12,DPS_12_cat2_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_12],cat,1,2,Yes,Yes,N/A,1,Yes,Sad/depressed - felt down on self - 2 wk,"At these times, people sometimes feel down on themselves, no good or worthless. Did you feel this way?", -DPS_12,DPS_12_cat2_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_12],cat,2,2,No,No,N/A,2,No,Sad/depressed - felt down on self - 2 wk,"At these times, people sometimes feel down on themselves, no good or worthless. Did you feel this way?", -DPS_12,DPS_12_cat2_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_12],cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Sad/depressed - felt down on self - 2 wk,"At these times, people sometimes feel down on themselves, no good or worthless. Did you feel this way?", -DPS_12,DPS_12_cat2_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_12],cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Sad/depressed - felt down on self - 2 wk,"At these times, people sometimes feel down on themselves, no good or worthless. Did you feel this way?", -DPS_12,DPS_12_cat2_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_12],cat,NA::b,2,missing,missing,N/A,else,else,Sad/depressed - felt down on self - 2 wk,"At these times, people sometimes feel down on themselves, no good or worthless. Did you feel this way?", -DPS_13,DPS_13_cat2_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_13],cat,1,2,Yes,Yes,N/A,1,Yes,Sad/depressed - thought a lot about death - 2 wk,"Did you think a lot about death - either your own, someone elses, or death in general?", -DPS_13,DPS_13_cat2_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_13],cat,2,2,No,No,N/A,2,No,Sad/depressed - thought a lot about death - 2 wk,"Did you think a lot about death - either your own, someone elses, or death in general?", -DPS_13,DPS_13_cat2_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_13],cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Sad/depressed - thought a lot about death - 2 wk,"Did you think a lot about death - either your own, someone elses, or death in general?", -DPS_13,DPS_13_cat2_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_13],cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Sad/depressed - thought a lot about death - 2 wk,"Did you think a lot about death - either your own, someone elses, or death in general?", -DPS_13,DPS_13_cat2_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_13],cat,NA::b,2,missing,missing,N/A,else,else,Sad/depressed - thought a lot about death - 2 wk,"Did you think a lot about death - either your own, someone elses, or death in general?", -DPS_14,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_14],cont,copy,N/A,Number of weeks,Number of weeks,weeks,"[2,53]",Number of week feel this way,Sad/depressed - number of weeks - 12 mo,About how many weeks altogether did you feel this way during the past 12 months?, -DPS_14,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_14],cont,NA::a,N/A,not applicable,not applicable,weeks,96,not applicable,Sad/depressed - number of weeks - 12 mo,About how many weeks altogether did you feel this way during the past 12 months?, -DPS_14,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_14],cont,NA::b,N/A,missing,missing,weeks,"[97,99]",don't know (97); refusal (98); not stated (99),Sad/depressed - number of weeks - 12 mo,About how many weeks altogether did you feel this way during the past 12 months?, -DPS_14,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p",[DPS_14],cont,NA::b,N/A,missing,missing,weeks,else,else,Sad/depressed - number of weeks - 12 mo,About how many weeks altogether did you feel this way during the past 12 months?, -DPSDMT,DPSDMT_cat12_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADMT, cchs2003_p::DPSCDMT, cchs2005_p::DPSEDMT, [DPSDMT]",cat,1,12,January,January,N/A,1,January,Specific month when felt depressed,Specific month felt depressed - 2 weeks in a row - (D), -DPSDMT,DPSDMT_cat12_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADMT, cchs2003_p::DPSCDMT, cchs2005_p::DPSEDMT, [DPSDMT]",cat,2,12,February,February,N/A,2,February,Specific month when felt depressed,Specific month felt depressed - 2 weeks in a row - (D), -DPSDMT,DPSDMT_cat12_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADMT, cchs2003_p::DPSCDMT, cchs2005_p::DPSEDMT, [DPSDMT]",cat,3,12,March,March,N/A,3,March,Specific month when felt depressed,Specific month felt depressed - 2 weeks in a row - (D), -DPSDMT,DPSDMT_cat12_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADMT, cchs2003_p::DPSCDMT, cchs2005_p::DPSEDMT, [DPSDMT]",cat,4,12,April,April,N/A,4,April,Specific month when felt depressed,Specific month felt depressed - 2 weeks in a row - (D), -DPSDMT,DPSDMT_cat12_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADMT, cchs2003_p::DPSCDMT, cchs2005_p::DPSEDMT, [DPSDMT]",cat,5,12,May,May,N/A,5,May,Specific month when felt depressed,Specific month felt depressed - 2 weeks in a row - (D), -DPSDMT,DPSDMT_cat12_6,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADMT, cchs2003_p::DPSCDMT, cchs2005_p::DPSEDMT, [DPSDMT]",cat,6,12,June,June,N/A,6,June,Specific month when felt depressed,Specific month felt depressed - 2 weeks in a row - (D), -DPSDMT,DPSDMT_cat12_7,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADMT, cchs2003_p::DPSCDMT, cchs2005_p::DPSEDMT, [DPSDMT]",cat,7,12,July,July,N/A,7,July,Specific month when felt depressed,Specific month felt depressed - 2 weeks in a row - (D), -DPSDMT,DPSDMT_cat12_8,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADMT, cchs2003_p::DPSCDMT, cchs2005_p::DPSEDMT, [DPSDMT]",cat,8,12,August,August,N/A,8,August,Specific month when felt depressed,Specific month felt depressed - 2 weeks in a row - (D), -DPSDMT,DPSDMT_cat12_9,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADMT, cchs2003_p::DPSCDMT, cchs2005_p::DPSEDMT, [DPSDMT]",cat,9,12,September,September,N/A,9,September,Specific month when felt depressed,Specific month felt depressed - 2 weeks in a row - (D), -DPSDMT,DPSDMT_cat12_10,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADMT, cchs2003_p::DPSCDMT, cchs2005_p::DPSEDMT, [DPSDMT]",cat,10,12,October,October,N/A,10,October,Specific month when felt depressed,Specific month felt depressed - 2 weeks in a row - (D), -DPSDMT,DPSDMT_cat12_11,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADMT, cchs2003_p::DPSCDMT, cchs2005_p::DPSEDMT, [DPSDMT]",cat,11,12,November,November,N/A,11,November,Specific month when felt depressed,Specific month felt depressed - 2 weeks in a row - (D), -DPSDMT,DPSDMT_cat12_12,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADMT, cchs2003_p::DPSCDMT, cchs2005_p::DPSEDMT, [DPSDMT]",cat,12,12,December,December,N/A,12,December,Specific month when felt depressed,Specific month felt depressed - 2 weeks in a row - (D), -DPSDMT,DPSDMT_cat12_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADMT, cchs2003_p::DPSCDMT, cchs2005_p::DPSEDMT, [DPSDMT]",cat,NA::a,12,not applicable,not applicable,N/A,96,not applicable,Specific month when felt depressed,Specific month felt depressed - 2 weeks in a row - (D), -DPSDMT,DPSDMT_cat12_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADMT, cchs2003_p::DPSCDMT, cchs2005_p::DPSEDMT, [DPSDMT]",cat,NA::b,12,missing,missing,N/A,99,not stated,Specific month when felt depressed,Specific month felt depressed - 2 weeks in a row - (D), -DPSDMT,DPSDMT_cat12_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADMT, cchs2003_p::DPSCDMT, cchs2005_p::DPSEDMT, [DPSDMT]",cat,NA::b,12,missing,missing,N/A,else,else,Specific month when felt depressed,Specific month felt depressed - 2 weeks in a row - (D), -DPSDPP,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADPP, cchs2003_p::DPSCDPP, cchs2005_p::DPSEDPP, [DPSDPP]",cont,copy,N/A,Depression Scale - Predicted Probability,Depression Scale - Predicted Probability,N/A,"[0,0.90]",Predicted Probability,Depression Scale - Predicted Probability,Depression Scale - Predicted Probability,"Variable was documented as a categorical variable with categories 0, 0.05, 0.25, 0.50, 0.80, 0.90 across all cycles. See documentation for DPSDPP() for more details, or type ?DPSDPP in the console." -DPSDPP,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADPP, cchs2003_p::DPSCDPP, cchs2005_p::DPSEDPP, [DPSDPP]",cont,NA::a,N/A,not applicable,not applicable,N/A,9.96,not applicable,Depression Scale - Predicted Probability,Depression Scale - Predicted Probability, -DPSDPP,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADPP, cchs2003_p::DPSCDPP, cchs2005_p::DPSEDPP, [DPSDPP]",cont,NA::b,N/A,missing,missing,N/A,9.99,not stated,Depression Scale - Predicted Probability,Depression Scale - Predicted Probability, -DPSDPP,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADPP, cchs2003_p::DPSCDPP, cchs2005_p::DPSEDPP, [DPSDPP]",cont,NA::b,N/A,missing,missing,N/A,else,else,Depression Scale - Predicted Probability,Depression Scale - Predicted Probability, -DPSDSF,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADSF, cchs2003_p::DPSCDSF, cchs2005_p::DPSEDSF, [DPSDSF]",cont,copy,N/A,Depression Scale - Short Form Score,Depression Scale - Short Form Score,N/A,"[0,8]",Short Form Score,Depression Scale - Short Form Score,Depression Scale - Short Form Score, -DPSDSF,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADSF, cchs2003_p::DPSCDSF, cchs2005_p::DPSEDSF, [DPSDSF]",cont,NA::a,N/A,not applicable,not applicable,N/A,96,not applicable,Depression Scale - Short Form Score,Depression Scale - Short Form Score, -DPSDSF,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADSF, cchs2003_p::DPSCDSF, cchs2005_p::DPSEDSF, [DPSDSF]",cont,NA::b,N/A,missing,missing,N/A,99,not stated,Depression Scale - Short Form Score,Depression Scale - Short Form Score, -DPSDSF,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADSF, cchs2003_p::DPSCDSF, cchs2005_p::DPSEDSF, [DPSDSF]",cont,NA::b,N/A,missing,missing,N/A,else,else,Depression Scale - Short Form Score,Depression Scale - Short Form Score, -DPSDWK,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADWK, cchs2003_p::DPSCDWK, cchs2005_p::DPSEDWK, [DPSDWK]",cont,copy,N/A,Number of weeks,Number of weeks,weeks,"[2,53]",Number of weeks felt depressed,Number of weeks felt depressed - (D),Number of weeks felt depressed - (D), -DPSDWK,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADWK, cchs2003_p::DPSCDWK, cchs2005_p::DPSEDWK, [DPSDWK]",cont,NA::a,N/A,not applicable,not applicable,weeks,96,not applicable,Number of weeks felt depressed - (D),Number of weeks felt depressed - (D), -DPSDWK,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADWK, cchs2003_p::DPSCDWK, cchs2005_p::DPSEDWK, [DPSDWK]",cont,NA::b,N/A,missing,missing,weeks,99,not stated,Number of weeks felt depressed - (D),Number of weeks felt depressed - (D), -DPSDWK,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADWK, cchs2003_p::DPSCDWK, cchs2005_p::DPSEDWK, [DPSDWK]",cont,NA::b,N/A,missing,missing,weeks,else,else,Number of weeks felt depressed - (D),Number of weeks felt depressed - (D), -DEPDVSEV,DEPDVSEV_cat6_1,,"cchs2015_2016_p, cchs2017_2018_p",[DEPDVPHQ],cat,1,6,No depression,No depression,N/A,0,No depression,Depression scale - severity of depression - (D),Depression scale - severity of depression - (D),This module is a validated instrument to measure self-reported depression. It is called PHQ-9 and was developed by Spitzer et al (1999). It was first introduced in the CCHS in 2015. -DEPDVSEV,DEPDVSEV_cat6_2,,"cchs2015_2016_p, cchs2017_2018_p",[DEPDVPHQ],cat,2,6,Minimal depression,Minimal depression,N/A,1,Minimal depression,Depression scale - severity of depression - (D),Depression scale - severity of depression - (D), -DEPDVSEV,DEPDVSEV_cat6_3,,"cchs2015_2016_p, cchs2017_2018_p",[DEPDVPHQ],cat,3,6,Mild depression,Mild depression,N/A,2,Mild depression,Depression scale - severity of depression - (D),Depression scale - severity of depression - (D), -DEPDVSEV,DEPDVSEV_cat6_4,,"cchs2015_2016_p, cchs2017_2018_p",[DEPDVPHQ],cat,4,6,Moderate depression,Moderate depression,N/A,3,Moderate depression,Depression scale - severity of depression - (D),Depression scale - severity of depression - (D), -DEPDVSEV,DEPDVSEV_cat6_5,,"cchs2015_2016_p, cchs2017_2018_p",[DEPDVPHQ],cat,5,6,Moderately severe depression,Moderately severe depression,N/A,4,Moderately severe depression,Depression scale - severity of depression - (D),Depression scale - severity of depression - (D), -DEPDVSEV,DEPDVSEV_cat6_6,,"cchs2015_2016_p, cchs2017_2018_p",[DEPDVPHQ],cat,6,6,Severe depression,Severe depression,N/A,5,Severe depression,Depression scale - severity of depression - (D),Depression scale - severity of depression - (D), -DEPDVSEV,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[DEPDVPHQ],cat,NA::a,N/A,not applicable,not applicable,N/A,6,not applicable,Depression scale - severity of depression - (D),Depression scale - severity of depression - (D), -DEPDVSEV,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[DEPDVPHQ],cat,NA::b,N/A,missing,missing,N/A,"[7,9]",not stated,Depression scale - severity of depression - (D),Depression scale - severity of depression - (D), -DEPDVSEV,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[DEPDVPHQ],cat,NA::b,N/A,missing,missing,N/A,else,else,Depression scale - severity of depression - (D),Depression scale - severity of depression - (D), -EDUDR04,EDUDR04_cat4_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::EDUADR04, cchs2003_p::EDUCDR04, cchs2005_p::EDUEDR04, [EDUDR04]",cat,1,4,Less than high school,Less than High School,N/A,1,< Than Secondary,Education,Highest level/education - respondent 4 levels - (D),Slight change in wording of categories from CCHS 2011 onwards -EDUDR04,EDUDR04_cat4_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::EDUADR04, cchs2003_p::EDUCDR04, cchs2005_p::EDUEDR04, [EDUDR04]",cat,2,4,High school graduate,High School Graduate,N/A,2,Secondary grad,Education,Highest level/education - respondent 4 levels - (D), -EDUDR04,EDUDR04_cat4_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::EDUADR04, cchs2003_p::EDUCDR04, cchs2005_p::EDUEDR04, [EDUDR04]",cat,3,4,Some post-secondary education,Some post-secondary education,N/A,3,Other post-sec.,Education,Highest level/education - respondent 4 levels - (D), -EDUDR04,EDUDR04_cat4_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::EDUADR04, cchs2003_p::EDUCDR04, cchs2005_p::EDUEDR04, [EDUDR04]",cat,4,4,Post-secondary graduate,Post-secondary graduate,N/A,4,Post-sec. grad,Education,Highest level/education - respondent 4 levels - (D), -EDUDR04,EDUDR04_cat4_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::EDUADR04, cchs2003_p::EDUCDR04, cchs2005_p::EDUEDR04, [EDUDR04]",cat,NA::a,4,not applicable,not applicable,N/A,6,not applicable,Education,Highest level/education - respondent 4 levels - (D), -EDUDR04,EDUDR04_cat4_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::EDUADR04, cchs2003_p::EDUCDR04, cchs2005_p::EDUEDR04, [EDUDR04]",cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Education,Highest level/education - respondent 4 levels - (D),CCHS 2001 does not have don't know (7) or refusal (8) -EDUDR04,EDUDR04_cat4_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::EDUADR04, cchs2003_p::EDUCDR04, cchs2005_p::EDUEDR04, [EDUDR04]",cat,NA::b,4,missing,missing,N/A,else,else,Education,Highest level/education - respondent 4 levels - (D), -EDUDR03,EDUDR03_cat3_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::EDUADR04, cchs2003_p::EDUCDR04, cchs2005_p::EDUEDR04, [EDUDR04]",cat,1,3,Less than high school,Less than High School,N/A,1,< Than Secondary,Education,Highest level/education - respondent 3 levels - (D), -EDUDR03,EDUDR03_cat3_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::EDUADR04, cchs2003_p::EDUCDR04, cchs2005_p::EDUEDR04, [EDUDR04]",cat,2,3,High school graduate,High School Graduate,N/A,2,Secondary grad,Education,Highest level/education - respondent 3 levels - (D), -EDUDR03,EDUDR03_cat3_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::EDUADR04, cchs2003_p::EDUCDR04, cchs2005_p::EDUEDR04, [EDUDR04]",cat,3,3,Post-secondary graduate,Post-secondary graduate,N/A,"[3,4]",Post-sec. grad,Education,Highest level/education - respondent 3 levels - (D), -EDUDR03,EDUDR03_cat3_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::EDUADR04, cchs2003_p::EDUCDR04, cchs2005_p::EDUEDR04, [EDUDR04]",cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Education,Highest level/education - respondent 3 levels - (D), -EDUDR03,EDUDR03_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::EDUADR04, cchs2003_p::EDUCDR04, cchs2005_p::EDUEDR04, [EDUDR04]",cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Education,Highest level/education - respondent 3 levels - (D), -EDUDR03,EDUDR03_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::EDUADR04, cchs2003_p::EDUCDR04, cchs2005_p::EDUEDR04, [EDUDR04]",cat,NA::b,3,missing,missing,N/A,else,else,Education,Highest level/education - respondent 3 levels - (D), -EDUDR03,EDUDR03_cat3_1,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::EHG2DVR3, cchs2017_2018_p::EHG2DVR3",cat,1,3,Less than high school,Less than High School,N/A,1,< Than Secondary,Education,Highest level/education - respondent 3 levels - (D), -EDUDR03,EDUDR03_cat3_2,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::EHG2DVR3, cchs2017_2018_p::EHG2DVR3",cat,2,3,High school graduate,High School Graduate,N/A,2,Secondary grad,Education,Highest level/education - respondent 3 levels - (D), -EDUDR03,EDUDR03_cat3_3,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::EHG2DVR3, cchs2017_2018_p::EHG2DVR3",cat,3,3,Post-secondary graduate,Post-secondary graduate,N/A,3,Post-sec. grad,Education,Highest level/education - respondent 3 levels - (D), -EDUDR03,EDUDR03_cat3_NA::a,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::EHG2DVR3, cchs2017_2018_p::EHG2DVR3",cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Education,Highest level/education - respondent 3 levels - (D), -EDUDR03,EDUDR03_cat3_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::EHG2DVR3, cchs2017_2018_p::EHG2DVR3",cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Education,Highest level/education - respondent 3 levels - (D),CCHS 2015-2018 does not have don't know (7) or refusal (8) -EDUDR03,EDUDR03_cat3_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::EHG2DVR3, cchs2017_2018_p::EHG2DVR3",cat,NA::b,3,missing,missing,N/A,else,else,Education,Highest level/education - respondent 3 levels - (D), -energy_exp,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHHGAGE_cont, PAA_045, PAA_050, PAA_075, PAA_080, PAADVDYS, PAADVVIG, PAYDVTOA, PAYDVADL, PAY_105, PAYDVDYS]",N/A,func::energy_exp_fun,N/A,N/A,N/A,N/A,N/A,Daily energy expenditure,Physical Activity,Daily energy expenditure,Used for all cycles. Derived from various physical activity measure for 18+ and 12-17 years old. -energy_exp,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHHGAGE_cont, PAA_045, PAA_050, PAA_075, PAA_080, PAADVDYS, PAADVVIG, PAYDVTOA, PAYDVADL, PAY_105, PAYDVDYS]",N/A,NA::b,N/A,missing,missing,N/A,N/A,Daily energy expenditure,Physical Activity,Daily energy expenditure, -energy_exp,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::PACADEE, cchs2003_p::PACCDEE, cchs2005_p::PACEDEE, [PACDEE]",cont,copy,N/A,Daily energry expenditure,Daily energry expenditure,N/A,"[0,43.5]",Daily energy expenditure - (D),Physical Activity,Daily energy expenditure, -energy_exp,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::PACADEE, cchs2003_p::PACCDEE, cchs2005_p::PACEDEE, [PACDEE]",cont,NA::a,N/A,not applicable,not applicable,N/A,99.6,Not applicable,Physical Activity,Daily energy expenditure, -energy_exp,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::PACADEE, cchs2003_p::PACCDEE, cchs2005_p::PACEDEE, [PACDEE]",cont,NA::b,N/A,missing,missing,N/A,"[99.7,99.9]",don't know (99.7); refusal (99.8); not stated (99.9),Physical Activity,Daily energy expenditure, -energy_exp,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::PACADEE, cchs2003_p::PACCDEE, cchs2005_p::PACEDEE, [PACDEE]",cont,NA::b,N/A,missing,missing,N/A,else,else,Physical Activity,Daily energy expenditure, -FINF1,FINF1_cat2_1,cat,"cchs2001_p, cchs2003_p","cchs2001_p::FINAF1, cchs2003_p::FINCF1",cat,1,2,Yes,Yes,N/A,1,Yes,Some food insecurity in past 12 months,Some food insecurity in past 12 months, -FINF1,FINF1_cat2_2,cat,"cchs2001_p, cchs2003_p","cchs2001_p::FINAF1, cchs2003_p::FINCF1",cat,2,2,No,No,N/A,2,No,Some food insecurity in past 12 months,Some food insecurity in past 12 months, -FINF1,FINF1_cat2_NA::a,cat,"cchs2001_p, cchs2003_p","cchs2001_p::FINAF1, cchs2003_p::FINCF1",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Some food insecurity in past 12 months,Some food insecurity in past 12 months, -FINF1,FINF1_cat2_NA::b,cat,"cchs2001_p, cchs2003_p","cchs2001_p::FINAF1, cchs2003_p::FINCF1",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Some food insecurity in past 12 months,Some food insecurity in past 12 months, -FINF1,FINF1_cat2_NA::b,cat,"cchs2001_p, cchs2003_p","cchs2001_p::FINAF1, cchs2003_p::FINCF1",cat,NA::b,2,missing,missing,N/A,else,else,Some food insecurity in past 12 months,Some food insecurity in past 12 months, -FLU_160,FLU_160_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FLUA_160, cchs2003_p::FLUC_160, cchs2005_p::FLUE_160, cchs2015_2016_p::FLU_005, cchs2017_2018_p::FLU_005, [FLU_160]",cat,1,2,Yes,Yes,N/A,1,Yes,Ever had a flu shot,Have you ever had a flu shot?,"In 2007, question was reworded to ""Have you ever had a seasonal flu shot?"" In 2015-2018, question was reworded to ""Have you ever had a seasonal flu shot, excluding the H1N1 flu shot?""" -FLU_160,FLU_160_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FLUA_160, cchs2003_p::FLUC_160, cchs2005_p::FLUE_160, cchs2015_2016_p::FLU_005, cchs2017_2018_p::FLU_005, [FLU_160]",cat,2,2,No,No,N/A,2,No,Ever had a flu shot,Have you ever had a flu shot?, -FLU_160,FLU_160_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FLUA_160, cchs2003_p::FLUC_160, cchs2005_p::FLUE_160, cchs2015_2016_p::FLU_005, cchs2017_2018_p::FLU_005, [FLU_160]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Ever had a flu shot,Have you ever had a flu shot?, -FLU_160,FLU_160_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FLUA_160, cchs2003_p::FLUC_160, cchs2005_p::FLUE_160, cchs2015_2016_p::FLU_005, cchs2017_2018_p::FLU_005, [FLU_160]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Ever had a flu shot,Have you ever had a flu shot?, -FLU_160,FLU_160_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FLUA_160, cchs2003_p::FLUC_160, cchs2005_p::FLUE_160, cchs2015_2016_p::FLU_005, cchs2017_2018_p::FLU_005, [FLU_160]",cat,NA::b,2,missing,missing,N/A,else,else,Ever had a flu shot,Have you ever had a flu shot?, -FLU_162,FLU_162_cat3_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FLUA_162, cchs2003_p::FLUC_162, cchs2005_p::FLUE_162, cchs2015_2016_p::FLU_010, cchs2017_2018_p::FLU_010, [FLU_162]",cat,1,3,<1 year ago,<1 year ago,N/A,1,<1 year ago,Last time had flu shot,When did you have your last flu shot?,"In 2015-2018, question was reworded to ""When did you have your last seasonal flu shot?""" -FLU_162,FLU_162_cat3_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FLUA_162, cchs2003_p::FLUC_162, cchs2005_p::FLUE_162, cchs2015_2016_p::FLU_010, cchs2017_2018_p::FLU_010, [FLU_162]",cat,2,3,1-<2 years ago,1-<2 years ago,N/A,2,1-<2 years ago,Last time had flu shot,When did you have your last flu shot?, -FLU_162,FLU_162_cat3_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FLUA_162, cchs2003_p::FLUC_162, cchs2005_p::FLUE_162, cchs2015_2016_p::FLU_010, cchs2017_2018_p::FLU_010, [FLU_162]",cat,3,3,2 years ago or more,2 years ago or more,N/A,3,2 years ago or more,Last time had flu shot,When did you have your last flu shot?, -FLU_162,FLU_162_cat3_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FLUA_162, cchs2003_p::FLUC_162, cchs2005_p::FLUE_162, cchs2015_2016_p::FLU_010, cchs2017_2018_p::FLU_010, [FLU_162]",cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Last time had flu shot,When did you have your last flu shot?, -FLU_162,FLU_162_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FLUA_162, cchs2003_p::FLUC_162, cchs2005_p::FLUE_162, cchs2015_2016_p::FLU_010, cchs2017_2018_p::FLU_010, [FLU_162]",cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Last time had flu shot,When did you have your last flu shot?, -FLU_162,FLU_162_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FLUA_162, cchs2003_p::FLUC_162, cchs2005_p::FLUE_162, cchs2015_2016_p::FLU_010, cchs2017_2018_p::FLU_010, [FLU_162]",cat,NA::b,3,missing,missing,N/A,else,else,Last time had flu shot,When did you have your last flu shot?, -food_insecurity_der,food_insecurity_der_cat2_1,cat,"cchs2001_p, cchs2003_p","cchs2001_p::FINAF1, cchs2003_p::FINCF1",cat,1,2,No food insecurity,No food insecurity in the last 12 months,N/A,2,No food insecurity in the last 12 months,Food insecurity (last 12 months),Derived food insecurity in the last 12 months,"This variable is derived from FINF1, FSCDHFS, FSCDHFS2 by dichotomizing food insecurity into 2 categories. See ?food_insecurity_der for more details" -food_insecurity_der,food_insecurity_der_cat2_2,cat,"cchs2001_p, cchs2003_p","cchs2001_p::FINAF1, cchs2003_p::FINCF1",cat,2,2,Food insecurity,Food insecurity in the last 12 months,N/A,1,Food insecurity in the last 12 months,Food insecurity (last 12 months),Derived food insecurity in the last 12 months, -food_insecurity_der,food_insecurity_der_cat2_NA::a,cat,"cchs2001_p, cchs2003_p","cchs2001_p::FINAF1, cchs2003_p::FINCF1",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Food insecurity (last 12 months),Derived food insecurity in the last 12 months, -food_insecurity_der,food_insecurity_der_cat2_NA::b,cat,"cchs2001_p, cchs2003_p","cchs2001_p::FINAF1, cchs2003_p::FINCF1",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Food insecurity (last 12 months),Derived food insecurity in the last 12 months, -food_insecurity_der,food_insecurity_der_cat2_NA::b,cat,"cchs2001_p, cchs2003_p","cchs2001_p::FINAF1, cchs2003_p::FINCF1",cat,NA::b,2,missing,missing,N/A,else,else,Food insecurity (last 12 months),Derived food insecurity in the last 12 months, -food_insecurity_der,food_insecurity_der_cat2_1,cat,cchs2005_p,[FSCEDHFS],cat,1,2,No food insecurity,No food insecurity in the last 12 months,N/A,0,No food insecurity in the last 12 months,Food insecurity (last 12 months),Derived food insecurity in the last 12 months, -food_insecurity_der,food_insecurity_der_cat2_2,cat,cchs2005_p,[FSCEDHFS],cat,2,2,Food insecurity,Food insecurity in the last 12 months,N/A,1,Food insecurity in the last 12 months,Food insecurity (last 12 months),Derived food insecurity in the last 12 months, -food_insecurity_der,food_insecurity_der_cat2_2,cat,cchs2005_p,[FSCEDHFS],cat,2,2,Food insecurity,Food insecurity in the last 12 months,N/A,2,Food insecurity in the last 12 months,Food insecurity (last 12 months),Derived food insecurity in the last 12 months, -food_insecurity_der,food_insecurity_der_cat2_2,cat,cchs2005_p,[FSCEDHFS],cat,2,2,Food insecurity,Food insecurity in the last 12 months,N/A,3,Food insecurity in the last 12 months,Food insecurity (last 12 months),Derived food insecurity in the last 12 months, -food_insecurity_der,food_insecurity_der_cat2_NA::a,cat,cchs2005_p,[FSCEDHFS],cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Food insecurity (last 12 months),Derived food insecurity in the last 12 months, -food_insecurity_der,food_insecurity_der_cat2_NA::b,cat,cchs2005_p,[FSCEDHFS],cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Food insecurity (last 12 months),Derived food insecurity in the last 12 months, -food_insecurity_der,food_insecurity_der_cat2_NA::b,cat,cchs2005_p,[FSCEDHFS],cat,NA::b,2,missing,missing,N/A,else,else,Food insecurity (last 12 months),Derived food insecurity in the last 12 months, -food_insecurity_der,food_insecurity_der_cat2_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::FSCDVHFS, cchs2017_2018_p::FSCDVHFS, [FSCDHFS2]",cat,1,2,No food insecurity,No food insecurity in the last 12 months,N/A,0,No food insecurity in the last 12 months,Food insecurity (last 12 months),Derived food insecurity in the last 12 months, -food_insecurity_der,food_insecurity_der_cat2_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::FSCDVHFS, cchs2017_2018_p::FSCDVHFS, [FSCDHFS2]",cat,2,2,Food insecurity,Food insecurity in the last 12 months,N/A,1,Food insecurity in the last 12 months,Food insecurity (last 12 months),Derived food insecurity in the last 12 months, -food_insecurity_der,food_insecurity_der_cat2_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::FSCDVHFS, cchs2017_2018_p::FSCDVHFS, [FSCDHFS2]",cat,2,2,Food insecurity,Food insecurity in the last 12 months,N/A,2,Food insecurity in the last 12 months,Food insecurity (last 12 months),Derived food insecurity in the last 12 months, -food_insecurity_der,food_insecurity_der_cat2_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::FSCDVHFS, cchs2017_2018_p::FSCDVHFS, [FSCDHFS2]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Food insecurity (last 12 months),Derived food insecurity in the last 12 months, -food_insecurity_der,food_insecurity_der_cat2_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::FSCDVHFS, cchs2017_2018_p::FSCDVHFS, [FSCDHFS2]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Food insecurity (last 12 months),Derived food insecurity in the last 12 months, -food_insecurity_der,food_insecurity_der_cat2_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::FSCDVHFS, cchs2017_2018_p::FSCDVHFS, [FSCDHFS2]",cat,NA::b,2,missing,missing,N/A,else,else,Food insecurity (last 12 months),Derived food insecurity in the last 12 months, -FSCDHFS,FSCDHFS_cat4_0,cat,cchs2005_p,[FSCEDHFS],cat,0,4,Secure,Secure,N/A,0,Secure,Food security,Household food security status - (D),CCHS 2005 has different categories from other CCHS cycles so new variable created -FSCDHFS,FSCDHFS_cat4_1,cat,cchs2005_p,[FSCEDHFS],cat,1,4,Without hunger,Without hunger,N/A,1,Without hunger,Food security,Household food security status - (D), -FSCDHFS,FSCDHFS_cat4_2,cat,cchs2005_p,[FSCEDHFS],cat,2,4,W/mod. hunger,With moderate hunger,N/A,2,With moderate hunger,Food security,Household food security status - (D), -FSCDHFS,FSCDHFS_cat4_3,cat,cchs2005_p,[FSCEDHFS],cat,3,4,W/severe hunger,With severe hunger,N/A,3,With severe hunger,Food security,Household food security status - (D), -FSCDHFS,FSCDHFS_cat4_NA::a,cat,cchs2005_p,[FSCEDHFS],cat,NA::a,4,not applicable,not applicable,N/A,6,not applicable,Food security,Household food security status - (D), -FSCDHFS,FSCDHFS_cat4_NA::b,cat,cchs2005_p,[FSCEDHFS],cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Food security,Household food security status - (D), -FSCDHFS,FSCDHFS_cat4_NA::b,cat,cchs2005_p,[FSCEDHFS],cat,NA::b,4,missing,missing,N/A,else,else,Food security,Household food security status - (D), -FSCDHFS2,FSCDHFS2_cat3_0,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::FSCDVHFS, cchs2017_2018_p::FSCDVHFS, [FSCDHFS2]",cat,0,3,Food secure,Food secure,N/A,0,Food secure,Food security,Household Food Security Status (HC), -FSCDHFS2,FSCDHFS2_cat3_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::FSCDVHFS, cchs2017_2018_p::FSCDVHFS, [FSCDHFS2]",cat,1,3,Mod. food insec.,Mod. food insec.,N/A,1,Moderate food insecurity,Food security,Household Food Security Status (HC), -FSCDHFS2,FSCDHFS2_cat3_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::FSCDVHFS, cchs2017_2018_p::FSCDVHFS, [FSCDHFS2]",cat,2,3,Sev. food insec.,Sev. food insec.,N/A,2,Severe food insecurity,Food security,Household Food Security Status (HC), -FSCDHFS2,FSCDHFS2_cat3_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::FSCDVHFS, cchs2017_2018_p::FSCDVHFS, [FSCDHFS2]",cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Food security,Household Food Security Status (HC), -FSCDHFS2,FSCDHFS2_cat3_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::FSCDVHFS, cchs2017_2018_p::FSCDVHFS, [FSCDHFS2]",cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Food security,Household Food Security Status (HC), -FSCDHFS2,FSCDHFS2_cat3_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::FSCDVHFS, cchs2017_2018_p::FSCDVHFS, [FSCDHFS2]",cat,NA::b,3,missing,missing,N/A,else,else,Food security,Household Food Security Status (HC), -FVCDCAR,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADCAR, cchs2003_p::FVCCDCAR, cchs2005_p::FVCEDCAR, cchs2015_2016_p::FVCDVORA, cchs2017_2018_p::FVCDVORA, [FVCDCAR]",cont,copy,N/A,Daily carrots,Daily carrots,N/A,"[0,30]",Daily consumption - carrots - (D),Daily carrots,Daily consumption - carrots - (D),2015 onward changed question to look at all orange-coloured vegetables -FVCDCAR,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADCAR, cchs2003_p::FVCCDCAR, cchs2005_p::FVCEDCAR, cchs2015_2016_p::FVCDVORA, cchs2017_2018_p::FVCDVORA, [FVCDCAR]",cont,NA::a,N/A,not applicable,not applicable,N/A,999.6,Not applicable,Daily carrots,Daily consumption - carrots - (D), -FVCDCAR,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADCAR, cchs2003_p::FVCCDCAR, cchs2005_p::FVCEDCAR, cchs2015_2016_p::FVCDVORA, cchs2017_2018_p::FVCDVORA, [FVCDCAR]",cont,NA::b,N/A,missing,missing,N/A,"[999.7,999.9]",don't know (999.7); refusal (999.8); not stated (999.9),Daily carrots,Daily consumption - carrots - (D),"Don't know (999.7) and refusal (999.8) not included in 2001, 2015-2016, 2017-2018 CCHS" -FVCDCAR,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADCAR, cchs2003_p::FVCCDCAR, cchs2005_p::FVCEDCAR, cchs2015_2016_p::FVCDVORA, cchs2017_2018_p::FVCDVORA, [FVCDCAR]",cont,NA::b,N/A,missing,missing,N/A,else,else,Daily carrots,Daily consumption - carrots - (D), -FVCDFRU,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADFRU, cchs2003_p::FVCCDFRU, cchs2005_p::FVCEDFRU, cchs2015_2016_p::FVCDVFRU, cchs2017_2018_p::FVCDVFRU, [FVCDFRU]",cont,copy,N/A,Daily fruit,Daily fruit,N/A,"[0,73]",Daily consumption - fruit - (D),Daily fruit,Daily consumption - fruit - (D), -FVCDFRU,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADFRU, cchs2003_p::FVCCDFRU, cchs2005_p::FVCEDFRU, cchs2015_2016_p::FVCDVFRU, cchs2017_2018_p::FVCDVFRU, [FVCDFRU]",cont,NA::a,N/A,not applicable,not applicable,N/A,999.6,Not applicable,Daily fruit,Daily consumption - fruit - (D), -FVCDFRU,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADFRU, cchs2003_p::FVCCDFRU, cchs2005_p::FVCEDFRU, cchs2015_2016_p::FVCDVFRU, cchs2017_2018_p::FVCDVFRU, [FVCDFRU]",cont,NA::b,N/A,missing,missing,N/A,"[999.7,999.9]",don't know (999.7); refusal (999.8); not stated (999.9),Daily fruit,Daily consumption - fruit - (D),Don't know (999.7) and refusal (999.8) not included in 2001 CCHS -FVCDFRU,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADFRU, cchs2003_p::FVCCDFRU, cchs2005_p::FVCEDFRU, cchs2015_2016_p::FVCDVFRU, cchs2017_2018_p::FVCDVFRU, [FVCDFRU]",cont,NA::b,N/A,missing,missing,N/A,else,else,Daily fruit,Daily consumption - fruit - (D), -FVCDJUI,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADJUI, cchs2003_p::FVCCDJUI, cchs2005_p::FVCEDJUI, cchs2015_2016_p::FVCDVJUI, cchs2017_2018_p::FVCDVJUI, [FVCDJUI]",cont,copy,N/A,Daily juice,Daily juice,N/A,"[0,47]",Daily consumption - fruit juice - (D),Daily juice,Daily consumption - fruit juice - (D), -FVCDJUI,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADJUI, cchs2003_p::FVCCDJUI, cchs2005_p::FVCEDJUI, cchs2015_2016_p::FVCDVJUI, cchs2017_2018_p::FVCDVJUI, [FVCDJUI]",cont,NA::a,N/A,not applicable,not applicable,N/A,999.6,Not applicable,Daily juice,Daily consumption - fruit juice - (D), -FVCDJUI,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADJUI, cchs2003_p::FVCCDJUI, cchs2005_p::FVCEDJUI, cchs2015_2016_p::FVCDVJUI, cchs2017_2018_p::FVCDVJUI, [FVCDJUI]",cont,NA::b,N/A,missing,missing,N/A,"[999.7,999.9]",don't know (999.7); refusal (999.8); not stated (999.9),Daily juice,Daily consumption - fruit juice - (D),Don't know (999.7) and refusal (999.8) not included in 2001 CCHS -FVCDJUI,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADJUI, cchs2003_p::FVCCDJUI, cchs2005_p::FVCEDJUI, cchs2015_2016_p::FVCDVJUI, cchs2017_2018_p::FVCDVJUI, [FVCDJUI]",cont,NA::b,N/A,missing,missing,N/A,else,else,Daily juice,Daily consumption - fruit juice - (D), -FVCDPOT,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADPOT, cchs2003_p::FVCCDPOT, cchs2005_p::FVCEDPOT, cchs2015_2016_p::FVCDVPOT, cchs2017_2018_p::FVCDVPOT, [FVCDPOT]",cont,copy,N/A,Daily potatoes,Daily potatoes,N/A,"[0,30]",Daily consumption - potatoes - (D),Daily potatoes,Daily consumption - potatoes - (D), -FVCDPOT,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADPOT, cchs2003_p::FVCCDPOT, cchs2005_p::FVCEDPOT, cchs2015_2016_p::FVCDVPOT, cchs2017_2018_p::FVCDVPOT, [FVCDPOT]",cont,NA::a,N/A,not applicable,not applicable,N/A,999.6,Not applicable,Daily potatoes,Daily consumption - potatoes - (D), -FVCDPOT,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADPOT, cchs2003_p::FVCCDPOT, cchs2005_p::FVCEDPOT, cchs2015_2016_p::FVCDVPOT, cchs2017_2018_p::FVCDVPOT, [FVCDPOT]",cont,NA::b,N/A,missing,missing,N/A,"[999.7,999.9]",don't know (999.7); refusal (999.8); not stated (999.9),Daily potatoes,Daily consumption - potatoes - (D),Don't know (999.7) and refusal (999.8) not included in 2001 CCHS -FVCDPOT,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADPOT, cchs2003_p::FVCCDPOT, cchs2005_p::FVCEDPOT, cchs2015_2016_p::FVCDVPOT, cchs2017_2018_p::FVCDVPOT, [FVCDPOT]",cont,NA::b,N/A,missing,missing,N/A,else,else,Daily potatoes,Daily consumption - potatoes - (D), -FVCDSAL,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADSAL, cchs2003_p::FVCCDSAL, cchs2005_p::FVCEDSAL, cchs2015_2016_p::FVCDVGRN, cchs2017_2018_p::FVCDVGRN, [FVCDSAL]",cont,copy,N/A,Daily salad,Daily salad,N/A,"[0,60]",Daily consumption - green salad - (D),Daily salad,Daily consumption - green salad - (D),2015 onwards changed question to look at dark green vegetables -FVCDSAL,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADSAL, cchs2003_p::FVCCDSAL, cchs2005_p::FVCEDSAL, cchs2015_2016_p::FVCDVGRN, cchs2017_2018_p::FVCDVGRN, [FVCDSAL]",cont,NA::a,N/A,not applicable,not applicable,N/A,999.6,Not applicable,Daily salad,Daily consumption - green salad - (D), -FVCDSAL,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADSAL, cchs2003_p::FVCCDSAL, cchs2005_p::FVCEDSAL, cchs2015_2016_p::FVCDVGRN, cchs2017_2018_p::FVCDVGRN, [FVCDSAL]",cont,NA::b,N/A,missing,missing,N/A,"[999.7,999.9]",don't know (999.7); refusal (999.8); not stated (999.9),Daily salad,Daily consumption - green salad - (D),"Don't know (999.7) and refusal (999.8) not included in 2001, 2015-2016, 2017-2018 CCHS" -FVCDSAL,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADSAL, cchs2003_p::FVCCDSAL, cchs2005_p::FVCEDSAL, cchs2015_2016_p::FVCDVGRN, cchs2017_2018_p::FVCDVGRN, [FVCDSAL]",cont,NA::b,N/A,missing,missing,N/A,else,else,Daily salad,Daily consumption - green salad - (D), -FVCDTOT,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADTOT, cchs2003_p::FVCCDTOT, cchs2005_p::FVCEDTOT, cchs2015_2016_p::FVCDVTOT, cchs2017_2018_p::FVCDVTOT, [FVCDTOT]",cont,copy,N/A,Daily total fruits and vegetables,Daily total fruits and vegetables,N/A,"[0,70]",Daily consumption - total fruits and veg. - (D),Daily total fruits and vegetables,Daily consumption - total fruits and veg. - (D), -FVCDTOT,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::FVCADTOT, cchs2003_p::FVCCDTOT, cchs2005_p::FVCEDTOT, [FVCDTOT]",cont,NA::a,N/A,not applicable,not applicable,N/A,999.6,Not applicable,Daily total fruits and vegetables,Daily consumption - total fruits and veg. - (D), -FVCDTOT,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::FVCADTOT, cchs2003_p::FVCCDTOT, cchs2005_p::FVCEDTOT, [FVCDTOT]",cont,NA::b,N/A,missing,missing,N/A,"[999.7,999.9]",don't know (999.7); refusal (999.8); not stated (999.9),Daily total fruits and vegetables,Daily consumption - total fruits and veg. - (D),Don't know (999.7) and refusal (999.8) not included in 2001 CCHS -FVCDTOT,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADTOT, cchs2003_p::FVCCDTOT, cchs2005_p::FVCEDTOT, cchs2015_2016_p::FVCDVTOT, cchs2017_2018_p::FVCDVTOT, [FVCDTOT]",cont,NA::b,N/A,missing,missing,N/A,else,else,Daily total fruits and vegetables,Daily consumption - total fruits and veg. - (D), -FVCDTOT,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::FVCDVTOT, cchs2017_2018_p::FVCDVTOT, [FVCDTOT]",cont,NA::a,N/A,not applicable,not applicable,N/A,9999.6,Not applicable,Daily total fruits and vegetables,Daily consumption - total fruits and veg. - (D),Not applicable (9999.6) not included in 2015-2016 CCHS -FVCDTOT,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::FVCDVTOT, cchs2017_2018_p::FVCDVTOT, [FVCDTOT]",cont,NA::b,N/A,missing,missing,N/A,9999.9,don't know (999.7); refusal (999.8); not stated (999.9),Daily total fruits and vegetables,Daily consumption - total fruits and veg. - (D), -FVCDVEG,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADVEG, cchs2003_p::FVCCDVEG, cchs2005_p::FVCEDVEG, cchs2015_2016_p::FVCDVVEG, cchs2017_2018_p::FVCDVVEG, [FVCDVEG]",cont,copy,N/A,Daily other vegetables,Daily other vegetables,N/A,"[0,30]",Daily consumption other vegetables - (D),Daily other vegetables,Daily consumption other vegetables - (D), -FVCDVEG,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADVEG, cchs2003_p::FVCCDVEG, cchs2005_p::FVCEDVEG, cchs2015_2016_p::FVCDVVEG, cchs2017_2018_p::FVCDVVEG, [FVCDVEG]",cont,NA::a,N/A,not applicable,not applicable,N/A,999.6,Not applicable,Daily other vegetables,Daily consumption other vegetables - (D), -FVCDVEG,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADVEG, cchs2003_p::FVCCDVEG, cchs2005_p::FVCEDVEG, cchs2015_2016_p::FVCDVVEG, cchs2017_2018_p::FVCDVVEG, [FVCDVEG]",cont,NA::b,N/A,missing,missing,N/A,"[999.7,999.9]",don't know (999.7); refusal (999.8); not stated (999.9),Daily other vegetables,Daily consumption other vegetables - (D),Don't know (999.7) and refusal (999.8) not included in 2001 CCHS -FVCDVEG,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::FVCADVEG, cchs2003_p::FVCCDVEG, cchs2005_p::FVCEDVEG, cchs2015_2016_p::FVCDVVEG, cchs2017_2018_p::FVCDVVEG, [FVCDVEG]",cont,NA::b,N/A,missing,missing,N/A,else,else,Daily other vegetables,Daily consumption other vegetables - (D), -GEN_01,GEN_01_cat5_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_01, cchs2003_p::GENC_01, cchs2005_p::GENE_01, cchs2015_2016_p::GEN_005, cchs2017_2018_p::GEN_005, [GEN_01]",cat,1,5,Excellent,Excellent,N/A,1,Excellent,Self-perceived health,"In general, would you say your health is (excellent, very good, good, fair or poor)?", -GEN_01,GEN_01_cat5_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_01, cchs2003_p::GENC_01, cchs2005_p::GENE_01, cchs2015_2016_p::GEN_005, cchs2017_2018_p::GEN_005, [GEN_01]",cat,2,5,Very good,Very good,N/A,2,Very good,Self-perceived health,"In general, would you say your health is (excellent, very good, good, fair or poor)?", -GEN_01,GEN_01_cat5_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_01, cchs2003_p::GENC_01, cchs2005_p::GENE_01, cchs2015_2016_p::GEN_005, cchs2017_2018_p::GEN_005, [GEN_01]",cat,3,5,Good,Good,N/A,3,Good,Self-perceived health,"In general, would you say your health is (excellent, very good, good, fair or poor)?", -GEN_01,GEN_01_cat5_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_01, cchs2003_p::GENC_01, cchs2005_p::GENE_01, cchs2015_2016_p::GEN_005, cchs2017_2018_p::GEN_005, [GEN_01]",cat,4,5,Fair,Fair,N/A,4,Fair,Self-perceived health,"In general, would you say your health is (excellent, very good, good, fair or poor)?", -GEN_01,GEN_01_cat5_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_01, cchs2003_p::GENC_01, cchs2005_p::GENE_01, cchs2015_2016_p::GEN_005, cchs2017_2018_p::GEN_005, [GEN_01]",cat,5,5,Poor,Poor,N/A,5,Poor,Self-perceived health,"In general, would you say your health is (excellent, very good, good, fair or poor)?", -GEN_01,GEN_01_cat5_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_01, cchs2003_p::GENC_01, cchs2005_p::GENE_01, cchs2015_2016_p::GEN_005, cchs2017_2018_p::GEN_005, [GEN_01]",cat,NA::a,5,not applicable,not applicable,N/A,6,not applicable,Self-perceived health,"In general, would you say your health is (excellent, very good, good, fair or poor)?", -GEN_01,GEN_01_cat5_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_01, cchs2003_p::GENC_01, cchs2005_p::GENE_01, cchs2015_2016_p::GEN_005, cchs2017_2018_p::GEN_005, [GEN_01]",cat,NA::b,5,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Self-perceived health,"In general, would you say your health is (excellent, very good, good, fair or poor)?", -GEN_01,GEN_01_cat5_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_01, cchs2003_p::GENC_01, cchs2005_p::GENE_01, cchs2015_2016_p::GEN_005, cchs2017_2018_p::GEN_005, [GEN_01]",cat,NA::b,5,missing,missing,N/A,else,else,Self-perceived health,"In general, would you say your health is (excellent, very good, good, fair or poor)?", -GEN_02A,GEN_02A_cat5_1,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2003_p::GENC_02A, cchs2005_p::GENE_02A, [GEN_02A]",cat,1,5,Very satisfied,Very satisfied,N/A,1,Very satisfied,Satisfication with life,How satisfied are you with your life in general, -GEN_02A,GEN_02A_cat5_2,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2003_p::GENC_02A, cchs2005_p::GENE_02A, [GEN_02A]",cat,2,5,Satisfied,Satisfied,N/A,2,Satisfied,Satisfication with life,How satisfied are you with your life in general, -GEN_02A,GEN_02A_cat5_3,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2003_p::GENC_02A, cchs2005_p::GENE_02A, [GEN_02A]",cat,3,5,Neither satisfied or dissatisfied,Neither satisfied or dissatisfied,N/A,3,Neither satisfied or dissatisfied,Satisfication with life,How satisfied are you with your life in general, -GEN_02A,GEN_02A_cat5_4,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2003_p::GENC_02A, cchs2005_p::GENE_02A, [GEN_02A]",cat,4,5,Dissatisfied,Dissatisfied,N/A,4,Dissatisfied,Satisfication with life,How satisfied are you with your life in general, -GEN_02A,GEN_02A_cat5_5,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2003_p::GENC_02A, cchs2005_p::GENE_02A, [GEN_02A]",cat,5,5,Very dissatisfied,Very dissatisfied,N/A,5,Very dissatisfied,Satisfication with life,How satisfied are you with your life in general, -GEN_02A,GEN_02A_cat5_NA::a,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2003_p::GENC_02A, cchs2005_p::GENE_02A, [GEN_02A]",cat,NA::a,5,not applicable,not applicable,N/A,6,not applicable,Satisfication with life,How satisfied are you with your life in general, -GEN_02A,GEN_02A_cat5_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2003_p::GENC_02A, cchs2005_p::GENE_02A, [GEN_02A]",cat,NA::b,5,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Satisfication with life,How satisfied are you with your life in general, -GEN_02A,GEN_02A_cat5_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2003_p::GENC_02A, cchs2005_p::GENE_02A, [GEN_02A]",cat,NA::b,5,missing,missing,N/A,else,else,Satisfication with life,How satisfied are you with your life in general, -GEN_02A2,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2003_p::GENC_02A, cchs2005_p::GENE_02A, cchs2007_2008_p::GEN_02A",cat,10,5,Very satisfied,Very satisfied,N/A,1,Very satisfied,Satisfaction with life in general,"Using a scale of 0 to 10, where 0 means ""very dissatisfied"" and 10 means ""Very satisfied"", how do you feel about life as a whole right now?","For CCHS cycles 2003-2007, GEN_02A2 was derived from GEN_02A where the values were rescaled to match GEN_02A2" -GEN_02A2,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2003_p::GENC_02A, cchs2005_p::GENE_02A, cchs2007_2008_p::GEN_02A",cat,7,5,Satisfied,Satisfied,N/A,2,Satisfied,Satisfaction with life in general,"Using a scale of 0 to 10, where 0 means ""very dissatisfied"" and 10 means ""Very satisfied"", how do you feel about life as a whole right now?", -GEN_02A2,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2003_p::GENC_02A, cchs2005_p::GENE_02A, cchs2007_2008_p::GEN_02A",cat,5,5,Neither satisfied or dissatisfied,Neither satisfied or dissatisfied,N/A,3,Neither satisfied or dissatisfied,Satisfaction with life in general,"Using a scale of 0 to 10, where 0 means ""very dissatisfied"" and 10 means ""Very satisfied"", how do you feel about life as a whole right now?", -GEN_02A2,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2003_p::GENC_02A, cchs2005_p::GENE_02A, cchs2007_2008_p::GEN_02A",cat,2,5,Dissatisfied,Dissatisfied,N/A,4,Dissatisfied,Satisfaction with life in general,"Using a scale of 0 to 10, where 0 means ""very dissatisfied"" and 10 means ""Very satisfied"", how do you feel about life as a whole right now?", -GEN_02A2,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2003_p::GENC_02A, cchs2005_p::GENE_02A, cchs2007_2008_p::GEN_02A",cat,0,5,Very dissatisfied,Very dissatisfied,N/A,5,Very dissatisfied,Satisfaction with life in general,"Using a scale of 0 to 10, where 0 means ""very dissatisfied"" and 10 means ""Very satisfied"", how do you feel about life as a whole right now?", -GEN_02A2,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2003_p::GENC_02A, cchs2005_p::GENE_02A, cchs2007_2008_p::GEN_02A",cat,NA::a,5,not applicable,not applicable,N/A,6,not applicable,Satisfaction with life in general,"Using a scale of 0 to 10, where 0 means ""very dissatisfied"" and 10 means ""Very satisfied"", how do you feel about life as a whole right now?", -GEN_02A2,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2003_p::GENC_02A, cchs2005_p::GENE_02A, cchs2007_2008_p::GEN_02A",cat,NA::b,5,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Satisfaction with life in general,"Using a scale of 0 to 10, where 0 means ""very dissatisfied"" and 10 means ""Very satisfied"", how do you feel about life as a whole right now?", -GEN_02A2,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2003_p::GENC_02A, cchs2005_p::GENE_02A, cchs2007_2008_p::GEN_02A",cat,NA::b,5,missing,missing,N/A,else,else,Satisfaction with life in general,"Using a scale of 0 to 10, where 0 means ""very dissatisfied"" and 10 means ""Very satisfied"", how do you feel about life as a whole right now?", -GEN_02A2,N/A,cont,"cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::GEN_010, cchs2017_2018_p::GEN_010, [GEN_02A2]",cat,0,11,Very dissatisfied,Very dissatisfied,N/A,0,Very dissatisfied,Satisfaction with life in general,"Using a scale of 0 to 10, where 0 means ""very dissatisfied"" and 10 means ""Very satisfied"", how do you feel about life as a whole right now?", -GEN_02A2,N/A,cont,"cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::GEN_010, cchs2017_2018_p::GEN_010, [GEN_02A2]",cat,1,11,1,1,N/A,1,1,Satisfaction with life in general,"Using a scale of 0 to 10, where 0 means ""very dissatisfied"" and 10 means ""Very satisfied"", how do you feel about life as a whole right now?", -GEN_02A2,N/A,cont,"cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::GEN_010, cchs2017_2018_p::GEN_010, [GEN_02A2]",cat,2,11,2,2,N/A,2,2,Satisfaction with life in general,"Using a scale of 0 to 10, where 0 means ""very dissatisfied"" and 10 means ""Very satisfied"", how do you feel about life as a whole right now?", -GEN_02A2,N/A,cont,"cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::GEN_010, cchs2017_2018_p::GEN_010, [GEN_02A2]",cat,3,11,3,3,N/A,3,3,Satisfaction with life in general,"Using a scale of 0 to 10, where 0 means ""very dissatisfied"" and 10 means ""Very satisfied"", how do you feel about life as a whole right now?", -GEN_02A2,N/A,cont,"cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::GEN_010, cchs2017_2018_p::GEN_010, [GEN_02A2]",cat,4,11,4,4,N/A,4,4,Satisfaction with life in general,"Using a scale of 0 to 10, where 0 means ""very dissatisfied"" and 10 means ""Very satisfied"", how do you feel about life as a whole right now?", -GEN_02A2,N/A,cont,"cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::GEN_010, cchs2017_2018_p::GEN_010, [GEN_02A2]",cat,5,11,5,5,N/A,5,5,Satisfaction with life in general,"Using a scale of 0 to 10, where 0 means ""very dissatisfied"" and 10 means ""Very satisfied"", how do you feel about life as a whole right now?", -GEN_02A2,N/A,cont,"cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::GEN_010, cchs2017_2018_p::GEN_010, [GEN_02A2]",cat,6,11,6,6,N/A,6,6,Satisfaction with life in general,"Using a scale of 0 to 10, where 0 means ""very dissatisfied"" and 10 means ""Very satisfied"", how do you feel about life as a whole right now?", -GEN_02A2,N/A,cont,"cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::GEN_010, cchs2017_2018_p::GEN_010, [GEN_02A2]",cat,7,11,7,7,N/A,7,7,Satisfaction with life in general,"Using a scale of 0 to 10, where 0 means ""very dissatisfied"" and 10 means ""Very satisfied"", how do you feel about life as a whole right now?", -GEN_02A2,N/A,cont,"cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::GEN_010, cchs2017_2018_p::GEN_010, [GEN_02A2]",cat,8,11,8,8,N/A,8,8,Satisfaction with life in general,"Using a scale of 0 to 10, where 0 means ""very dissatisfied"" and 10 means ""Very satisfied"", how do you feel about life as a whole right now?", -GEN_02A2,N/A,cont,"cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::GEN_010, cchs2017_2018_p::GEN_010, [GEN_02A2]",cat,9,11,9,9,N/A,9,9,Satisfaction with life in general,"Using a scale of 0 to 10, where 0 means ""very dissatisfied"" and 10 means ""Very satisfied"", how do you feel about life as a whole right now?", -GEN_02A2,N/A,cont,"cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::GEN_010, cchs2017_2018_p::GEN_010, [GEN_02A2]",cat,10,11,Very satisfied,Very satisfied,N/A,10,Very satisfied,Satisfaction with life in general,"Using a scale of 0 to 10, where 0 means ""very dissatisfied"" and 10 means ""Very satisfied"", how do you feel about life as a whole right now?", -GEN_02A2,N/A,cont,"cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::GEN_010, cchs2017_2018_p::GEN_010, [GEN_02A2]",cat,NA::a,11,not applicable,not applicable,N/A,96,not applicable,Satisfaction with life in general,"Using a scale of 0 to 10, where 0 means ""very dissatisfied"" and 10 means ""Very satisfied"", how do you feel about life as a whole right now?",CCHS 2015-2018 does not have not applicable (96) -GEN_02A2,N/A,cont,"cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::GEN_010, cchs2017_2018_p::GEN_010, [GEN_02A2]",cat,NA::b,11,missing,missing,N/A,"[97,99]",don't know (97); refusal (98); not stated (99),Satisfaction with life in general,"Using a scale of 0 to 10, where 0 means ""very dissatisfied"" and 10 means ""Very satisfied"", how do you feel about life as a whole right now?", -GEN_02A2,N/A,cont,"cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::GEN_010, cchs2017_2018_p::GEN_010, [GEN_02A2]",cat,NA::b,11,missing,missing,N/A,else,else,Satisfaction with life in general,"Using a scale of 0 to 10, where 0 means ""very dissatisfied"" and 10 means ""Very satisfied"", how do you feel about life as a whole right now?", -GEN_02B,GEN_02B_cat5_1,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::GENC_02B, cchs2005_p::GENE_02B, cchs2015_2016_p::GEN_015, cchs2017_2018_p::GEN_015, [GEN_02B]",cat,1,5,Excellent,Excellent,N/A,1,Excellent,Self-perceived mental health,"In general, would you say your mental health is (excellent, very good, good, fair, poor)?", -GEN_02B,GEN_02B_cat5_2,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::GENC_02B, cchs2005_p::GENE_02B, cchs2015_2016_p::GEN_015, cchs2017_2018_p::GEN_015, [GEN_02B]",cat,2,5,Very good,Very good,N/A,2,Very good,Self-perceived mental health,"In general, would you say your mental health is (excellent, very good, good, fair, poor)?", -GEN_02B,GEN_02B_cat5_3,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::GENC_02B, cchs2005_p::GENE_02B, cchs2015_2016_p::GEN_015, cchs2017_2018_p::GEN_015, [GEN_02B]",cat,3,5,Good,Good,N/A,3,Good,Self-perceived mental health,"In general, would you say your mental health is (excellent, very good, good, fair, poor)?", -GEN_02B,GEN_02B_cat5_4,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::GENC_02B, cchs2005_p::GENE_02B, cchs2015_2016_p::GEN_015, cchs2017_2018_p::GEN_015, [GEN_02B]",cat,4,5,Fair,Fair,N/A,4,Fair,Self-perceived mental health,"In general, would you say your mental health is (excellent, very good, good, fair, poor)?", -GEN_02B,GEN_02B_cat5_5,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::GENC_02B, cchs2005_p::GENE_02B, cchs2015_2016_p::GEN_015, cchs2017_2018_p::GEN_015, [GEN_02B]",cat,5,5,Poor,Poor,N/A,5,Poor,Self-perceived mental health,"In general, would you say your mental health is (excellent, very good, good, fair, poor)?", -GEN_02B,GEN_02B_cat5_NA::a,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::GENC_02B, cchs2005_p::GENE_02B, cchs2015_2016_p::GEN_015, cchs2017_2018_p::GEN_015, [GEN_02B]",cat,NA::a,5,not applicable,not applicable,N/A,6,not applicable,Self-perceived mental health,"In general, would you say your mental health is (excellent, very good, good, fair, poor)?", -GEN_02B,GEN_02B_cat5_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::GENC_02B, cchs2005_p::GENE_02B, cchs2015_2016_p::GEN_015, cchs2017_2018_p::GEN_015, [GEN_02B]",cat,NA::b,5,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Self-perceived mental health,"In general, would you say your mental health is (excellent, very good, good, fair, poor)?", -GEN_02B,GEN_02B_cat5_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::GENC_02B, cchs2005_p::GENE_02B, cchs2015_2016_p::GEN_015, cchs2017_2018_p::GEN_015, [GEN_02B]",cat,NA::b,5,missing,missing,N/A,else,else,Self-perceived mental health,"In general, would you say your mental health is (excellent, very good, good, fair, poor)?", -GEN_07,GEN_07_cat5_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_07, cchs2003_p::GENC_07, cchs2005_p::GENE_07, cchs2015_2016_p::GEN_020, cchs2017_2018_p:: GEN_020, [GEN_07]",cat,1,5,Not at all,Not at all,N/A,1,Not at all,Self-perceived life stress,"Thinking about the amount of stress in your life, would you say that most days are (not at all stressful, not very stressful, a bit stressful, quite a bit stressful, extremely stressful)?", -GEN_07,GEN_07_cat5_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_07, cchs2003_p::GENC_07, cchs2005_p::GENE_07, cchs2015_2016_p::GEN_020, cchs2017_2018_p:: GEN_020, [GEN_07]",cat,2,5,Not very,Not very,N/A,2,Not very,Self-perceived life stress,"Thinking about the amount of stress in your life, would you say that most days are (not at all stressful, not very stressful, a bit stressful, quite a bit stressful, extremely stressful)?", -GEN_07,GEN_07_cat5_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_07, cchs2003_p::GENC_07, cchs2005_p::GENE_07, cchs2015_2016_p::GEN_020, cchs2017_2018_p:: GEN_020, [GEN_07]",cat,3,5,A bit,A bit,N/A,3,A bit,Self-perceived life stress,"Thinking about the amount of stress in your life, would you say that most days are (not at all stressful, not very stressful, a bit stressful, quite a bit stressful, extremely stressful)?", -GEN_07,GEN_07_cat5_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_07, cchs2003_p::GENC_07, cchs2005_p::GENE_07, cchs2015_2016_p::GEN_020, cchs2017_2018_p:: GEN_020, [GEN_07]",cat,4,5,Quite a bit,Quite a bit,N/A,4,Quite a bit,Self-perceived life stress,"Thinking about the amount of stress in your life, would you say that most days are (not at all stressful, not very stressful, a bit stressful, quite a bit stressful, extremely stressful)?", -GEN_07,GEN_07_cat5_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_07, cchs2003_p::GENC_07, cchs2005_p::GENE_07, cchs2015_2016_p::GEN_020, cchs2017_2018_p:: GEN_020, [GEN_07]",cat,5,5,Extremely,Extremely,N/A,5,Extremely,Self-perceived life stress,"Thinking about the amount of stress in your life, would you say that most days are (not at all stressful, not very stressful, a bit stressful, quite a bit stressful, extremely stressful)?", -GEN_07,GEN_07_cat5_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_07, cchs2003_p::GENC_07, cchs2005_p::GENE_07, cchs2015_2016_p::GEN_020, cchs2017_2018_p:: GEN_020, [GEN_07]",cat,NA::a,5,not applicable,not applicable,N/A,6,not applicable,Self-perceived life stress,"Thinking about the amount of stress in your life, would you say that most days are (not at all stressful, not very stressful, a bit stressful, quite a bit stressful, extremely stressful)?",CCHS 2015-2018 does not have not applicable (6) -GEN_07,GEN_07_cat5_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_07, cchs2003_p::GENC_07, cchs2005_p::GENE_07, cchs2015_2016_p::GEN_020, cchs2017_2018_p:: GEN_020, [GEN_07]",cat,NA::b,5,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Self-perceived life stress,"Thinking about the amount of stress in your life, would you say that most days are (not at all stressful, not very stressful, a bit stressful, quite a bit stressful, extremely stressful)?", -GEN_07,GEN_07_cat5_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_07, cchs2003_p::GENC_07, cchs2005_p::GENE_07, cchs2015_2016_p::GEN_020, cchs2017_2018_p:: GEN_020, [GEN_07]",cat,NA::b,5,missing,missing,N/A,else,else,Self-perceived life stress,"Thinking about the amount of stress in your life, would you say that most days are (not at all stressful, not very stressful, a bit stressful, quite a bit stressful, extremely stressful)?", -GEN_09,GEN_09_cat5_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_09, cchs2003_p::GENC_09, cchs2005_p::GENE_09, cchs2015_2016_p::GEN_025, cchs2017_2018_p::GEN_025, [GEN_09]",cat,1,5,Not at all,Not at all,N/A,1,Not at all,Self-perceived work stress,"Would you say that most days at work were (not at all stressful, not very stressful, a bit stressful, quite a bit stressful, extremely stressful)?", -GEN_09,GEN_09_cat5_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_09, cchs2003_p::GENC_09, cchs2005_p::GENE_09, cchs2015_2016_p::GEN_025, cchs2017_2018_p::GEN_025, [GEN_09]",cat,2,5,Not very,Not very,N/A,2,Not very,Self-perceived work stress,"Would you say that most days at work were (not at all stressful, not very stressful, a bit stressful, quite a bit stressful, extremely stressful)?", -GEN_09,GEN_09_cat5_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_09, cchs2003_p::GENC_09, cchs2005_p::GENE_09, cchs2015_2016_p::GEN_025, cchs2017_2018_p::GEN_025, [GEN_09]",cat,3,5,A bit,A bit,N/A,3,A bit,Self-perceived work stress,"Would you say that most days at work were (not at all stressful, not very stressful, a bit stressful, quite a bit stressful, extremely stressful)?", -GEN_09,GEN_09_cat5_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_09, cchs2003_p::GENC_09, cchs2005_p::GENE_09, cchs2015_2016_p::GEN_025, cchs2017_2018_p::GEN_025, [GEN_09]",cat,4,5,Quite a bit,Quite a bit,N/A,4,Quite a bit,Self-perceived work stress,"Would you say that most days at work were (not at all stressful, not very stressful, a bit stressful, quite a bit stressful, extremely stressful)?", -GEN_09,GEN_09_cat5_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_09, cchs2003_p::GENC_09, cchs2005_p::GENE_09, cchs2015_2016_p::GEN_025, cchs2017_2018_p::GEN_025, [GEN_09]",cat,5,5,Extremely,Extremely,N/A,5,Extremely,Self-perceived work stress,"Would you say that most days at work were (not at all stressful, not very stressful, a bit stressful, quite a bit stressful, extremely stressful)?", -GEN_09,GEN_09_cat5_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_09, cchs2003_p::GENC_09, cchs2005_p::GENE_09, cchs2015_2016_p::GEN_025, cchs2017_2018_p::GEN_025, [GEN_09]",cat,NA::a,5,not applicable,not applicable,N/A,6,not applicable,Self-perceived work stress,"Would you say that most days at work were (not at all stressful, not very stressful, a bit stressful, quite a bit stressful, extremely stressful)?", -GEN_09,GEN_09_cat5_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_09, cchs2003_p::GENC_09, cchs2005_p::GENE_09, cchs2015_2016_p::GEN_025, cchs2017_2018_p::GEN_025, [GEN_09]",cat,NA::b,5,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Self-perceived work stress,"Would you say that most days at work were (not at all stressful, not very stressful, a bit stressful, quite a bit stressful, extremely stressful)?", -GEN_09,GEN_09_cat5_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_09, cchs2003_p::GENC_09, cchs2005_p::GENE_09, cchs2015_2016_p::GEN_025, cchs2017_2018_p::GEN_025, [GEN_09]",cat,NA::b,5,missing,missing,N/A,else,else,Self-perceived work stress,"Would you say that most days at work were (not at all stressful, not very stressful, a bit stressful, quite a bit stressful, extremely stressful)?", -GEN_10,GEN_10_cat4_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_10, cchs2003_p::GENC_10, cchs2005_p::GENE_10, cchs2015_2016_p::GEN_030, cchs2017_2018_p::GEN_030, [GEN_10]",cat,1,4,Very strong,Very strong,N/A,1,Very strong,Sense of belonging in the community,How would you describe your sense of belonging to your local community?, -GEN_10,GEN_10_cat4_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_10, cchs2003_p::GENC_10, cchs2005_p::GENE_10, cchs2015_2016_p::GEN_030, cchs2017_2018_p::GEN_030, [GEN_10]",cat,2,4,Somewhat strong,Somewhat strong,N/A,2,Somewhat strong,Sense of belonging in the community,How would you describe your sense of belonging to your local community?, -GEN_10,GEN_10_cat4_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_10, cchs2003_p::GENC_10, cchs2005_p::GENE_10, cchs2015_2016_p::GEN_030, cchs2017_2018_p::GEN_030, [GEN_10]",cat,3,4,Somewhat weak,Somewhat weak,N/A,3,Somewhat weak,Sense of belonging in the community,How would you describe your sense of belonging to your local community?, -GEN_10,GEN_10_cat4_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_10, cchs2003_p::GENC_10, cchs2005_p::GENE_10, cchs2015_2016_p::GEN_030, cchs2017_2018_p::GEN_030, [GEN_10]",cat,4,4,Very weak,Very weak,N/A,4,Very weak,Sense of belonging in the community,How would you describe your sense of belonging to your local community?, -GEN_10,GEN_10_cat4_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_10, cchs2003_p::GENC_10, cchs2005_p::GENE_10, cchs2015_2016_p::GEN_030, cchs2017_2018_p::GEN_030, [GEN_10]",cat,NA::a,4,not applicable,not applicable,N/A,6,not applicable,Sense of belonging in the community,How would you describe your sense of belonging to your local community?, -GEN_10,GEN_10_cat4_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_10, cchs2003_p::GENC_10, cchs2005_p::GENE_10, cchs2015_2016_p::GEN_030, cchs2017_2018_p::GEN_030, [GEN_10]",cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Sense of belonging in the community,How would you describe your sense of belonging to your local community?, -GEN_10,GEN_10_cat4_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GENA_10, cchs2003_p::GENC_10, cchs2005_p::GENE_10, cchs2015_2016_p::GEN_030, cchs2017_2018_p::GEN_030, [GEN_10]",cat,NA::b,4,missing,missing,N/A,else,else,Sense of belonging in the community,How would you describe your sense of belonging to your local community?, -GEODPMF,GEODPMF_cat97_1,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,10911,97,EASTERN REGIONAL INTEGRATED HA,EASTERN REGIONAL INTEGRATED HA,N/A,10911,EASTERN REGIONAL INTEGRATED HA,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_2,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,10912,97,CENTRAL REGIONAL INTEGRATED HA,CENTRAL REGIONAL INTEGRATED HA,N/A,10912,CENTRAL REGIONAL INTEGRATED HA,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_3,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,10913,97,WESTERN/LABRADOR-GRENFELL REGIONAL HA,WESTERN/LABRADOR-GRENFELL REGIONAL HA,N/A,10913,WESTERN/LABRADOR-GRENFELL REGIONAL HA,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_4,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,11901,97,PRINCE EDWARD ISLAND,PRINCE EDWARD ISLAND,N/A,11901,PRINCE EDWARD ISLAND,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_5,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,12910,97,SOUTH SHORE-SOUTH WEST NOVA,SOUTH SHORE-SOUTH WEST NOVA,N/A,12910,SOUTH SHORE-SOUTH WEST NOVA,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_6,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,12923,97,ANNAPOLIS VALLEY DISTRICT HEALTH AUT,ANNAPOLIS VALLEY DISTRICT HEALTH AUT,N/A,12923,ANNAPOLIS VALLEY DISTRICT HEALTH AUT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_7,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,12930,97,COLCHESTER EAST HANTS-CUMBERLAND,COLCHESTER EAST HANTS-CUMBERLAND,N/A,12930,COLCHESTER EAST HANTS-CUMBERLAND,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_8,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,12940,97,PICTOU COUNTY-GUYSBOROUGH ANTIGONISH,PICTOU COUNTY-GUYSBOROUGH ANTIGONISH,N/A,12940,PICTOU COUNTY-GUYSBOROUGH ANTIGONISH,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_9,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,12958,97,CAPE BRETON DISTRICT HEALTH AUTHORITY,CAPE BRETON DISTRICT HEALTH AUTHORITY,N/A,12958,CAPE BRETON DISTRICT HEALTH AUTHORITY,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_10,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,12969,97,CAPITAL DISTRICT HEALTH AUTHORITY,CAPITAL DISTRICT HEALTH AUTHORITY,N/A,12969,CAPITAL DISTRICT HEALTH AUTHORITY,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_11,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,13901,97,ZONE 1,ZONE 1,N/A,13901,ZONE 1,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_12,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,13902,97,ZONE 2,ZONE 2,N/A,13902,ZONE 2,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_13,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,13903,97,ZONE 3,ZONE 3,N/A,13903,ZONE 3,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_14,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,13904,97,ZONES 4 AND 5,ZONES 4 AND 5,N/A,13904,ZONES 4 AND 5,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_15,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,13906,97,ZONES 6 AND 7,ZONES 6 AND 7,N/A,13906,ZONES 6 AND 7,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_16,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,24901,97,REGION DU BAS-SAINT-LAURENT,REGION DU BAS-SAINT-LAURENT,N/A,24901,REGION DU BAS-SAINT-LAURENT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_17,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,24902,97,REGION DU SAGUENAY - LAC-SAINT-JEAN,REGION DU SAGUENAY - LAC-SAINT-JEAN,N/A,24902,REGION DU SAGUENAY - LAC-SAINT-JEAN,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_18,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,24903,97,REGION DE LA CAPITALE-NATIONALE,REGION DE LA CAPITALE-NATIONALE,N/A,24903,REGION DE LA CAPITALE-NATIONALE,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_19,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,24904,97,REGION DE LA MAURICIE-CENTRE-DU-QUEBEC,REGION DE LA MAURICIE-CENTRE-DU-QUEBEC,N/A,24904,REGION DE LA MAURICIE-CENTRE-DU-QUEBEC,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_20,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,24905,97,REGION DE L'ESTRIE,REGION DE L'ESTRIE,N/A,24905,REGION DE L'ESTRIE,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_21,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,24906,97,REGION DE MONTREAL,REGION DE MONTREAL,N/A,24906,REGION DE MONTREAL,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_22,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,24907,97,REGION DE L'OUTAOUAIS,REGION DE L'OUTAOUAIS,N/A,24907,REGION DE L'OUTAOUAIS,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_23,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,24908,97,REGION DE L'ABITIBI-TEMISCAMINGUE,REGION DE L'ABITIBI-TEMISCAMINGUE,N/A,24908,REGION DE L'ABITIBI-TEMISCAMINGUE,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_24,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,24909,97,REGION DE LA COTE-NORD,REGION DE LA COTE-NORD,N/A,24909,REGION DE LA COTE-NORD,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_25,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,24911,97,REG. DE LA GASPESIE-ILES-DE-LA-MADELEINE,REG. DE LA GASPESIE-ILES-DE-LA-MADELEINE,N/A,24911,REG. DE LA GASPESIE-ILES-DE-LA-MADELEINE,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_26,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,24912,97,REGION DE LA CHAUDIERE-APPALACHES,REGION DE LA CHAUDIERE-APPALACHES,N/A,24912,REGION DE LA CHAUDIERE-APPALACHES,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_27,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,24913,97,REGION DE LAVAL,REGION DE LAVAL,N/A,24913,REGION DE LAVAL,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_28,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,24914,97,REGION DE LANAUDIERE,REGION DE LANAUDIERE,N/A,24914,REGION DE LANAUDIERE,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_29,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,24915,97,REGION DES LAURENTIDES,REGION DES LAURENTIDES,N/A,24915,REGION DES LAURENTIDES,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_30,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,24916,97,REGION DE LA MONTEREGIE,REGION DE LA MONTEREGIE,N/A,24916,REGION DE LA MONTEREGIE,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_31,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35926,97,DISTRICT OF ALGOMA HEALTH UNIT,DISTRICT OF ALGOMA HEALTH UNIT,N/A,35926,DISTRICT OF ALGOMA HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_32,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35927,97,BRANT COUNTY HEALTH UNIT,BRANT COUNTY HEALTH UNIT,N/A,35927,BRANT COUNTY HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_33,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35930,97,DURHAM REGIONAL HEALTH UNIT,DURHAM REGIONAL HEALTH UNIT,N/A,35930,DURHAM REGIONAL HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_34,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35931,97,ELGIN-ST THOMAS HEALTH UNIT,ELGIN-ST THOMAS HEALTH UNIT,N/A,35931,ELGIN-ST THOMAS HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_35,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35933,97,GREY BRUCE HEALTH UNIT,GREY BRUCE HEALTH UNIT,N/A,35933,GREY BRUCE HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_36,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35934,97,HALDIMAND-NORFOLK HEALTH UNIT,HALDIMAND-NORFOLK HEALTH UNIT,N/A,35934,HALDIMAND-NORFOLK HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_37,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35935,97,HALIBURTON-KAWARTHA-PINE RIDGE DHU,HALIBURTON-KAWARTHA-PINE RIDGE DHU,N/A,35935,HALIBURTON-KAWARTHA-PINE RIDGE DHU,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_38,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35936,97,HALTON REGIONAL HEALTH UNIT,HALTON REGIONAL HEALTH UNIT,N/A,35936,HALTON REGIONAL HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_39,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35937,97,CITY OF HAMILTON HEALTH UNIT,CITY OF HAMILTON HEALTH UNIT,N/A,35937,CITY OF HAMILTON HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_40,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35938,97,HASTINGS AND PRINCE EDWARD COUNTIES HU,HASTINGS AND PRINCE EDWARD COUNTIES HU,N/A,35938,HASTINGS AND PRINCE EDWARD COUNTIES HU,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_41,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35939,97,HURON AND PERTH HEALTH UNITS,HURON AND PERTH HEALTH UNITS,N/A,35939,HURON AND PERTH HEALTH UNITS,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_42,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35940,97,CHATHAM-KENT HEALTH UNIT,CHATHAM-KENT HEALTH UNIT,N/A,35940,CHATHAM-KENT HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_43,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35941,97,KINGSTON-FRONTENAC-LENNOX-ADDINGTON HU,KINGSTON-FRONTENAC-LENNOX-ADDINGTON HU,N/A,35941,KINGSTON-FRONTENAC-LENNOX-ADDINGTON HU,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_44,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35942,97,LAMBTON HEALTH UNIT,LAMBTON HEALTH UNIT,N/A,35942,LAMBTON HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_45,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35943,97,LEEDS-GRENVILLE-LANARK DHU,LEEDS-GRENVILLE-LANARK DHU,N/A,35943,LEEDS-GRENVILLE-LANARK DHU,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_46,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35944,97,MIDDLESEX-LONDON HEALTH UNIT,MIDDLESEX-LONDON HEALTH UNIT,N/A,35944,MIDDLESEX-LONDON HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_47,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35946,97,NIAGARA REGIONAL AREA HEALTH UNIT,NIAGARA REGIONAL AREA HEALTH UNIT,N/A,35946,NIAGARA REGIONAL AREA HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_48,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35947,97,NORTH BAY AND TIMISKAMING HEALTH UNITS,NORTH BAY AND TIMISKAMING HEALTH UNITS,N/A,35947,NORTH BAY AND TIMISKAMING HEALTH UNITS,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_49,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35949,97,NORTHWESTERN HEALTH UNIT,NORTHWESTERN HEALTH UNIT,N/A,35949,NORTHWESTERN HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_50,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35951,97,CITY OF OTTAWA HEALTH UNIT,CITY OF OTTAWA HEALTH UNIT,N/A,35951,CITY OF OTTAWA HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_51,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35952,97,OXFORD COUNTY HEALTH UNIT,OXFORD COUNTY HEALTH UNIT,N/A,35952,OXFORD COUNTY HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_52,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35953,97,PEEL REGIONAL HEALTH UNIT,PEEL REGIONAL HEALTH UNIT,N/A,35953,PEEL REGIONAL HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_53,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35955,97,PETERBOROUGH COUNTY-CITY HEALTH UNIT,PETERBOROUGH COUNTY-CITY HEALTH UNIT,N/A,35955,PETERBOROUGH COUNTY-CITY HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_54,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35956,97,PORCUPINE HEALTH UNIT,PORCUPINE HEALTH UNIT,N/A,35956,PORCUPINE HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_55,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35957,97,RENFREW COUNTY AND DISTRICT HEALTH UNIT,RENFREW COUNTY AND DISTRICT HEALTH UNIT,N/A,35957,RENFREW COUNTY AND DISTRICT HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_56,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35958,97,EASTERN ONTARIO HEALTH UNIT,EASTERN ONTARIO HEALTH UNIT,N/A,35958,EASTERN ONTARIO HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_57,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35960,97,SIMCOE MUSKOKA DISTRICT HEALTH UNIT,SIMCOE MUSKOKA DISTRICT HEALTH UNIT,N/A,35960,SIMCOE MUSKOKA DISTRICT HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_58,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35961,97,SUDBURY AND DISTRICT HEALTH UNIT,SUDBURY AND DISTRICT HEALTH UNIT,N/A,35961,SUDBURY AND DISTRICT HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_59,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35962,97,THUNDER BAY DISTRICT HEALTH UNIT,THUNDER BAY DISTRICT HEALTH UNIT,N/A,35962,THUNDER BAY DISTRICT HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_60,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35965,97,WATERLOO HEALTH UNIT,WATERLOO HEALTH UNIT,N/A,35965,WATERLOO HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_61,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35966,97,WELLINGTON-DUFFERIN-GUELPH HU,WELLINGTON-DUFFERIN-GUELPH HU,N/A,35966,WELLINGTON-DUFFERIN-GUELPH HU,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_62,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35968,97,WINDSOR-ESSEX COUNTY HEALTH UNIT,WINDSOR-ESSEX COUNTY HEALTH UNIT,N/A,35968,WINDSOR-ESSEX COUNTY HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_63,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35970,97,YORK REGIONAL HEALTH UNIT,YORK REGIONAL HEALTH UNIT,N/A,35970,YORK REGIONAL HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_64,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,35995,97,CITY OF TORONTO HEALTH UNIT,CITY OF TORONTO HEALTH UNIT,N/A,35995,CITY OF TORONTO HEALTH UNIT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_65,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,46901,97,WINNIPEG RHA,WINNIPEG RHA,N/A,46901,WINNIPEG RHA,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_66,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,46902,97,PRAIRIE M. HEALTH,PRAIRIE M. HEALTH,N/A,46902,PRAIRIE M. HEALTH,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_67,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,46903,97,INTERLAKE-EASTERN RHA,INTERLAKE-EASTERN RHA,N/A,46903,INTERLAKE-EASTERN RHA,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_68,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,46904,97,NORTHEN RHA,NORTHEN RHA,N/A,46904,NORTHEN RHA,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_69,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,46905,97,SOUTHEN HEALTH,SOUTHEN HEALTH,N/A,46905,SOUTHEN HEALTH,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_70,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,47901,97,SUN COUNTRY/FIVE HILLS/CYPRESS,SUN COUNTRY/FIVE HILLS/CYPRESS,N/A,47901,SUN COUNTRY/FIVE HILLS/CYPRESS,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_71,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,47904,97,REGINA QU'APPELLE,REGINA QU'APPELLE,N/A,47904,REGINA QU'APPELLE,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_72,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,47905,97,SUNRISE/KELSEY TRAIL,SUNRISE/KELSEY TRAIL,N/A,47905,SUNRISE/KELSEY TRAIL,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_73,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,47906,97,SASKATOON,SASKATOON,N/A,47906,SASKATOON,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_74,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,47907,97,HEARTLAND/PRAIRIE NORTH,HEARTLAND/PRAIRIE NORTH,N/A,47907,HEARTLAND/PRAIRIE NORTH,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_75,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,47909,97,PRINCE ALBERT/MAMAWETAN/KEEWATIN/ATHABA,PRINCE ALBERT/MAMAWETAN/KEEWATIN/ATHABA,N/A,47909,PRINCE ALBERT/MAMAWETAN/KEEWATIN/ATHABA,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_76,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,48931,97,SOUTH ZONE,SOUTH ZONE,N/A,48931,SOUTH ZONE,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_77,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,48932,97,CALGARY ZONE,CALGARY ZONE,N/A,48932,CALGARY ZONE,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_78,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,48933,97,CENTRAL ZONE,CENTRAL ZONE,N/A,48933,CENTRAL ZONE,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_79,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,48934,97,EDMONTON ZONE,EDMONTON ZONE,N/A,48934,EDMONTON ZONE,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_80,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,48935,97,NORTH ZONE,NORTH ZONE,N/A,48935,NORTH ZONE,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_81,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,59911,97,EAST KOOTENAY,EAST KOOTENAY,N/A,59911,EAST KOOTENAY,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_82,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,59912,97,KOOTENAY-BOUNDARY,KOOTENAY-BOUNDARY,N/A,59912,KOOTENAY-BOUNDARY,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_83,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,59913,97,OKANAGAN,OKANAGAN,N/A,59913,OKANAGAN,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_84,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,59914,97,THOMPSON/CARIBOO,THOMPSON/CARIBOO,N/A,59914,THOMPSON/CARIBOO,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_85,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,59921,97,FRASER EAST,FRASER EAST,N/A,59921,FRASER EAST,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_86,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,59922,97,FRASER NORTH,FRASER NORTH,N/A,59922,FRASER NORTH,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_87,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,59923,97,FRASER SOUTH,FRASER SOUTH,N/A,59923,FRASER SOUTH,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_88,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,59931,97,RICHMOND,RICHMOND,N/A,59931,RICHMOND,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_89,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,59932,97,VANCOUVER,VANCOUVER,N/A,59932,VANCOUVER,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_90,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,59933,97,NORTH SHORE/COAST GARIBALDI,NORTH SHORE/COAST GARIBALDI,N/A,59933,NORTH SHORE/COAST GARIBALDI,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_91,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,59941,97,SOUTH VANCOUVER ISLAND,SOUTH VANCOUVER ISLAND,N/A,59941,SOUTH VANCOUVER ISLAND,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_92,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,59942,97,CENTRAL VANCOUVER ISLAND,CENTRAL VANCOUVER ISLAND,N/A,59942,CENTRAL VANCOUVER ISLAND,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_93,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,59943,97,NORTH VANCOUVER ISLAND,NORTH VANCOUVER ISLAND,N/A,59943,NORTH VANCOUVER ISLAND,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_94,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,59951,97,NORTHWEST,NORTHWEST,N/A,59951,NORTHWEST,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_95,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,59952,97,NORTHERN INTERIOR,NORTHERN INTERIOR,N/A,59952,NORTHERN INTERIOR,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_96,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,59953,97,NORTHEAST,NORTHEAST,N/A,59953,NORTHEAST,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_97,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,60901,97,YUKON/NORTHWEST TERRITORIES/NUNAVUT,YUKON/NORTHWEST TERRITORIES/NUNAVUT,N/A,60901,YUKON/NORTHWEST TERRITORIES/NUNAVUT,Health Region - (G),Health Region - (G), -GEODPMF,GEODPMF_cat97_NA::b,cat,"cchs2013_2014_p, cchs2014_p",[GEODPMF],cat,NA::b,97,missing,missing,N/A,else,else,Health Region - (G),Health Region - (G), -GEOGPRV,GEOGPRV_cat11_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GEOAGPRV, cchs2003_p::GEOCGPRV, cchs2005_p::GEOEGPRV, cchs2015_2016_p::GEO_PRV, cchs2017_2018_p::GEO_PRV, [GEOGPRV]",cat,10,11,NL,Nfld. & Labrador,N/A,10,Nfld. & Labrador,Province,Province of residence of respondent - (G), -GEOGPRV,GEOGPRV_cat11_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GEOAGPRV, cchs2003_p::GEOCGPRV, cchs2005_p::GEOEGPRV, cchs2015_2016_p::GEO_PRV, cchs2017_2018_p::GEO_PRV, [GEOGPRV]",cat,11,11,PEI,Prince Edward Island,N/A,11,Prince Edward Island,Province,Province of residence of respondent - (G), -GEOGPRV,GEOGPRV_cat11_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GEOAGPRV, cchs2003_p::GEOCGPRV, cchs2005_p::GEOEGPRV, cchs2015_2016_p::GEO_PRV, cchs2017_2018_p::GEO_PRV, [GEOGPRV]",cat,12,11,NS,Nova Scotia,N/A,12,Nova Scotia,Province,Province of residence of respondent - (G), -GEOGPRV,GEOGPRV_cat11_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GEOAGPRV, cchs2003_p::GEOCGPRV, cchs2005_p::GEOEGPRV, cchs2015_2016_p::GEO_PRV, cchs2017_2018_p::GEO_PRV, [GEOGPRV]",cat,13,11,NB,New Brunswick,N/A,13,New Brunswick,Province,Province of residence of respondent - (G), -GEOGPRV,GEOGPRV_cat11_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GEOAGPRV, cchs2003_p::GEOCGPRV, cchs2005_p::GEOEGPRV, cchs2015_2016_p::GEO_PRV, cchs2017_2018_p::GEO_PRV, [GEOGPRV]",cat,24,11,QC,Quebec,N/A,24,Quebec,Province,Province of residence of respondent - (G), -GEOGPRV,GEOGPRV_cat11_6,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GEOAGPRV, cchs2003_p::GEOCGPRV, cchs2005_p::GEOEGPRV, cchs2015_2016_p::GEO_PRV, cchs2017_2018_p::GEO_PRV, [GEOGPRV]",cat,35,11,ON,Ontario,N/A,35,Ontario,Province,Province of residence of respondent - (G), -GEOGPRV,GEOGPRV_cat11_7,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GEOAGPRV, cchs2003_p::GEOCGPRV, cchs2005_p::GEOEGPRV, cchs2015_2016_p::GEO_PRV, cchs2017_2018_p::GEO_PRV, [GEOGPRV]",cat,46,11,MB,Manitoba,N/A,46,Manitoba,Province,Province of residence of respondent - (G), -GEOGPRV,GEOGPRV_cat11_8,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GEOAGPRV, cchs2003_p::GEOCGPRV, cchs2005_p::GEOEGPRV, cchs2015_2016_p::GEO_PRV, cchs2017_2018_p::GEO_PRV, [GEOGPRV]",cat,47,11,SK,Saskatchewan,N/A,47,Saskatchewan,Province,Province of residence of respondent - (G), -GEOGPRV,GEOGPRV_cat11_9,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GEOAGPRV, cchs2003_p::GEOCGPRV, cchs2005_p::GEOEGPRV, cchs2015_2016_p::GEO_PRV, cchs2017_2018_p::GEO_PRV, [GEOGPRV]",cat,48,11,AB,Alberta,N/A,48,Alberta,Province,Province of residence of respondent - (G), -GEOGPRV,GEOGPRV_cat11_10,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GEOAGPRV, cchs2003_p::GEOCGPRV, cchs2005_p::GEOEGPRV, cchs2015_2016_p::GEO_PRV, cchs2017_2018_p::GEO_PRV, [GEOGPRV]",cat,59,11,BC,British Columbia,N/A,59,British Columbia,Province,Province of residence of respondent - (G), -GEOGPRV,GEOGPRV_cat11_11,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GEOAGPRV, cchs2003_p::GEOCGPRV, cchs2005_p::GEOEGPRV, cchs2015_2016_p::GEO_PRV, cchs2017_2018_p::GEO_PRV, [GEOGPRV]",cat,60,11,YT/NT/NU,Yukon/NWT/Nunavut,N/A,"[60,62]",Yukon/NWT/Nunavut,Province,Province of residence of respondent - (G),"CCHS2015_2016 and CCHS2017_2018 divides category into Yukon (60), NWT (61), and Nunavut (62)" -GEOGPRV,GEOGPRV_cat11_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GEOAGPRV, cchs2003_p::GEOCGPRV, cchs2005_p::GEOEGPRV, cchs2015_2016_p::GEO_PRV, cchs2017_2018_p::GEO_PRV, [GEOGPRV]",cat,NA::a,11,not applicable,not applicable,N/A,96,not applicable,Province,Province of residence of respondent - (G), -GEOGPRV,GEOGPRV_cat11_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GEOAGPRV, cchs2003_p::GEOCGPRV, cchs2005_p::GEOEGPRV, cchs2015_2016_p::GEO_PRV, cchs2017_2018_p::GEO_PRV, [GEOGPRV]",cat,NA::b,11,missing,missing,N/A,"[97,99]","don't know (97), refusal (98), not stated (99)",Province,Province of residence of respondent - (G), -GEOGPRV,GEOGPRV_cat11_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::GEOAGPRV, cchs2003_p::GEOCGPRV, cchs2005_p::GEOEGPRV, cchs2015_2016_p::GEO_PRV, cchs2017_2018_p::GEO_PRV, [GEOGPRV]",cat,NA::b,11,missing,missing,N/A,else,else,Province,Province of residence of respondent - (G), -HCU_1AA,HCU_1AA_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::TWDA_5, cchs2003_p::HCUC_1AA, cchs2005_p::HCUE_1AA, cchs2015_2016_p::PHC_020, cchs2017_2018_p::PHC_020, [HCU_1AA]",cat,1,2,Yes,Yes (Has regular medical doctor),N/A,1,Yes (Has regular medical doctor),Has regular medical doctor,Do you have a regular medical doctor?,"In 2015-2018, question was reworded to ""Do you have a regular health care provider?""" -HCU_1AA,HCU_1AA_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::TWDA_5, cchs2003_p::HCUC_1AA, cchs2005_p::HCUE_1AA, cchs2015_2016_p::PHC_020, cchs2017_2018_p::PHC_020, [HCU_1AA]",cat,2,2,No,No (Does not have regular medical doctor),N/A,2,No (Does not have regular medical doctor),Has regular medical doctor,Do you have a regular medical doctor?, -HCU_1AA,HCU_1AA_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::TWDA_5, cchs2003_p::HCUC_1AA, cchs2005_p::HCUE_1AA, cchs2015_2016_p::PHC_020, cchs2017_2018_p::PHC_020, [HCU_1AA]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Has regular medical doctor,Do you have a regular medical doctor?, -HCU_1AA,HCU_1AA_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::TWDA_5, cchs2003_p::HCUC_1AA, cchs2005_p::HCUE_1AA, cchs2015_2016_p::PHC_020, cchs2017_2018_p::PHC_020, [HCU_1AA]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Has regular medical doctor,Do you have a regular medical doctor?, -HCU_1AA,HCU_1AA_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::TWDA_5, cchs2003_p::HCUC_1AA, cchs2005_p::HCUE_1AA, cchs2015_2016_p::PHC_020, cchs2017_2018_p::PHC_020, [HCU_1AA]",cat,NA::b,2,missing,missing,N/A,else,else,Has regular medical doctor,Do you have a regular medical doctor?, -HUIDCOG,HUIDCOG_cat6_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADCOG, cchs2003_p::HUICDCOG, cchs2005_p::HUIEDCOG, cchs2015_2016_p::HUIDVCOG, [HUIDCOG]",cat,1,6,No cognit prob,No cognition problems,N/A,1,No cognit prob,Cognition prob. - function code - (D),Cognition prob. - function code - (D),CCHS 2007 onwards uses cognition levels which coincide with HUI Mark 3 -HUIDCOG,HUIDCOG_cat6_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADCOG, cchs2003_p::HUICDCOG, cchs2005_p::HUIEDCOG, cchs2015_2016_p::HUIDVCOG, [HUIDCOG]",cat,2,6,Little difficult,Little difficulty,N/A,2,Little difficulty,Cognition prob. - function code - (D),Cognition prob. - function code - (D), -HUIDCOG,HUIDCOG_cat6_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADCOG, cchs2003_p::HUICDCOG, cchs2005_p::HUIEDCOG, cchs2015_2016_p::HUIDVCOG, [HUIDCOG]",cat,3,6,Some forgetful,Some forgetful,N/A,3,Some forgetful,Cognition prob. - function code - (D),Cognition prob. - function code - (D), -HUIDCOG,HUIDCOG_cat6_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADCOG, cchs2003_p::HUICDCOG, cchs2005_p::HUIEDCOG, cchs2015_2016_p::HUIDVCOG, [HUIDCOG]",cat,4,6,Forget/dif think,Forgetful/difficulty thinking,N/A,4,Forget/dif think,Cognition prob. - function code - (D),Cognition prob. - function code - (D), -HUIDCOG,HUIDCOG_cat6_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADCOG, cchs2003_p::HUICDCOG, cchs2005_p::HUIEDCOG, cchs2015_2016_p::HUIDVCOG, [HUIDCOG]",cat,5,6,Very forgetful,Very forgetful,N/A,5,Very forgetful,Cognition prob. - function code - (D),Cognition prob. - function code - (D), -HUIDCOG,HUIDCOG_cat6_6,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADCOG, cchs2003_p::HUICDCOG, cchs2005_p::HUIEDCOG, cchs2015_2016_p::HUIDVCOG, [HUIDCOG]",cat,6,6,Can't remember,Can't remember,N/A,6,Can't remember,Cognition prob. - function code - (D),Cognition prob. - function code - (D), -HUIDCOG,HUIDCOG_cat6_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADCOG, cchs2003_p::HUICDCOG, cchs2005_p::HUIEDCOG, cchs2015_2016_p::HUIDVCOG, [HUIDCOG]",cat,NA::a,6,not applicable,not applicable,N/A,96,not applicable,Cognition prob. - function code - (D),Cognition prob. - function code - (D), -HUIDCOG,HUIDCOG_cat6_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADCOG, cchs2003_p::HUICDCOG, cchs2005_p::HUIEDCOG, cchs2015_2016_p::HUIDVCOG, [HUIDCOG]",cat,NA::b,6,missing,missing,N/A,"[97,99]",don't know (97); refusal (98); not stated (99),Cognition prob. - function code - (D),Cognition prob. - function code - (D),"CCHS 2001, 2015-2018 does not include don't know (97) or refusal (98)" -HUIDCOG,HUIDCOG_cat6_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADCOG, cchs2003_p::HUICDCOG, cchs2005_p::HUIEDCOG, cchs2015_2016_p::HUIDVCOG, [HUIDCOG]",cat,NA::b,6,missing,missing,N/A,else,else,Cognition prob. - function code - (D),Cognition prob. - function code - (D), -HUIDEMO,HUIDEMO_cat5_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADEMO, cchs2003_p::HUICDEMO, cchs2005_p::HUIEDEMO, cchs2015_2016_p::HUIDVEMO, [HUIDEMO]",cat,1,5,Happy in life,Happy in life,N/A,1,Happy in life,Emotional problems - function code - (D),Emotional problems - function code - (D),CCHS 2007 onwards uses emotional levels which coincide with HUI Mark 3 -HUIDEMO,HUIDEMO_cat5_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADEMO, cchs2003_p::HUICDEMO, cchs2005_p::HUIEDEMO, cchs2015_2016_p::HUIDVEMO, [HUIDEMO]",cat,2,5,Somewhat happy,Somewhat happy,N/A,2,Somewhat happy,Emotional problems - function code - (D),Emotional problems - function code - (D), -HUIDEMO,HUIDEMO_cat5_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADEMO, cchs2003_p::HUICDEMO, cchs2005_p::HUIEDEMO, cchs2015_2016_p::HUIDVEMO, [HUIDEMO]",cat,3,5,Somewhat unhappy,Somewhat unhappy,N/A,3,Somewhat unhappy,Emotional problems - function code - (D),Emotional problems - function code - (D), -HUIDEMO,HUIDEMO_cat5_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADEMO, cchs2003_p::HUICDEMO, cchs2005_p::HUIEDEMO, cchs2015_2016_p::HUIDVEMO, [HUIDEMO]",cat,4,5,Very unhappy,Very unhappy,N/A,4,Very unhappy,Emotional problems - function code - (D),Emotional problems - function code - (D), -HUIDEMO,HUIDEMO_cat5_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADEMO, cchs2003_p::HUICDEMO, cchs2005_p::HUIEDEMO, cchs2015_2016_p::HUIDVEMO, [HUIDEMO]",cat,5,5,Life not worth,Life not worth,N/A,5,Life not worth,Emotional problems - function code - (D),Emotional problems - function code - (D), -HUIDEMO,HUIDEMO_cat5_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADEMO, cchs2003_p::HUICDEMO, cchs2005_p::HUIEDEMO, cchs2015_2016_p::HUIDVEMO, [HUIDEMO]",cat,NA::a,5,not applicable,not applicable,N/A,6,not applicable,Emotional problems - function code - (D),Emotional problems - function code - (D), -HUIDEMO,HUIDEMO_cat5_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADEMO, cchs2003_p::HUICDEMO, cchs2005_p::HUIEDEMO, cchs2015_2016_p::HUIDVEMO, [HUIDEMO]",cat,NA::b,5,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Emotional problems - function code - (D),Emotional problems - function code - (D),"CCHS 2001, 2015-2018 does not include don't know (7) or refusal (8)" -HUIDEMO,HUIDEMO_cat5_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADEMO, cchs2003_p::HUICDEMO, cchs2005_p::HUIEDEMO, cchs2015_2016_p::HUIDVEMO, [HUIDEMO]",cat,NA::b,5,missing,missing,N/A,else,else,Emotional problems - function code - (D),Emotional problems - function code - (D), -HUIDHSI,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,copy,N/A,HUI score,Health Utility Index (HUI3) - (D),N/A,"[-0.359,1]",Health Utility Index (HUI3) - (D),Health Utility Index (HUI3) - (D),Health Utility Index (HUI3) - (D), -HUIDHSI,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,NA::a,N/A,not applicable,not applicable,N/A,99.996,not applicable (99.996),Health Utility Index (HUI3) - (D),Health Utility Index (HUI3) - (D), -HUIDHSI,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,NA::b,N/A,missing,missing,N/A,"[99.997,99.999]","don't know (99.997), refusal (99.998), not stated (99.999)",Health Utility Index (HUI3) - (D),Health Utility Index (HUI3) - (D), -HUIDHSI,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,NA::b,N/A,missing,missing,N/A,else,else,Health Utility Index (HUI3) - (D),Health Utility Index (HUI3) - (D), -HUIDHSI_cat10,HUIDHSI_cat10_1,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,1,10,Decile 1,Decile 1,N/A,"[-0.359,-0.2231)",Decile 1,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat10,HUIDHSI_cat10_2,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,2,10,Decile 2,Decile 2,N/A,"[-0.2231,-0.0872)",Decile 2,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat10,HUIDHSI_cat10_3,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,3,10,Decile 3,Decile 3,N/A,"[-0.0872,0.0487)",Decile 3,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat10,HUIDHSI_cat10_4,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,4,10,Decile 4,Decile 4,N/A,"[0.0487,0.1846)",Decile 4,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat10,HUIDHSI_cat10_5,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,5,10,Decile 5,Decile 5,N/A,"[0.1846,0.3205)",Decile 5,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat10,HUIDHSI_cat10_6,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,6,10,Decile 6,Decile 6,N/A,"[0.3205,0.4564)",Decile 6,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat10,HUIDHSI_cat10_7,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,7,10,Decile 7,Decile 7,N/A,"[0.4564,0.5923)",Decile 7,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat10,HUIDHSI_cat10_8,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,8,10,Decile 8,Decile 8,N/A,"[0.5923,0.7282)",Decile 8,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat10,HUIDHSI_cat10_9,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,9,10,Decile 9,Decile 9,N/A,"[0.7282,0.8641)",Decile 9,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat10,HUIDHSI_cat10_10,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,10,10,Decile 10,Decile 10,N/A,"[0.8641,1]",Decile 10,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat10,HUIDHSI_cat10_NA::a,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,NA::a,10,not applicable,not applicable,N/A,99.996,not applicable (99.996),Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat10,HUIDHSI_cat10_NA::b,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,NA::b,10,missing,missing,N/A,"[99.997,99.999]","don't know (99.997), refusal (99.998), not stated (99.999)",Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat10,HUIDHSI_cat10_NA::b,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,NA::b,10,missing,missing,N/A,else,else,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_1,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,1,20,Group 1,Group 1,N/A,"[-0.359,-0.29105)",Group 1,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_2,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,2,20,Group 2,Group 2,N/A,"[-0.29105,-0.2231)",Group 2,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_3,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,3,20,Group 3,Group 3,N/A,"[-0.2231,-0.15515)",Group 3,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_4,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,4,20,Group 4,Group 4,N/A,"[-0.15515,-0.0872)",Group 4,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_5,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,5,20,Group 5,Group 5,N/A,"[-0.0872,-0.01925)",Group 5,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_6,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,6,20,Group 6,Group 6,N/A,"[-0.01925,0.0487)",Group 6,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_7,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,7,20,Group 7,Group 7,N/A,"[0.0487,0.11665)",Group 7,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_8,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,8,20,Group 8,Group 8,N/A,"[0.11665,0.1846)",Group 8,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_9,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,9,20,Group 9,Group 9,N/A,"[0.1846,0.25255)",Group 9,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_10,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,10,20,Group 10,Group 10,N/A,"[0.25255,0.3205)",Group 10,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_11,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,11,20,Group 11,Group 11,N/A,"[0.3205,0.38845)",Group 11,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_12,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,12,20,Group 12,Group 12,N/A,"[0.38845,0.4564)",Group 12,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_13,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,13,20,Group 13,Group 13,N/A,"[0.4564,0.52435)",Group 13,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_14,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,14,20,Group 14,Group 14,N/A,"[0.52435,0.5923)",Group 14,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_15,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,15,20,Group 15,Group 15,N/A,"[0.5923,0.66025)",Group 15,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_16,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,16,20,Group 16,Group 16,N/A,"[0.66025,0.7282)",Group 16,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_17,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,17,20,Group 17,Group 17,N/A,"[0.7282,0.79615)",Group 17,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_18,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,18,20,Group 18,Group 18,N/A,"[0.79615,0.8641)",Group 18,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_19,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,19,20,Group 19,Group 19,N/A,"[0.8641,0.93205)",Group 19,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_20,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,20,20,Group 20,Group 20,N/A,"[0.93205,1]",Group 20,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_NA::a,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,NA::a,20,not applicable,not applicable,N/A,99.996,not applicable (99.996),Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_NA::b,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,NA::b,20,missing,missing,N/A,"[99.997,99.999]","don't know (99.997), refusal (99.998), not stated (99.999)",Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat20,HUIDHSI_cat20_NA::b,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,NA::b,20,missing,missing,N/A,else,else,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_1,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,1,50,Group 1,Group 1,N/A,"[-0.359,-0.33182)",Group 1,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_2,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,2,50,Group 2,Group 2,N/A,"[-0.33182,-0.30464)",Group 2,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_3,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,3,50,Group 3,Group 3,N/A,"[-0.30464,-0.27746)",Group 3,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_4,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,4,50,Group 4,Group 4,N/A,"[-0.27746,-0.25028)",Group 4,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_5,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,5,50,Group 5,Group 5,N/A,"[-0.25028,-0.2231)",Group 5,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_6,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,6,50,Group 6,Group 6,N/A,"[-0.2231,-0.19592)",Group 6,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_7,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,7,50,Group 7,Group 7,N/A,"[-0.19592,-0.16874)",Group 7,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_8,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,8,50,Group 8,Group 8,N/A,"[-0.16874,-0.14156)",Group 8,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_9,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,9,50,Group 9,Group 9,N/A,"[-0.14156,-0.11438)",Group 9,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_10,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,10,50,Group 10,Group 10,N/A,"[-0.11438,-0.0872)",Group 10,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_11,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,11,50,Group 11,Group 11,N/A,"[-0.0872,-0.06002)",Group 11,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_12,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,12,50,Group 12,Group 12,N/A,"[-0.06002,-0.03284)",Group 12,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_13,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,13,50,Group 13,Group 13,N/A,"[-0.03284,-0.00566000000000004)",Group 13,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_14,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,14,50,Group 14,Group 14,N/A,"[-0.00566000000000004,0.02152)",Group 14,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_15,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,15,50,Group 15,Group 15,N/A,"[0.02152,0.0487)",Group 15,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_16,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,16,50,Group 16,Group 16,N/A,"[0.0487,0.07588)",Group 16,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_17,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,17,50,Group 17,Group 17,N/A,"[0.07588,0.10306)",Group 17,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_18,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,18,50,Group 18,Group 18,N/A,"[0.10306,0.13024)",Group 18,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_19,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,19,50,Group 19,Group 19,N/A,"[0.13024,0.15742)",Group 19,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_20,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,20,50,Group 20,Group 20,N/A,"[0.15742,0.1846)",Group 20,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_21,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,21,50,Group 21,Group 21,N/A,"[0.1846,0.21178)",Group 21,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_22,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,22,50,Group 22,Group 22,N/A,"[0.21178,0.23896)",Group 22,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_23,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,23,50,Group 23,Group 23,N/A,"[0.23896,0.26614)",Group 23,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_24,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,24,50,Group 24,Group 24,N/A,"[0.26614,0.29332)",Group 24,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_25,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,25,50,Group 25,Group 25,N/A,"[0.29332,0.3205)",Group 25,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_26,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,26,50,Group 26,Group 26,N/A,"[0.3205,0.34768)",Group 26,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_27,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,27,50,Group 27,Group 27,N/A,"[0.34768,0.37486)",Group 27,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_28,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,28,50,Group 28,Group 28,N/A,"[0.37486,0.40204)",Group 28,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_29,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,29,50,Group 29,Group 29,N/A,"[0.40204,0.42922)",Group 29,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_30,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,30,50,Group 30,Group 30,N/A,"[0.42922,0.4564)",Group 30,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_31,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,31,50,Group 31,Group 31,N/A,"[0.4564,0.48358)",Group 31,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_32,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,32,50,Group 32,Group 32,N/A,"[0.48358,0.51076)",Group 32,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_33,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,33,50,Group 33,Group 33,N/A,"[0.51076,0.53794)",Group 33,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_34,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,34,50,Group 34,Group 34,N/A,"[0.53794,0.56512)",Group 34,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_35,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,35,50,Group 35,Group 35,N/A,"[0.56512,0.5923)",Group 35,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_36,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,36,50,Group 36,Group 36,N/A,"[0.5923,0.61948)",Group 36,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_37,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,37,50,Group 37,Group 37,N/A,"[0.61948,0.64666)",Group 37,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_38,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,38,50,Group 38,Group 38,N/A,"[0.64666,0.67384)",Group 38,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_39,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,39,50,Group 39,Group 39,N/A,"[0.67384,0.70102)",Group 39,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_40,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,40,50,Group 40,Group 40,N/A,"[0.70102,0.7282)",Group 40,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_41,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,41,50,Group 41,Group 41,N/A,"[0.7282,0.75538)",Group 41,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_42,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,42,50,Group 42,Group 42,N/A,"[0.75538,0.78256)",Group 42,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_43,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,43,50,Group 43,Group 43,N/A,"[0.78256,0.80974)",Group 43,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_44,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,44,50,Group 44,Group 44,N/A,"[0.80974,0.83692)",Group 44,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_45,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,45,50,Group 45,Group 45,N/A,"[0.83692,0.8641)",Group 45,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_46,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,46,50,Group 46,Group 46,N/A,"[0.8641,0.89128)",Group 46,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_47,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,47,50,Group 47,Group 47,N/A,"[0.89128,0.91846)",Group 47,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_48,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,48,50,Group 48,Group 48,N/A,"[0.91846,0.94564)",Group 48,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_49,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,49,50,Group 49,Group 49,N/A,"[0.94564,0.97282)",Group 49,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_50,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,50,50,Group 50,Group 50,N/A,"[0.97282,1]",Group 50,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_NA::a,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,NA::a,50,not applicable,not applicable,N/A,99.996,not applicable (99.996),Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_NA::b,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,NA::b,50,missing,missing,N/A,"[99.997,99.999]","don't know (99.997), refusal (99.998), not stated (99.999)",Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIDHSI_cat50,HUIDHSI_cat50_NA::b,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, cchs2015_2016_p::HUIDVHSI, [HUIDHSI]",cont,NA::b,50,missing,missing,N/A,else,else,Categorical Health Utility Index (HUI3),Categorical Health Utility Index (HUI3), -HUIGDEX,HUIGDEX_cat3_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGDEX, cchs2003_p::HUICGDEX, cchs2005_p::HUIEGDEX, cchs2015_2016_p::HUIDGDEX, [HUIGDEX]",cat,1,3,No dext prob,No problems,N/A,1,No dext prob,"Dexterity trouble - function code (D, G)","Dexterity trouble - function code (D, G)", -HUIGDEX,HUIGDEX_cat3_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGDEX, cchs2003_p::HUICGDEX, cchs2005_p::HUIEGDEX, cchs2015_2016_p::HUIDGDEX, [HUIGDEX]",cat,2,3,Dext/no help,No help needed,N/A,2,Dext/no help,"Dexterity trouble - function code (D, G)","Dexterity trouble - function code (D, G)", -HUIGDEX,HUIGDEX_cat3_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGDEX, cchs2003_p::HUICGDEX, cchs2005_p::HUIEGDEX, cchs2015_2016_p::HUIDGDEX, [HUIGDEX]",cat,3,3,Dext/need help,Needs help,N/A,3,Dext/need help,"Dexterity trouble - function code (D, G)","Dexterity trouble - function code (D, G)", -HUIGDEX,HUIGDEX_cat3_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGDEX, cchs2003_p::HUICGDEX, cchs2005_p::HUIEGDEX, cchs2015_2016_p::HUIDGDEX, [HUIGDEX]",cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,"Dexterity trouble - function code (D, G)","Dexterity trouble - function code (D, G)", -HUIGDEX,HUIGDEX_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGDEX, cchs2003_p::HUICGDEX, cchs2005_p::HUIEGDEX, cchs2015_2016_p::HUIDGDEX, [HUIGDEX]",cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),"Dexterity trouble - function code (D, G)","Dexterity trouble - function code (D, G)",CCHS 2001 does not include don't know (7) or refusal (8) -HUIGDEX,HUIGDEX_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGDEX, cchs2003_p::HUICGDEX, cchs2005_p::HUIEGDEX, cchs2015_2016_p::HUIDGDEX, [HUIGDEX]",cat,NA::b,3,missing,missing,N/A,else,else,"Dexterity trouble - function code (D, G)","Dexterity trouble - function code (D, G)", -HUIGHER,HUIGHER_cat3_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGHER, cchs2003_p::HUICGHER, cchs2005_p::HUIEGHER, cchs2015_2016_p::HUIDGHER, [HUIGHER]",cat,1,3,No hearing prob,No hearing problem,N/A,1,No hearing prob,"Hearing problems - function code (D, G)","Hearing problems - function code (D, G)", -HUIGHER,HUIGHER_cat3_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGHER, cchs2003_p::HUICGHER, cchs2005_p::HUIEGHER, cchs2015_2016_p::HUIDGHER, [HUIGHER]",cat,2,3,Hear corrected,Hearing corrected,N/A,2,Hear corrected,"Hearing problems - function code (D, G)","Hearing problems - function code (D, G)", -HUIGHER,HUIGHER_cat3_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGHER, cchs2003_p::HUICGHER, cchs2005_p::HUIEGHER, cchs2015_2016_p::HUIDGHER, [HUIGHER]",cat,3,3,Hear n-corrected,Hearing not-corrected,N/A,3,Hear n-corrected,"Hearing problems - function code (D, G)","Hearing problems - function code (D, G)", -HUIGHER,HUIGHER_cat3_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGHER, cchs2003_p::HUICGHER, cchs2005_p::HUIEGHER, cchs2015_2016_p::HUIDGHER, [HUIGHER]",cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,"Hearing problems - function code (D, G)","Hearing problems - function code (D, G)", -HUIGHER,HUIGHER_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGHER, cchs2003_p::HUICGHER, cchs2005_p::HUIEGHER, cchs2015_2016_p::HUIDGHER, [HUIGHER]",cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),"Hearing problems - function code (D, G)","Hearing problems - function code (D, G)",CCHS 2001 does not include don't know (7) or refusal (8) -HUIGHER,HUIGHER_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGHER, cchs2003_p::HUICGHER, cchs2005_p::HUIEGHER, cchs2015_2016_p::HUIDGHER, [HUIGHER]",cat,NA::b,3,missing,missing,N/A,else,else,"Hearing problems - function code (D, G)","Hearing problems - function code (D, G)", -HUIGMOB,HUIGMOB_cat4_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGMOB, cchs2003_p::HUICGMOB, cchs2005_p::HUIEGMOB, cchs2015_2016_p::HUIDGMOB, [HUIGMOB]",cat,1,4,No mobil. Prob.,No mobil. Prob.,N/A,1,No mobil. Prob.,"Mobility trouble - function code (D, G)","Mobility trouble - function code (D, G)", -HUIGMOB,HUIGMOB_cat4_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGMOB, cchs2003_p::HUICGMOB, cchs2005_p::HUIEGMOB, cchs2015_2016_p::HUIDGMOB, [HUIGMOB]",cat,2,4,Mob-no aid req.,Mob-no aid req.,N/A,2,Mob-no aid req.,"Mobility trouble - function code (D, G)","Mobility trouble - function code (D, G)", -HUIGMOB,HUIGMOB_cat4_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGMOB, cchs2003_p::HUICGMOB, cchs2005_p::HUIEGMOB, cchs2015_2016_p::HUIDGMOB, [HUIGMOB]",cat,3,4,Need mech supp.,Need mech supp.,N/A,3,Need mech supp.,"Mobility trouble - function code (D, G)","Mobility trouble - function code (D, G)", -HUIGMOB,HUIGMOB_cat4_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGMOB, cchs2003_p::HUICGMOB, cchs2005_p::HUIEGMOB, cchs2015_2016_p::HUIDGMOB, [HUIGMOB]",cat,4,4,Can't walk,Can't walk,N/A,4,Can't walk,"Mobility trouble - function code (D, G)","Mobility trouble - function code (D, G)", -HUIGMOB,HUIGMOB_cat4_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGMOB, cchs2003_p::HUICGMOB, cchs2005_p::HUIEGMOB, cchs2015_2016_p::HUIDGMOB, [HUIGMOB]",cat,NA::a,4,not applicable,not applicable,N/A,6,not applicable,"Mobility trouble - function code (D, G)","Mobility trouble - function code (D, G)", -HUIGMOB,HUIGMOB_cat4_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGMOB, cchs2003_p::HUICGMOB, cchs2005_p::HUIEGMOB, cchs2015_2016_p::HUIDGMOB, [HUIGMOB]",cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),"Mobility trouble - function code (D, G)","Mobility trouble - function code (D, G)",CCHS 2001 does not include don't know (7) or refusal (8) -HUIGMOB,HUIGMOB_cat4_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGMOB, cchs2003_p::HUICGMOB, cchs2005_p::HUIEGMOB, cchs2015_2016_p::HUIDGMOB, [HUIGMOB]",cat,NA::b,4,missing,missing,N/A,else,else,"Mobility trouble - function code (D, G)","Mobility trouble - function code (D, G)", -HUIGSPE,HUIGSPE_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGSPE, cchs2003_p::HUICGSPE, cchs2005_p::HUIEGSPE, cchs2015_2016_p::HUIDGSPE, [HUIGSPE]",cat,1,2,No speech prob,No speech problem,N/A,1,No speech prob,"Speech trouble - function code - (D, G)","Speech trouble - function code - (D, G)", -HUIGSPE,HUIGSPE_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGSPE, cchs2003_p::HUICGSPE, cchs2005_p::HUIEGSPE, cchs2015_2016_p::HUIDGSPE, [HUIGSPE]",cat,2,2,Part/not underst,Part/not underst,N/A,2,Part/not underst,"Speech trouble - function code - (D, G)","Speech trouble - function code - (D, G)", -HUIGSPE,HUIGSPE_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGSPE, cchs2003_p::HUICGSPE, cchs2005_p::HUIEGSPE, cchs2015_2016_p::HUIDGSPE, [HUIGSPE]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,"Speech trouble - function code - (D, G)","Speech trouble - function code - (D, G)", -HUIGSPE,HUIGSPE_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGSPE, cchs2003_p::HUICGSPE, cchs2005_p::HUIEGSPE, cchs2015_2016_p::HUIDGSPE, [HUIGSPE]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),"Speech trouble - function code - (D, G)","Speech trouble - function code - (D, G)",CCHS 2001 does not include don't know (7) or refusal (8) -HUIGSPE,HUIGSPE_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGSPE, cchs2003_p::HUICGSPE, cchs2005_p::HUIEGSPE, cchs2015_2016_p::HUIDGSPE, [HUIGSPE]",cat,NA::b,2,missing,missing,N/A,else,else,"Speech trouble - function code - (D, G)","Speech trouble - function code - (D, G)", -HUIGVIS,HUIGVIS_cat5_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGVIS, cchs2003_p::HUICGVIS, cchs2005_p::HUIEGVIS, cchs2015_2016_p::HUIDGVIS, [HUIGVIS]",cat,1,5,No visual probl.,No visual problems,N/A,1,No visual probl.,"Vision trouble - function code - (D, G)","Vision trouble - function code - (D, G)", -HUIGVIS,HUIGVIS_cat5_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGVIS, cchs2003_p::HUICGVIS, cchs2005_p::HUIEGVIS, cchs2015_2016_p::HUIDGVIS, [HUIGVIS]",cat,2,5,Corr. by lenses,Corrected by lenses,N/A,2,Corr. by lenses,"Vision trouble - function code - (D, G)","Vision trouble - function code - (D, G)", -HUIGVIS,HUIGVIS_cat5_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGVIS, cchs2003_p::HUICGVIS, cchs2005_p::HUIEGVIS, cchs2015_2016_p::HUIDGVIS, [HUIGVIS]",cat,3,5,Hypermet/n corr,Hypermetropia/no correction,N/A,3,Hypermet/n corr,"Vision trouble - function code - (D, G)","Vision trouble - function code - (D, G)", -HUIGVIS,HUIGVIS_cat5_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGVIS, cchs2003_p::HUICGVIS, cchs2005_p::HUIEGVIS, cchs2015_2016_p::HUIDGVIS, [HUIGVIS]",cat,4,5,Myopia/n corr,Myopia/no correction,N/A,4,Myopia/n corr,"Vision trouble - function code - (D, G)","Vision trouble - function code - (D, G)", -HUIGVIS,HUIGVIS_cat5_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGVIS, cchs2003_p::HUICGVIS, cchs2005_p::HUIEGVIS, cchs2015_2016_p::HUIDGVIS, [HUIGVIS]",cat,5,5,Myopia & hypermet,Myopia & hypermetropia,N/A,5,Myopia & hypermet,"Vision trouble - function code - (D, G)","Vision trouble - function code - (D, G)", -HUIGVIS,HUIGVIS_cat5_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGVIS, cchs2003_p::HUICGVIS, cchs2005_p::HUIEGVIS, cchs2015_2016_p::HUIDGVIS, [HUIGVIS]",cat,NA::a,5,not applicable,not applicable,N/A,6,not applicable,"Vision trouble - function code - (D, G)","Vision trouble - function code - (D, G)", -HUIGVIS,HUIGVIS_cat5_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGVIS, cchs2003_p::HUICGVIS, cchs2005_p::HUIEGVIS, cchs2015_2016_p::HUIDGVIS, [HUIGVIS]",cat,NA::b,5,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),"Vision trouble - function code - (D, G)","Vision trouble - function code - (D, G)",CCHS 2001 does not include don't know (7) or refusal (8) -HUIGVIS,HUIGVIS_cat5_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIAGVIS, cchs2003_p::HUICGVIS, cchs2005_p::HUIEGVIS, cchs2015_2016_p::HUIDGVIS, [HUIGVIS]",cat,NA::b,5,missing,missing,N/A,else,else,"Vision trouble - function code - (D, G)","Vision trouble - function code - (D, G)", -HUPDPAD,HUPDPAD_cat5_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADPAD, cchs2003_p::HUICDPAD, cchs2005_p::HUIEDPAD, cchs2015_2016_p::HUIDVPAD, [HUPDPAD]",cat,1,5,No pain/discomf,No pain/discomf,N/A,1,No pain/discomf,Act. prevent/pain - function code - (D),Act. prevent/pain - function code - (D), -HUPDPAD,HUPDPAD_cat5_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADPAD, cchs2003_p::HUICDPAD, cchs2005_p::HUIEDPAD, cchs2015_2016_p::HUIDVPAD, [HUPDPAD]",cat,2,5,Doesn't prev act,Doesn't prev act,N/A,2,Doesn't prev act,Act. prevent/pain - function code - (D),Act. prevent/pain - function code - (D), -HUPDPAD,HUPDPAD_cat5_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADPAD, cchs2003_p::HUICDPAD, cchs2005_p::HUIEDPAD, cchs2015_2016_p::HUIDVPAD, [HUPDPAD]",cat,3,5,Prevents few act,Prevents few act,N/A,3,Prevents few act,Act. prevent/pain - function code - (D),Act. prevent/pain - function code - (D), -HUPDPAD,HUPDPAD_cat5_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADPAD, cchs2003_p::HUICDPAD, cchs2005_p::HUIEDPAD, cchs2015_2016_p::HUIDVPAD, [HUPDPAD]",cat,4,5,Prev. some act,Prev. some act,N/A,4,Prev. some act,Act. prevent/pain - function code - (D),Act. prevent/pain - function code - (D), -HUPDPAD,HUPDPAD_cat5_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADPAD, cchs2003_p::HUICDPAD, cchs2005_p::HUIEDPAD, cchs2015_2016_p::HUIDVPAD, [HUPDPAD]",cat,5,5,Prev. most act,Prev. most act,N/A,5,Prev. most act,Act. prevent/pain - function code - (D),Act. prevent/pain - function code - (D), -HUPDPAD,HUPDPAD_cat5_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADPAD, cchs2003_p::HUICDPAD, cchs2005_p::HUIEDPAD, cchs2015_2016_p::HUIDVPAD, [HUPDPAD]",cat,NA::a,5,not applicable,not applicable,N/A,6,not applicable,Act. prevent/pain - function code - (D),Act. prevent/pain - function code - (D), -HUPDPAD,HUPDPAD_cat5_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADPAD, cchs2003_p::HUICDPAD, cchs2005_p::HUIEDPAD, cchs2015_2016_p::HUIDVPAD, [HUPDPAD]",cat,NA::b,5,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Act. prevent/pain - function code - (D),Act. prevent/pain - function code - (D),CCHS 2001 does not include don't know (7) or refusal (8) -HUPDPAD,HUPDPAD_cat5_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p","cchs2001_p::HUIADPAD, cchs2003_p::HUICDPAD, cchs2005_p::HUIEDPAD, cchs2015_2016_p::HUIDVPAD, [HUPDPAD]",cat,NA::b,5,missing,missing,N/A,else,else,Act. prevent/pain - function code - (D),Act. prevent/pain - function code - (D), -HWTGBMI,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::HWTAGBMI, cchs2003_p::HWTCGBMI, cchs2005_p::HWTEGBMI, cchs2015_2016_p::HWTDGBMI, cchs2017_2018_p::HWTDGBMI, [HWTGBMI]",cont,copy,N/A,BMI,Body Mass Index,kg/m2,"[11.91,57.9]","BMI / self-report - (D,G)",BMI,"BMI / self-report - (D,G)","CCHS 2001 restricts BMI to ages 20-64. CCHS 2015-2016 uses adjusted BMI. Consider using using HWTGBMI_der for the most concistent BMI variable across all CCHS cycles. See documentation for BMI_fun() in derived variables for more details, or type ?BMI_fun in the console." -HWTGBMI,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGBMI, cchs2003_p::HWTCGBMI",cont,NA::a,N/A,not applicable,not applicable,kg/m2,999.6,Not applicable,BMI,"BMI / self-report - (D,G)","CCHS 2001 and 2003 codes not applicable and missing variables as 999.6 and 999.7-999.9 respectively, while CCHS 2005 onwards codes not applicable and missing variables as 999.96 and 999.7-999.99 respectively" -HWTGBMI,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGBMI, cchs2003_p::HWTCGBMI",cont,NA::b,N/A,missing,missing,kg/m2,"[999.7,999.9]",don't know (999.7); refusal (999.8); not stated (999.9),BMI,"BMI / self-report - (D,G)",Don't know (999.7) and refusal (999.8) not included in 2001 CCHS -HWTGBMI,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::HWTEGBMI, cchs2015_2016_p::HWTDGBMI, cchs2017_2018_p::HWTDGBMI, [HWTGBMI]",cont,NA::a,N/A,not applicable,not applicable,kg/m2,999.96,Not applicable,BMI,"BMI / self-report - (D,G)", -HWTGBMI,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::HWTEGBMI, cchs2015_2016_p::HWTDGBMI, cchs2017_2018_p::HWTDGBMI, [HWTGBMI]",cont,NA::b,N/A,missing,missing,kg/m2,"[999.97,999.99]",don't know (999.97); refusal (999.98); not stated (999.99),BMI,"BMI / self-report - (D,G)", -HWTGBMI,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::HWTAGBMI, cchs2003_p::HWTCGBMI, cchs2005_p::HWTEGBMI, cchs2015_2016_p::HWTDGBMI, cchs2017_2018_p::HWTDGBMI, [HWTGBMI]",cont,NA::b,N/A,missing,missing,kg/m2,else,else,BMI,"BMI / self-report - (D,G)", -HWTGBMI_der,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[HWTGHTM, HWTGWTK]",N/A,Func::bmi_fun,N/A,N/A,N/A,kg/m2,N/A,N/A,Derived BMI,Derived Body Mass Index,"BMI variable derived from the harmonized height and weight variables. See documentation for BMI_fun() in derived variables for more details, or type ?BMI_fun in the console." -HWTGBMI_der,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[HWTGHTM, HWTGWTK]",N/A,NA::b,N/A,missing,missing,kg/m2,N/A,N/A,Derived BMI,Derived Body Mass Index, -HWTGBMI_der_cat4,HWTGBMI_der_cat4N/A_Func::bmi_fun_cat,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[HWTGBMI_der],N/A,Func::bmi_fun_cat,N/A,N/A,N/A,N/A,N/A,N/A,Categorical BMI (int'l),Categorical body mass index (international standard), -HWTGBMI_der_cat4,HWTGBMI_der_cat4_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[HWTGBMI_der],N/A,1,4,Underweight,Underweight with BMI less than 18.5,kg/m2,1,Underweight,Categorical BMI (int'l),Categorical body mass index (international standard), -HWTGBMI_der_cat4,HWTGBMI_der_cat4_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[HWTGBMI_der],N/A,2,4,Normal weight,Normal weight with BMI between 18.5 and 25,kg/m2,2,Normal weight,Categorical BMI (int'l),Categorical body mass index (international standard), -HWTGBMI_der_cat4,HWTGBMI_der_cat4_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[HWTGBMI_der],N/A,3,4,Overweight,Overweight with BMI between 25 and 30,kg/m2,3,Overweight,Categorical BMI (int'l),Categorical body mass index (international standard), -HWTGBMI_der_cat4,HWTGBMI_der_cat4_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[HWTGBMI_der],N/A,4,4,Obese,Obese with BMI greater than 30,kg/m2,4,Obese,Categorical BMI (int'l),Categorical body mass index (international standard), -HWTGBMI_der_cat4,HWTGBMI_der_cat4_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[HWTGBMI_der],N/A,NA::a,4,not applicable,not applicable,kg/m2,NA::a,not applicable,Categorical BMI (int'l),Categorical body mass index (international standard), -HWTGBMI_der_cat4,HWTGBMI_der_cat4_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[HWTGBMI_der],N/A,NA::b,4,missing,missing,kg/m2,NA::b,missing,Categorical BMI (int'l),Categorical body mass index (international standard), -HWTGCOR,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[HWTDGCOR],N/A,copy,N/A,Adjusted BMI,Adjusted body mass index,kg/m2,"[14.23,56.72]",Adjusted BMI,Adjusted BMI,Adjusted body mass index, -HWTGCOR,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[HWTDGCOR],N/A,NA::a,N/A,not applicable,not applicable,kg/m2,999.96,Not applicable,Adjusted BMI,Adjusted body mass index, -HWTGCOR,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[HWTDGCOR],N/A,NA::b,N/A,missing,missing,kg/m2,"[999.97,999.99]",don't know (999.97); refusal (999.98); not stated (999.99),Adjusted BMI,Adjusted body mass index, -HWTGCOR,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[HWTDGCOR],N/A,NA::b,N/A,missing,missing,kg/m2,else,else,Adjusted BMI,Adjusted body mass index, -HWTGCOR_der,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, HWTGHTM, HWTGWTK]",N/A,Func::adjusted_bmi_fun,N/A,N/A,N/A,kg/m2,N/A,N/A,Derived adjusted BMI,Derived adjusted body mass index,"Adjusted BMI variable derived from the harmonized sex, height and weight variables. See documentation for adjusted_bmi_fun() in derived variables for more details, or type ?adjusted_bmi_fun in the console." -HWTGCOR_der,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX,HWTGHTM, HWTGWTK]",N/A,NA::b,N/A,missing,missing,kg/m2,N/A,N/A,Derived adjusted BMI,Derived adjusted body mass index, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.118,N/A,Height,converted height (3'8 IN - 44 inches),meters,1,3'8 IN - 44 inches,Height,Height,"2001 and 2003 CCHS use inches, values converted to meters to 3 decimal points" -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.143,N/A,Height,converted height (3'9 IN - 45 inches),meters,2,3'9 IN - 45 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.168,N/A,Height,converted height (3'10 IN - 46 inches),meters,3,3'10 IN - 46 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.194,N/A,Height,converted height (3'11 IN - 47 inches),meters,4,3'11 IN - 47 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.219,N/A,Height,converted height (4'0 IN - 48 inches),meters,5,4'0 IN - 48 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.245,N/A,Height,converted height (4'1 IN - 49 inches),meters,6,4'1 IN - 49 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.27,N/A,Height,converted height (4'2 IN - 50 inches),meters,7,4'2 IN - 50 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.295,N/A,Height,converted height (4'3 IN - 51 inches),meters,8,4'3 IN - 51 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.321,N/A,Height,converted height (4'4 IN - 52 inches),meters,9,4'4 IN - 52 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.346,N/A,Height,converted height (4'5 IN - 53 inches),meters,10,4'5 IN - 53 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.372,N/A,Height,converted height (4'6 IN - 54 inches),meters,11,4'6 IN - 54 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.397,N/A,Height,converted height (4'7 IN - 55 inches),meters,12,4'7 IN - 55 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.422,N/A,Height,converted height (4'8 IN - 56 inches),meters,13,4'8 IN - 56 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.448,N/A,Height,converted height (4'9 IN - 57 inches),meters,14,4'9 IN - 57 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.473,N/A,Height,converted height (4'10 IN - 58 inches),meters,15,4'10 IN - 58 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.499,N/A,Height,converted height (4'11 in - 59 inches),meters,16,4'11 in - 59 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.524,N/A,Height,converted height (5'0 IN - 60 inches),meters,17,5'0 IN - 60 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.549,N/A,Height,converted height (5'1 IN - 61 inches),meters,18,5'1 IN - 61 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.575,N/A,Height,converted height (5'2 IN - 62 inches),meters,19,5'2 IN - 62 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.6,N/A,Height,converted height (5'3 IN - 63 inches),meters,20,5'3 IN - 63 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.626,N/A,Height,converted height (5'4 IN - 64 inches),meters,21,5'4 IN - 64 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.651,N/A,Height,converted height (5'5 IN - 65 inches),meters,22,5'5 IN - 65 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.676,N/A,Height,converted height (5'6 IN - 66 inches),meters,23,5'6 IN - 66 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.702,N/A,Height,converted height (5'7 IN - 67 inches),meters,24,5'7 IN - 67 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.727,N/A,Height,converted height (5'8 IN - 68 inches),meters,25,5'8 IN - 68 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.753,N/A,Height,converted height (5'9 IN - 69 inches),meters,26,5'9 IN - 69 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.778,N/A,Height,converted height (5'10 IN - 70 inches),meters,27,5'10 IN - 70 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.803,N/A,Height,converted height (5'11 IN - 71 inches),meters,28,5'11 IN - 71 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.829,N/A,Height,converted height (6'0 IN - 72 inches),meters,29,6'0 IN - 72 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.854,N/A,Height,converted height (6'1 IN - 73 inches),meters,30,6'1 IN - 73 inches,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,1.93,N/A,Height,converted height (6'2 IN+ - 74+ inches),meters,31,6'2 IN+ - 74+ inches,Height,Height,74+ inches converted to 76 inches -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,NA::a,N/A,not applicable,not applicable,meters,96,not applicable,Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,NA::b,N/A,missing,missing,meters,99,not stated (99),Height,Height, -HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",cat,NA::b,N/A,missing,missing,meters,else,else,Height,Height, -HWTGHTM,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::HWTEGHTM, cchs2015_2016_p::HWTDGHTM, cchs2017_2018_p::HWTDGHTM, [HWTGHTM]",cont,copy,N/A,Height,Height,meters,"[0.914,2.134]",Height,Height,"Height (metres)/self-reported - (D,G)",Height is a reported in meters from 2005 CCHS onwards -HWTGHTM,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::HWTEGHTM, cchs2015_2016_p::HWTDGHTM, cchs2017_2018_p::HWTDGHTM, [HWTGHTM]",cont,NA::a,N/A,not applicable,not applicable,meters,9.996,not applicable,Height,"Height (metres)/self-reported - (D,G)", -HWTGHTM,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::HWTEGHTM, cchs2015_2016_p::HWTDGHTM, cchs2017_2018_p::HWTDGHTM, [HWTGHTM]",cont,NA::b,N/A,missing,missing,meters,"[9.997,9.999]","don't know (9.997), refusal (9.998), not stated (9.999)",Height,"Height (metres)/self-reported - (D,G)", -HWTGHTM,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::HWTEGHTM, cchs2015_2016_p::HWTDGHTM, cchs2017_2018_p::HWTDGHTM, [HWTGHTM]",cont,NA::b,N/A,missing,missing,meters,else,else,Height,"Height (metres)/self-reported - (D,G)", -HWTGWTK,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::HWTAGWTK, cchs2003_p::HWTCGWTK, cchs2005_p::HWTEGWTK, cchs2015_2016_p::HWTDGWTK, cchs2017_2018_p::HWTDGWTK, [HWTGWTK]",cont,copy,N/A,Weight,Weight - kilograms,kg,"[27.0,135.0]","Weight - kilograms (D, G)",Weight,"Weight - kilograms (D, G)", -HWTGWTK,N/A,cont,"cchs2001_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::HWTAGWTK, cchs2005_p::HWTEGWTK, cchs2015_2016_p::HWTDGWTK, cchs2017_2018_p::HWTDGWTK, [HWTGWTK]",cont,NA::a,N/A,not applicable,not applicable,kg,999.96,not applicable,Weight,"Weight - kilograms (D, G)", -HWTGWTK,N/A,cont,"cchs2001_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::HWTAGWTK, cchs2005_p::HWTEGWTK, cchs2015_2016_p::HWTDGWTK, cchs2017_2018_p::HWTDGWTK, [HWTGWTK]",cont,NA::b,N/A,missing,missing,kg,"[999.97,999.99]",don't know (999.97); refusal (999.98); not stated (999.99),Weight,"Weight - kilograms (D, G)", -HWTGWTK,N/A,cont,cchs2003_p,cchs2003_p::HWTCGWTK,cont,NA::a,N/A,not applicable,not applicable,kg,996,not applicable,Weight,"Weight - kilograms (D, G)", -HWTGWTK,N/A,cont,cchs2003_p,cchs2003_p::HWTCGWTK,cont,NA::b,N/A,missing,missing,kg,"[997,999]",don't know (997); refusal (998); not stated (999),Weight,"Weight - kilograms (D, G)", -HWTGWTK,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::HWTAGWTK, cchs2003_p::HWTCGWTK, cchs2005_p::HWTEGWTK, cchs2015_2016_p::HWTDGWTK, cchs2017_2018_p::HWTDGWTK, [HWTGWTK]",cont,NA::b,N/A,missing,missing,kg,else,else,Weight,"Weight - kilograms (D, G)", -id_year,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[data_name, ADM_RNO]",N/A,id_from::unite,N/A,N/A,N/A,N/A,N/A,N/A,Unique ID,Unique ID,Variable appends data_name to sequential random number to generate a unique identifier for all respondents -immigration_der,immigration_derN/A_Func::immigration_fun,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[SDCFIMM, SDCGCBG, SDCGCGT, SDCGRES]",N/A,Func::immigration_fun,N/A,N/A,N/A,N/A,N/A,N/A,Immigration category,Immigration category,"Derived from SDCFIMM, SDCGCBG, SDCGCGT, SDCGRES" -immigration_der,immigration_der_cat6_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[SDCFIMM, SDCGCBG, SDCGCGT, SDCGRES]",N/A,1,6,White Canada-born,White Canada-born,N/A,1,White Canada-born,Immigration category,Immigration category, -immigration_der,immigration_der_cat6_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[SDCFIMM, SDCGCBG, SDCGCGT, SDCGRES]",N/A,2,6,Non-white Canadian born,Non-white Canadian born,N/A,2,Non-white Canadian born,Immigration category,Immigration category, -immigration_der,immigration_der_cat6_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[SDCFIMM, SDCGCBG, SDCGCGT, SDCGRES]",N/A,3,6,White immigrant born outside of Canada (0-9 years in Canada),White immigrant born outside of Canada (0-9 years in Canada),N/A,3,White immigrant born outside of Canada (0-9 years in Canada),Immigration category,Immigration category, -immigration_der,immigration_der_cat6_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[SDCFIMM, SDCGCBG, SDCGCGT, SDCGRES]",N/A,4,6,Non-white immigrant born outside of Canada (0-9 years in Canada),Non-white immigrant born outside of Canada (0-9 years in Canada),N/A,4,Non-white immigrant born outside of Canada (0-9 years in Canada),Immigration category,Immigration category, -immigration_der,immigration_der_cat6_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[SDCFIMM, SDCGCBG, SDCGCGT, SDCGRES]",N/A,5,6,White immigrant born outside of Canada (10+ years in Canada),White immigrant born outside of Canada (10+ years in Canada),N/A,5,White immigrant born outside of Canada (10+ years in Canada),Immigration category,Immigration category, -immigration_der,immigration_der_cat6_6,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[SDCFIMM, SDCGCBG, SDCGCGT, SDCGRES]",N/A,6,6,Non-white immigrant born outside of Canada (10+ years in Canada),Non-white immigrant born outside of Canada (10+ years in Canada),N/A,6,Non-white immigrant born outside of Canada (10+ years in Canada),Immigration category,Immigration category, -immigration_der,immigration_der_cat6_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[SDCFIMM, SDCGCBG, SDCGCGT, SDCGRES]",N/A,NA::a,6,not applicable,not applicable,N/A,NA::a,not applicable,Immigration category,Immigration category, -immigration_der,immigration_der_cat6_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[SDCFIMM, SDCGCBG, SDCGCGT, SDCGRES]",N/A,NA::b,6,missing,missing,N/A,NA::b,missing,Immigration category,Immigration category, -INCDRCA,INCDRCA_cat10_1,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRCA, cchs2015_2016_p::INCDVRCA, cchs2017_2018_p::INCDVRCA, [INCDRCA]",cat,1,10,Decile 1,Decile 1,N/A,1,Decile 1,Household income distribution,Household income distribution - (D), -INCDRCA,INCDRCA_cat10_2,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRCA, cchs2015_2016_p::INCDVRCA, cchs2017_2018_p::INCDVRCA, [INCDRCA]",cat,2,10,Decile 2,Decile 2,N/A,2,Decile 2,Household income distribution,Household income distribution - (D), -INCDRCA,INCDRCA_cat10_3,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRCA, cchs2015_2016_p::INCDVRCA, cchs2017_2018_p::INCDVRCA, [INCDRCA]",cat,3,10,Decile 3,Decile 3,N/A,3,Decile 3,Household income distribution,Household income distribution - (D), -INCDRCA,INCDRCA_cat10_4,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRCA, cchs2015_2016_p::INCDVRCA, cchs2017_2018_p::INCDVRCA, [INCDRCA]",cat,4,10,Decile 4,Decile 4,N/A,4,Decile 4,Household income distribution,Household income distribution - (D), -INCDRCA,INCDRCA_cat10_5,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRCA, cchs2015_2016_p::INCDVRCA, cchs2017_2018_p::INCDVRCA, [INCDRCA]",cat,5,10,Decile 5,Decile 5,N/A,5,Decile 5,Household income distribution,Household income distribution - (D), -INCDRCA,INCDRCA_cat10_6,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRCA, cchs2015_2016_p::INCDVRCA, cchs2017_2018_p::INCDVRCA, [INCDRCA]",cat,6,10,Decile 6,Decile 6,N/A,6,Decile 6,Household income distribution,Household income distribution - (D), -INCDRCA,INCDRCA_cat10_7,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRCA, cchs2015_2016_p::INCDVRCA, cchs2017_2018_p::INCDVRCA, [INCDRCA]",cat,7,10,Decile 7,Decile 7,N/A,7,Decile 7,Household income distribution,Household income distribution - (D), -INCDRCA,INCDRCA_cat10_8,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRCA, cchs2015_2016_p::INCDVRCA, cchs2017_2018_p::INCDVRCA, [INCDRCA]",cat,8,10,Decile 8,Decile 8,N/A,8,Decile 8,Household income distribution,Household income distribution - (D), -INCDRCA,INCDRCA_cat10_9,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRCA, cchs2015_2016_p::INCDVRCA, cchs2017_2018_p::INCDVRCA, [INCDRCA]",cat,9,10,Decile 9,Decile 9,N/A,9,Decile 9,Household income distribution,Household income distribution - (D), -INCDRCA,INCDRCA_cat10_10,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRCA, cchs2015_2016_p::INCDVRCA, cchs2017_2018_p::INCDVRCA, [INCDRCA]",cat,10,10,Decile 10,Decile 10,N/A,10,Decile 10,Household income distribution,Household income distribution - (D), -INCDRCA,INCDRCA_cat10_NA::a,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRCA, cchs2015_2016_p::INCDVRCA, cchs2017_2018_p::INCDVRCA, [INCDRCA]",cat,NA::a,10,not applicable,not applicable,N/A,96,not applicable,Household income distribution,Household income distribution - (D), -INCDRCA,INCDRCA_cat10_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRCA, cchs2015_2016_p::INCDVRCA, cchs2017_2018_p::INCDVRCA, [INCDRCA]",cat,NA::b,10,missing,missing,N/A,"[97,99]",don't know (97); refusal (98); not stated (99),Household income distribution,Household income distribution - (D), -INCDRCA,INCDRCA_cat10_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRCA, cchs2015_2016_p::INCDVRCA, cchs2017_2018_p::INCDVRCA, [INCDRCA]",cat,NA::b,10,missing,missing,N/A,else,else,Household income distribution,Household income distribution - (D), -INCDRPR,INCDRPR_cat10_1,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRPR, cchs2015_2016_p::INCDVRPR, cchs2017_2018_p::INCDVRPR, [INCDRPR]",cat,1,10,Decile 1,Decile 1,N/A,1,Decile 1,Household income distribution provincial level,household inc. distribution-prov. level - (D), -INCDRPR,INCDRPR_cat10_2,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRPR, cchs2015_2016_p::INCDVRPR, cchs2017_2018_p::INCDVRPR, [INCDRPR]",cat,2,10,Decile 2,Decile 2,N/A,2,Decile 2,Household income distribution provincial level,household inc. distribution-prov. level - (D), -INCDRPR,INCDRPR_cat10_3,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRPR, cchs2015_2016_p::INCDVRPR, cchs2017_2018_p::INCDVRPR, [INCDRPR]",cat,3,10,Decile 3,Decile 3,N/A,3,Decile 3,Household income distribution provincial level,household inc. distribution-prov. level - (D), -INCDRPR,INCDRPR_cat10_4,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRPR, cchs2015_2016_p::INCDVRPR, cchs2017_2018_p::INCDVRPR, [INCDRPR]",cat,4,10,Decile 4,Decile 4,N/A,4,Decile 4,Household income distribution provincial level,household inc. distribution-prov. level - (D), -INCDRPR,INCDRPR_cat10_5,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRPR, cchs2015_2016_p::INCDVRPR, cchs2017_2018_p::INCDVRPR, [INCDRPR]",cat,5,10,Decile 5,Decile 5,N/A,5,Decile 5,Household income distribution provincial level,household inc. distribution-prov. level - (D), -INCDRPR,INCDRPR_cat10_6,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRPR, cchs2015_2016_p::INCDVRPR, cchs2017_2018_p::INCDVRPR, [INCDRPR]",cat,6,10,Decile 6,Decile 6,N/A,6,Decile 6,Household income distribution provincial level,household inc. distribution-prov. level - (D), -INCDRPR,INCDRPR_cat10_7,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRPR, cchs2015_2016_p::INCDVRPR, cchs2017_2018_p::INCDVRPR, [INCDRPR]",cat,7,10,Decile 7,Decile 7,N/A,7,Decile 7,Household income distribution provincial level,household inc. distribution-prov. level - (D), -INCDRPR,INCDRPR_cat10_8,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRPR, cchs2015_2016_p::INCDVRPR, cchs2017_2018_p::INCDVRPR, [INCDRPR]",cat,8,10,Decile 8,Decile 8,N/A,8,Decile 8,Household income distribution provincial level,household inc. distribution-prov. level - (D), -INCDRPR,INCDRPR_cat10_9,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRPR, cchs2015_2016_p::INCDVRPR, cchs2017_2018_p::INCDVRPR, [INCDRPR]",cat,9,10,Decile 9,Decile 9,N/A,9,Decile 9,Household income distribution provincial level,household inc. distribution-prov. level - (D), -INCDRPR,INCDRPR_cat10_10,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRPR, cchs2015_2016_p::INCDVRPR, cchs2017_2018_p::INCDVRPR, [INCDRPR]",cat,10,10,Decile 10,Decile 10,N/A,10,Decile 10,Household income distribution provincial level,household inc. distribution-prov. level - (D), -INCDRPR,INCDRPR_cat10_NA::a,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRPR, cchs2015_2016_p::INCDVRPR, cchs2017_2018_p::INCDVRPR, [INCDRPR]",cat,NA::a,10,not applicable,not applicable,N/A,96,not applicable,Household income distribution provincial level,household inc. distribution-prov. level - (D), -INCDRPR,INCDRPR_cat10_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRPR, cchs2015_2016_p::INCDVRPR, cchs2017_2018_p::INCDVRPR, [INCDRPR]",cat,NA::b,10,missing,missing,N/A,"[97,99]",don't know (97); refusal (98); not stated (99),Household income distribution provincial level,household inc. distribution-prov. level - (D), -INCDRPR,INCDRPR_cat10_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRPR, cchs2015_2016_p::INCDVRPR, cchs2017_2018_p::INCDVRPR, [INCDRPR]",cat,NA::b,10,missing,missing,N/A,else,else,Household income distribution provincial level,household inc. distribution-prov. level - (D), -INCDRRS,INCDRRS_cat10_1,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRRS, cchs2015_2016_p::INCDVRRS, cchs2017_2018_p::INCDVRRS, [INCDRRS]",cat,1,10,Decile 1,Decile 1,N/A,1,Decile 1,Household income distribution health region level,household inc. distribution- hr level - (D), -INCDRRS,INCDRRS_cat10_2,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRRS, cchs2015_2016_p::INCDVRRS, cchs2017_2018_p::INCDVRRS, [INCDRRS]",cat,2,10,Decile 2,Decile 2,N/A,2,Decile 2,Household income distribution health region level,household inc. distribution- hr level - (D), -INCDRRS,INCDRRS_cat10_3,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRRS, cchs2015_2016_p::INCDVRRS, cchs2017_2018_p::INCDVRRS, [INCDRRS]",cat,3,10,Decile 3,Decile 3,N/A,3,Decile 3,Household income distribution health region level,household inc. distribution- hr level - (D), -INCDRRS,INCDRRS_cat10_4,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRRS, cchs2015_2016_p::INCDVRRS, cchs2017_2018_p::INCDVRRS, [INCDRRS]",cat,4,10,Decile 4,Decile 4,N/A,4,Decile 4,Household income distribution health region level,household inc. distribution- hr level - (D), -INCDRRS,INCDRRS_cat10_5,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRRS, cchs2015_2016_p::INCDVRRS, cchs2017_2018_p::INCDVRRS, [INCDRRS]",cat,5,10,Decile 5,Decile 5,N/A,5,Decile 5,Household income distribution health region level,household inc. distribution- hr level - (D), -INCDRRS,INCDRRS_cat10_6,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRRS, cchs2015_2016_p::INCDVRRS, cchs2017_2018_p::INCDVRRS, [INCDRRS]",cat,6,10,Decile 6,Decile 6,N/A,6,Decile 6,Household income distribution health region level,household inc. distribution- hr level - (D), -INCDRRS,INCDRRS_cat10_7,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRRS, cchs2015_2016_p::INCDVRRS, cchs2017_2018_p::INCDVRRS, [INCDRRS]",cat,7,10,Decile 7,Decile 7,N/A,7,Decile 7,Household income distribution health region level,household inc. distribution- hr level - (D), -INCDRRS,INCDRRS_cat10_8,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRRS, cchs2015_2016_p::INCDVRRS, cchs2017_2018_p::INCDVRRS, [INCDRRS]",cat,8,10,Decile 8,Decile 8,N/A,8,Decile 8,Household income distribution health region level,household inc. distribution- hr level - (D), -INCDRRS,INCDRRS_cat10_9,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRRS, cchs2015_2016_p::INCDVRRS, cchs2017_2018_p::INCDVRRS, [INCDRRS]",cat,9,10,Decile 9,Decile 9,N/A,9,Decile 9,Household income distribution health region level,household inc. distribution- hr level - (D), -INCDRRS,INCDRRS_cat10_10,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRRS, cchs2015_2016_p::INCDVRRS, cchs2017_2018_p::INCDVRRS, [INCDRRS]",cat,10,10,Decile 10,Decile 10,N/A,10,Decile 10,Household income distribution health region level,household inc. distribution- hr level - (D), -INCDRRS,INCDRRS_cat10_NA::a,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRRS, cchs2015_2016_p::INCDVRRS, cchs2017_2018_p::INCDVRRS, [INCDRRS]",cat,NA::a,10,not applicable,not applicable,N/A,96,not applicable,Household income distribution health region level,household inc. distribution- hr level - (D), -INCDRRS,INCDRRS_cat10_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRRS, cchs2015_2016_p::INCDVRRS, cchs2017_2018_p::INCDVRRS, [INCDRRS]",cat,NA::b,10,missing,missing,N/A,"[97,99]",don't know (97); refusal (98); not stated (99),Household income distribution health region level,household inc. distribution- hr level - (D), -INCDRRS,INCDRRS_cat10_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::INCEDRRS, cchs2015_2016_p::INCDVRRS, cchs2017_2018_p::INCDVRRS, [INCDRRS]",cat,NA::b,10,missing,missing,N/A,else,else,Household income distribution health region level,household inc. distribution- hr level - (D), -INCGHH_A,INCGHH_A_cat6_1,cat,cchs2001_p,cchs2001_p::INCAGHH,cat,1,6,No income,No income,$/year,1,No income,Household income,"Total household income from all sources (D, G)","CCHS 2001 classifies no income and less than $15,000 as separate categories" -INCGHH_A,INCGHH_A_cat6_2,cat,cchs2001_p,cchs2001_p::INCAGHH,cat,2,6,"Less than $15,000","Less than $15,000",$/year,2,"Less than $15,000",Household income,"Total household income from all sources (D, G)", -INCGHH_A,INCGHH_A_cat6_3,cat,cchs2001_p,cchs2001_p::INCAGHH,cat,3,6,"$15,000-29,999","$15,000-29,999",$/year,3,"$15,000-29,999",Household income,"Total household income from all sources (D, G)", -INCGHH_A,INCGHH_A_cat6_4,cat,cchs2001_p,cchs2001_p::INCAGHH,cat,4,6,"$30,000-$49,999","$30,000-$49,999",$/year,4,"$30,000-$49,999",Household income,"Total household income from all sources (D, G)", -INCGHH_A,INCGHH_A_cat6_5,cat,cchs2001_p,cchs2001_p::INCAGHH,cat,5,6,"$50,000-$79,999","$50,000-$79,999",$/year,5,"$50,000-$79,999",Household income,"Total household income from all sources (D, G)", -INCGHH_A,INCGHH_A_cat6_6,cat,cchs2001_p,cchs2001_p::INCAGHH,cat,6,6,"$80,000 or more","$80,000 or more",$/year,6,"$80,000 or more",Household income,"Total household income from all sources (D, G)", -INCGHH_A,INCGHH_A_cat6_NA::a,cat,cchs2001_p,cchs2001_p::INCAGHH,cat,NA::a,6,not applicable,not applicable,$/year,96,not applicable,Household income,"Total household income from all sources (D, G)", -INCGHH_A,INCGHH_A_cat6_NA::b,cat,cchs2001_p,cchs2001_p::INCAGHH,cat,NA::b,6,missing,missing,$/year,"[97,99]","don't know (97), refusal (98), not stated (99)",Household income,"Total household income from all sources (D, G)", -INCGHH_A,INCGHH_A_cat6_NA::b,cat,cchs2001_p,cchs2001_p::INCAGHH,cat,NA::b,6,missing,missing,$/year,else,else,Household income,"Total household income from all sources (D, G)", -INCGHH_B,INCGHH_B_cat5_1,cat,"cchs2003_p, cchs2005_p","cchs2003_p::INCCGHH, cchs2005_p::INCEGHH",cat,1,5,"No income or less than $15,000","No income or less than $15,000",$/year,1,"No income or less than $15,000",Household income,"Total household income from all sources (D, G)","CCHS 2003 and 2005 classifies no income and less than $15,000 as one category" -INCGHH_B,INCGHH_B_cat5_2,cat,"cchs2003_p, cchs2005_p","cchs2003_p::INCCGHH, cchs2005_p::INCEGHH",cat,2,5,"$15,000-29,999","$15,000-29,999",$/year,2,"$15,000-29,999",Household income,"Total household income from all sources (D, G)", -INCGHH_B,INCGHH_B_cat5_3,cat,"cchs2003_p, cchs2005_p","cchs2003_p::INCCGHH, cchs2005_p::INCEGHH",cat,3,5,"$30,000-$49,999","$30,000-$49,999",$/year,3,"$30,000-$49,999",Household income,"Total household income from all sources (D, G)", -INCGHH_B,INCGHH_B_cat5_4,cat,"cchs2003_p, cchs2005_p","cchs2003_p::INCCGHH, cchs2005_p::INCEGHH",cat,4,5,"$50,000-$79,999","$50,000-$79,999",$/year,4,"$50,000-$79,999",Household income,"Total household income from all sources (D, G)", -INCGHH_B,INCGHH_B_cat5_5,cat,"cchs2003_p, cchs2005_p","cchs2003_p::INCCGHH, cchs2005_p::INCEGHH",cat,5,5,"$80,000 or more","$80,000 or more",$/year,5,"$80,000 or more",Household income,"Total household income from all sources (D, G)", -INCGHH_B,INCGHH_B_cat5_NA::a,cat,"cchs2003_p, cchs2005_p","cchs2003_p::INCCGHH, cchs2005_p::INCEGHH",cat,NA::a,5,not applicable,not applicable,$/year,6,not applicable,Household income,"Total household income from all sources (D, G)", -INCGHH_B,INCGHH_B_cat5_NA::b,cat,"cchs2003_p, cchs2005_p","cchs2003_p::INCCGHH, cchs2005_p::INCEGHH",cat,NA::b,5,missing,missing,$/year,"[7,9]","don't know (7), refusal (8), not stated (9)",Household income,"Total household income from all sources (D, G)", -INCGHH_B,INCGHH_B_cat5_NA::b,cat,"cchs2003_p, cchs2005_p","cchs2003_p::INCCGHH, cchs2005_p::INCEGHH",cat,NA::b,5,missing,missing,$/year,else,else,Household income,"Total household income from all sources (D, G)", -INCGHH_C,INCGHH_C_cat5_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGHH, cchs2017_2018_p::INCDGHH, [INCGHH]",cat,1,5,"No income or less than $20,000","No income or less than $20,000",$/year,1,"No income or less than $20,000",Household income,"Total household income from all sources (D, G)", -INCGHH_C,INCGHH_C_cat5_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGHH, cchs2017_2018_p::INCDGHH, [INCGHH]",cat,2,5,"$20,000-39,999","$20,000-39,999",$/year,2,"$20,000-39,999",Household income,"Total household income from all sources (D, G)", -INCGHH_C,INCGHH_C_cat5_3,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGHH, cchs2017_2018_p::INCDGHH, [INCGHH]",cat,3,5,"$40,000-$59,999","$40,000-$59,999",$/year,3,"$40,000-$59,999",Household income,"Total household income from all sources (D, G)", -INCGHH_C,INCGHH_C_cat5_4,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGHH, cchs2017_2018_p::INCDGHH, [INCGHH]",cat,4,5,"$60,000-$79,999","$60,000-$79,999",$/year,4,"$60,000-$79,999",Household income,"Total household income from all sources (D, G)", -INCGHH_C,INCGHH_C_cat5_5,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGHH, cchs2017_2018_p::INCDGHH, [INCGHH]",cat,5,5,"$80,000 or more","$80,000 or more",$/year,5,"$80,000 or more",Household income,"Total household income from all sources (D, G)", -INCGHH_C,INCGHH_C_cat5_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGHH, cchs2017_2018_p::INCDGHH, [INCGHH]",cat,NA::a,5,not applicable,not applicable,$/year,6,not applicable,Household income,"Total household income from all sources (D, G)", -INCGHH_C,INCGHH_C_cat5_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGHH, cchs2017_2018_p::INCDGHH, [INCGHH]",cat,NA::b,5,missing,missing,$/year,"[7,9]","don't know (7), refusal (8), not stated (9)",Household income,"Total household income from all sources (D, G)", -INCGHH_C,INCGHH_C_cat5_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGHH, cchs2017_2018_p::INCDGHH, [INCGHH]",cat,NA::b,5,missing,missing,$/year,else,else,Household income,"Total household income from all sources (D, G)", -INCGHH_cont,N/A,cont,cchs2001_p,cchs2001_p::INCAGHH,cat,7500,N/A,No income,No income,$/year,1,No income,Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,cchs2001_p,cchs2001_p::INCAGHH,cat,7500,N/A,"Less than $15,000","Less than $15,000",$/year,2,"Less than $15,000",Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,cchs2001_p,cchs2001_p::INCAGHH,cat,22500,N/A,"$15,000-29,999","$15,000-29,999",$/year,3,"$15,000-29,999",Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,cchs2001_p,cchs2001_p::INCAGHH,cat,40000,N/A,"$30,000-$49,999","$30,000-$49,999",$/year,4,"$30,000-$49,999",Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,cchs2001_p,cchs2001_p::INCAGHH,cat,60000,N/A,"$50,000-$79,999","$50,000-$79,999",$/year,5,"$50,000-$79,999",Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,cchs2001_p,cchs2001_p::INCAGHH,cat,100000,N/A,"$80,000 or more","$80,000 or more",$/year,6,"$80,000 or more",Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,cchs2001_p,cchs2001_p::INCAGHH,cat,NA::a,N/A,not applicable,not applicable,$/year,96,not applicable,Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,cchs2001_p,cchs2001_p::INCAGHH,cat,NA::b,N/A,missing,missing,$/year,"[97,99]","don't know (97), refusal (98), not stated (99)",Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,cchs2001_p,cchs2001_p::INCAGHH,cat,NA::b,N/A,missing,missing,$/year,else,else,Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,"cchs2003_p, cchs2005_p","cchs2003_p::INCCGHH, cchs2005_p::INCEGHH",cat,7500,N/A,"No income or less than $15,000","No income or less than $15,000",$/year,1,"No income or less than $15,000",Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,"cchs2003_p, cchs2005_p","cchs2003_p::INCCGHH, cchs2005_p::INCEGHH",cat,22500,N/A,"$15,000-29,999","$15,000-29,999",$/year,2,"$15,000-29,999",Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,"cchs2003_p, cchs2005_p","cchs2003_p::INCCGHH, cchs2005_p::INCEGHH",cat,40000,N/A,"$30,000-$49,999","$30,000-$49,999",$/year,3,"$30,000-$49,999",Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,"cchs2003_p, cchs2005_p","cchs2003_p::INCCGHH, cchs2005_p::INCEGHH",cat,60000,N/A,"$50,000-$79,999","$50,000-$79,999",$/year,4,"$50,000-$79,999",Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,"cchs2003_p, cchs2005_p","cchs2003_p::INCCGHH, cchs2005_p::INCEGHH",cat,100000,N/A,"$80,000 or more","$80,000 or more",$/year,5,"$80,000 or more",Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,"cchs2003_p, cchs2005_p","cchs2003_p::INCCGHH, cchs2005_p::INCEGHH",cat,NA::a,N/A,not applicable,not applicable,$/year,6,not applicable,Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,"cchs2003_p, cchs2005_p","cchs2003_p::INCCGHH, cchs2005_p::INCEGHH",cat,NA::b,N/A,missing,missing,$/year,"[7,9]","don't know (7), refusal (8), not stated (9)",Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,"cchs2003_p, cchs2005_p","cchs2003_p::INCCGHH, cchs2005_p::INCEGHH",cat,NA::b,N/A,missing,missing,$/year,else,else,Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGHH, cchs2017_2018_p::INCDGHH, [INCGHH]",cat,10000,N/A,"No income or less than $20,000","No income or less than $20,000",$/year,1,"No income or less than $20,000",Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGHH, cchs2017_2018_p::INCDGHH, [INCGHH]",cat,30000,N/A,"$20,000-39,999","$20,000-39,999",$/year,2,"$20,000-39,999",Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGHH, cchs2017_2018_p::INCDGHH, [INCGHH]",cat,50000,N/A,"$40,000-$59,999","$40,000-$59,999",$/year,3,"$40,000-$59,999",Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGHH, cchs2017_2018_p::INCDGHH, [INCGHH]",cat,70000,N/A,"$60,000-$79,999","$60,000-$79,999",$/year,4,"$60,000-$79,999",Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGHH, cchs2017_2018_p::INCDGHH, [INCGHH]",cat,100000,N/A,"$80,000 or more","$80,000 or more",$/year,5,"$80,000 or more",Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGHH, cchs2017_2018_p::INCDGHH, [INCGHH]",cat,NA::a,N/A,not applicable,not applicable,$/year,6,not applicable,Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGHH, cchs2017_2018_p::INCDGHH, [INCGHH]",cat,NA::b,N/A,missing,missing,$/year,"[7,9]","don't know (7), refusal (8), not stated (9)",Household income,Total household income from all sources - continuous, -INCGHH_cont,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGHH, cchs2017_2018_p::INCDGHH, [INCGHH]",cat,NA::b,N/A,missing,missing,$/year,else,else,Household income,Total household income from all sources - continuous, -INCGPER_A,INCGPER_A_cat6_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::INCAGPER, cchs2003_p::INCCGPER, cchs2005_p::INCEGPER",cat,1,6,No income,No income,$/year,1,No income,Personal income,"Total pers. inc. from all sources (D, G)", -INCGPER_A,INCGPER_A_cat6_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::INCAGPER, cchs2003_p::INCCGPER, cchs2005_p::INCEGPER",cat,2,6,"Less than $15,000","Less than $15,000",$/year,2,"Less than $15,000",Personal income,"Total pers. inc. from all sources (D, G)", -INCGPER_A,INCGPER_A_cat6_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::INCAGPER, cchs2003_p::INCCGPER, cchs2005_p::INCEGPER",cat,3,6,"$15,000-$29,999","$15,000-$29,999",$/year,3,"$15,000-$29,999",Personal income,"Total pers. inc. from all sources (D, G)", -INCGPER_A,INCGPER_A_cat6_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::INCAGPER, cchs2003_p::INCCGPER, cchs2005_p::INCEGPER",cat,4,6,"$30,000-$49,999","$30,000-$49,999",$/year,4,"$30,000-$49,999",Personal income,"Total pers. inc. from all sources (D, G)", -INCGPER_A,INCGPER_A_cat6_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::INCAGPER, cchs2003_p::INCCGPER, cchs2005_p::INCEGPER",cat,5,6,"$50,000-$79,999","$50,000-$79,999",$/year,5,"$50,000-$79,999",Personal income,"Total pers. inc. from all sources (D, G)", -INCGPER_A,INCGPER_A_cat6_6,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::INCAGPER, cchs2003_p::INCCGPER, cchs2005_p::INCEGPER",cat,6,6,"$80,000 or more","$80,000 or more",$/year,6,"$80,000 or more",Personal income,"Total pers. inc. from all sources (D, G)", -INCGPER_A,INCGPER_A_cat6_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::INCAGPER, cchs2003_p::INCCGPER, cchs2005_p::INCEGPER",cat,NA::a,6,not applicable,not applicable,$/year,96,not applicable,Personal income,"Total pers. inc. from all sources (D, G)", -INCGPER_A,INCGPER_A_cat6_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::INCAGPER, cchs2003_p::INCCGPER, cchs2005_p::INCEGPER",cat,NA::b,6,missing,missing,$/year,"[97,99]",don't know (97); refusal (98); not stated (99),Personal income,"Total pers. inc. from all sources (D, G)",CCHS 2001 missing 97 (don't know) and 98 (refusal) -INCGPER_A,INCGPER_A_cat6_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::INCAGPER, cchs2003_p::INCCGPER, cchs2005_p::INCEGPER",cat,NA::b,6,missing,missing,$/year,else,else,Personal income,"Total pers. inc. from all sources (D, G)", -INCGPER_B,INCGPER_B_cat6_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGPER, cchs2017_2018_p::INCDGPER, [INCGPER]",cat,1,6,No income,No income,$/year,1,No income,Personal income,"Total pers. inc. from all sources (D, G)", -INCGPER_B,INCGPER_B_cat6_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGPER, cchs2017_2018_p::INCDGPER, [INCGPER]",cat,2,6,"Less than $20,000","Less than $20,000",$/year,2,"Less than $20,000",Personal income,"Total pers. inc. from all sources (D, G)", -INCGPER_B,INCGPER_B_cat6_3,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGPER, cchs2017_2018_p::INCDGPER, [INCGPER]",cat,3,6,"$20,000-$39,999","$20,000-$39,999",$/year,3,"$20,000-$39,999",Personal income,"Total pers. inc. from all sources (D, G)", -INCGPER_B,INCGPER_B_cat6_4,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGPER, cchs2017_2018_p::INCDGPER, [INCGPER]",cat,4,6,"$40,000-$59,999","$40,000-$59,999",$/year,4,"$40,000-$59,999",Personal income,"Total pers. inc. from all sources (D, G)", -INCGPER_B,INCGPER_B_cat6_5,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGPER, cchs2017_2018_p::INCDGPER, [INCGPER]",cat,5,6,"$60,000-$79,999","$60,000-$79,999",$/year,5,"$60,000-$79,999",Personal income,"Total pers. inc. from all sources (D, G)", -INCGPER_B,INCGPER_B_cat6_6,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGPER, cchs2017_2018_p::INCDGPER, [INCGPER]",cat,6,6,"$80,000 or more","$80,000 or more",$/year,6,"$80,000 or more",Personal income,"Total pers. inc. from all sources (D, G)", -INCGPER_B,INCGPER_B_cat6_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGPER, cchs2017_2018_p::INCDGPER, [INCGPER]",cat,NA::a,6,not applicable,not applicable,$/year,96,not applicable,Personal income,"Total pers. inc. from all sources (D, G)", -INCGPER_B,INCGPER_B_cat6_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGPER, cchs2017_2018_p::INCDGPER, [INCGPER]",cat,NA::b,6,missing,missing,$/year,"[97,99]",don't know (97); refusal (98); not stated (99),Personal income,"Total pers. inc. from all sources (D, G)", -INCGPER_B,INCGPER_B_cat6_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGPER, cchs2017_2018_p::INCDGPER, [INCGPER]",cat,NA::b,6,missing,missing,$/year,else,else,Personal income,"Total pers. inc. from all sources (D, G)", -INCGPER_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::INCAGPER, cchs2003_p::INCCGPER, cchs2005_p::INCEGPER",cat,0,N/A,No income,No income,$/year,1,No income,Personal income,"Total pers. inc. from all sources (D, G) - continuous", -INCGPER_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::INCAGPER, cchs2003_p::INCCGPER, cchs2005_p::INCEGPER",cat,7500,N/A,"Less than $15,000","Less than $15,000",$/year,2,"Less than $15,000",Personal income,"Total pers. inc. from all sources (D, G) - continuous", -INCGPER_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::INCAGPER, cchs2003_p::INCCGPER, cchs2005_p::INCEGPER",cat,22500,N/A,"$15,000-$29,999","$15,000-$29,999",$/year,3,"$15,000-$29,999",Personal income,"Total pers. inc. from all sources (D, G) - continuous", -INCGPER_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::INCAGPER, cchs2003_p::INCCGPER, cchs2005_p::INCEGPER",cat,40000,N/A,"$30,000-$49,999","$30,000-$49,999",$/year,4,"$30,000-$49,999",Personal income,"Total pers. inc. from all sources (D, G) - continuous", -INCGPER_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::INCAGPER, cchs2003_p::INCCGPER, cchs2005_p::INCEGPER",cat,60000,N/A,"$50,000-$79,999","$50,000-$79,999",$/year,5,"$50,000-$79,999",Personal income,"Total pers. inc. from all sources (D, G) - continuous", -INCGPER_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::INCAGPER, cchs2003_p::INCCGPER, cchs2005_p::INCEGPER",cat,100000,N/A,"$80,000 or more","$80,000 or more",$/year,6,"$80,000 or more",Personal income,"Total pers. inc. from all sources (D, G) - continuous", -INCGPER_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::INCAGPER, cchs2003_p::INCCGPER, cchs2005_p::INCEGPER",cat,NA::a,N/A,not applicable,not applicable,$/year,96,not applicable,Personal income,"Total pers. inc. from all sources (D, G) - continuous", -INCGPER_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::INCAGPER, cchs2003_p::INCCGPER, cchs2005_p::INCEGPER",cat,NA::b,N/A,missing,missing,$/year,"[97,99]",don't know (97); refusal (98); not stated (99),Personal income,"Total pers. inc. from all sources (D, G) - continuous", -INCGPER_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::INCAGPER, cchs2003_p::INCCGPER, cchs2005_p::INCEGPER",cat,NA::b,N/A,missing,missing,$/year,else,else,Personal income,"Total pers. inc. from all sources (D, G) - continuous", -INCGPER_cont,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGPER, cchs2017_2018_p::INCDGPER, [INCGPER]",cat,0,N/A,No income,No income,$/year,1,No income,Personal income,"Total pers. inc. from all sources (D, G) - continuous", -INCGPER_cont,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGPER, cchs2017_2018_p::INCDGPER, [INCGPER]",cat,10000,N/A,"Less than $20,000","Less than $20,000",$/year,2,"Less than $20,000",Personal income,"Total pers. inc. from all sources (D, G) - continuous", -INCGPER_cont,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGPER, cchs2017_2018_p::INCDGPER, [INCGPER]",cat,30000,N/A,"$20,000-$39,999","$20,000-$39,999",$/year,3,"$20,000-$39,999",Personal income,"Total pers. inc. from all sources (D, G) - continuous", -INCGPER_cont,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGPER, cchs2017_2018_p::INCDGPER, [INCGPER]",cat,50000,N/A,"$40,000-$59,999","$40,000-$59,999",$/year,4,"$40,000-$59,999",Personal income,"Total pers. inc. from all sources (D, G) - continuous", -INCGPER_cont,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGPER, cchs2017_2018_p::INCDGPER, [INCGPER]",cat,70000,N/A,"$60,000-$79,999","$60,000-$79,999",$/year,5,"$60,000-$79,999",Personal income,"Total pers. inc. from all sources (D, G) - continuous", -INCGPER_cont,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGPER, cchs2017_2018_p::INCDGPER, [INCGPER]",cat,100000,N/A,"$80,000 or more","$80,000 or more",$/year,6,"$80,000 or more",Personal income,"Total pers. inc. from all sources (D, G) - continuous", -INCGPER_cont,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGPER, cchs2017_2018_p::INCDGPER, [INCGPER]",cat,NA::a,N/A,not applicable,not applicable,$/year,96,not applicable,Personal income,"Total pers. inc. from all sources (D, G) - continuous", -INCGPER_cont,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGPER, cchs2017_2018_p::INCDGPER, [INCGPER]",cat,NA::b,N/A,missing,missing,$/year,"[97,99]",don't know (97); refusal (98); not stated (99),Personal income,"Total pers. inc. from all sources (D, G) - continuous", -INCGPER_cont,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::INCDGPER, cchs2017_2018_p::INCDGPER, [INCGPER]",cat,NA::b,N/A,missing,missing,$/year,else,else,Personal income,"Total pers. inc. from all sources (D, G) - continuous", -LBFA_31A,LBFA_31A_cat9_1,cat,cchs2001_p,[LBFA_31A],cat,1,9,Management,Management,N/A,1,Management,Occupation,Which of the following best describes your occupation?, -LBFA_31A,LBFA_31A_cat9_2,cat,cchs2001_p,[LBFA_31A],cat,2,9,Professional (including accountants),Professional (including accountants),N/A,2,Professional (including accountants),Occupation,Which of the following best describes your occupation?, -LBFA_31A,LBFA_31A_cat9_3,cat,cchs2001_p,[LBFA_31A],cat,3,9,"Technologist, Technician or Tech Occ","Technologist, Technician or Tech Occ",N/A,3,"Technologist, Technician or Tech Occ",Occupation,Which of the following best describes your occupation?, -LBFA_31A,LBFA_31A_cat9_4,cat,cchs2001_p,[LBFA_31A],cat,4,9,"Administrative, Financial or Clerical","Administrative, Financial or Clerical",N/A,4,"Administrative, Financial or Clerical",Occupation,Which of the following best describes your occupation?, -LBFA_31A,LBFA_31A_cat9_5,cat,cchs2001_p,[LBFA_31A],cat,5,9,Sales or Service,Sales or Service,N/A,5,Sales or Service,Occupation,Which of the following best describes your occupation?, -LBFA_31A,LBFA_31A_cat9_6,cat,cchs2001_p,[LBFA_31A],cat,6,9,"Trades, Transport or Equipment Operator","Trades, Transport or Equipment Operator",N/A,6,"Trades, Transport or Equipment Operator",Occupation,Which of the following best describes your occupation?, -LBFA_31A,LBFA_31A_cat9_7,cat,cchs2001_p,[LBFA_31A],cat,7,9,"Farming, Forestry, Fishing, Mining","Farming, Forestry, Fishing, Mining",N/A,7,"Farming, Forestry, Fishing, Mining",Occupation,Which of the following best describes your occupation?, -LBFA_31A,LBFA_31A_cat9_8,cat,cchs2001_p,[LBFA_31A],cat,8,9,"Processing, Manufacturing, Utilities","Processing, Manufacturing, Utilities",N/A,8,"Processing, Manufacturing, Utilities",Occupation,Which of the following best describes your occupation?, -LBFA_31A,LBFA_31A_cat9_9,cat,cchs2001_p,[LBFA_31A],cat,9,9,Other,Other,N/A,9,Other,Occupation,Which of the following best describes your occupation?, -LBFA_31A,LBFA_31A_cat9_NA::a,cat,cchs2001_p,[LBFA_31A],cat,NA::a,9,not applicable,not applicable,N/A,96,not applicable,Occupation,Which of the following best describes your occupation?, -LBFA_31A,LBFA_31A_cat9_NA::b,cat,cchs2001_p,[LBFA_31A],cat,NA::b,9,missing,missing,N/A,"[97,99]",don't know (97); refusal (98); not stated (99),Occupation,Which of the following best describes your occupation?, -LBFA_31A,LBFA_31A_cat9_NA::b,cat,cchs2001_p,[LBFA_31A],cat,NA::b,9,missing,missing,N/A,else,else,Occupation,Which of the following best describes your occupation?, -LBFA_31A_a,LBFA_31A_a_cat5_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::LBFDGOCG, cchs2017_2018_p::LBFDGOCG, [LBSGSOC]",cat,1,5,"Management, Health, Education, Art, Culture","Management, Health, Education, Art, Culture",N/A,1,"Management, Health, Education, Art, Culture",Occupation,Occupation group - (G), -LBFA_31A_a,LBFA_31A_a_cat5_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::LBFDGOCG, cchs2017_2018_p::LBFDGOCG, [LBSGSOC]",cat,2,5,"Business, Finance, Admin","Business, Finance, Admin",N/A,2,"Business, Finance, Admin",Occupation,Occupation group - (G), -LBFA_31A_a,LBFA_31A_a_cat5_3,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::LBFDGOCG, cchs2017_2018_p::LBFDGOCG, [LBSGSOC]",cat,3,5,Sales or Service,Sales or Service,N/A,3,Sales or Service,Occupation,Occupation group - (G), -LBFA_31A_a,LBFA_31A_a_cat5_4,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::LBFDGOCG, cchs2017_2018_p::LBFDGOCG, [LBSGSOC]",cat,4,5,"Trades, Transport or Equipment Operator","Trades, Transport or Equipment Operator",N/A,4,"Trades, Transport or Equipment Operator",Occupation,Occupation group - (G), -LBFA_31A_a,LBFA_31A_a_cat5_5,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::LBFDGOCG, cchs2017_2018_p::LBFDGOCG, [LBSGSOC]",cat,5,5,Unique to Prim. Ind./Proc./Manu.,Unique to Prim. Ind./Proc./Manu.,N/A,5,Unique to Prim. Ind./Proc./Manu.,Occupation,Occupation group - (G), -LBFA_31A_a,LBFA_31A_a_cat5_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::LBFDGOCG, cchs2017_2018_p::LBFDGOCG, [LBSGSOC]",cat,NA::a,5,not applicable,not applicable,N/A,6,not applicable,Occupation,Occupation group - (G), -LBFA_31A_a,LBFA_31A_a_cat5_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::LBFDGOCG, cchs2017_2018_p::LBFDGOCG, [LBSGSOC]",cat,NA::b,5,missing,missing,N/A,9,not stated,Occupation,Occupation group - (G), -LBFA_31A_a,LBFA_31A_a_cat5_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::LBFDGOCG, cchs2017_2018_p::LBFDGOCG, [LBSGSOC]",cat,NA::b,5,missing,missing,N/A,else,else,Occupation,Occupation group - (G), -LBFA_31A_a,LBFA_31A_a_cat5_1,cat,cchs2001_p,[LBFA_31A],cat,1,5,"Management, Health, Education, Art, Culture","Management, Health, Education, Art, Culture",N/A,1,Management,Occupation,Which of the following best describes your occupation?,"The three categories in CCHS 2001 ""Management, Professional (including accountants), Technologist, Technician or Tech Occ"" were combined into one category ""Management, Health, Education, Art, Culture"" to harmonize with CCHS cycles 2007-2014" -LBFA_31A_a,LBFA_31A_a_cat5_1,cat,cchs2001_p,[LBFA_31A],cat,1,5,"Management, Health, Education, Art, Culture","Management, Health, Education, Art, Culture",N/A,2,Professional (including accountants),Occupation,Which of the following best describes your occupation?,"The three categories in CCHS 2001 ""Management, Professional (including accountants), Technologist, Technician or Tech Occ"" were combined into one category ""Management, Health, Education, Art, Culture"" to harmonize with CCHS cycles 2007-2015" -LBFA_31A_a,LBFA_31A_a_cat5_1,cat,cchs2001_p,[LBFA_31A],cat,1,5,"Management, Health, Education, Art, Culture","Management, Health, Education, Art, Culture",N/A,3,"Technologist, Technician or Tech Occ",Occupation,Which of the following best describes your occupation?,"The three categories in CCHS 2001 ""Management, Professional (including accountants), Technologist, Technician or Tech Occ"" were combined into one category ""Management, Health, Education, Art, Culture"" to harmonize with CCHS cycles 2007-2016" -LBFA_31A_a,LBFA_31A_a_cat5_2,cat,cchs2001_p,[LBFA_31A],cat,2,5,"Business, Finance, Admin","Business, Finance, Admin",N/A,4,"Administrative, Financial or Clerical",Occupation,Which of the following best describes your occupation?, -LBFA_31A_a,LBFA_31A_a_cat5_3,cat,cchs2001_p,[LBFA_31A],cat,3,5,Sales or Service,Sales or Service,N/A,5,Sales or Service,Occupation,Which of the following best describes your occupation?, -LBFA_31A_a,LBFA_31A_a_cat5_4,cat,cchs2001_p,[LBFA_31A],cat,4,5,"Trades, Transport or Equipment Operator","Trades, Transport or Equipment Operator",N/A,6,"Trades, Transport or Equipment Operator",Occupation,Which of the following best describes your occupation?, -LBFA_31A_a,LBFA_31A_a_cat5_5,cat,cchs2001_p,[LBFA_31A],cat,5,5,Unique to Prim. Ind./Proc./Manu.,Unique to Prim. Ind./Proc./Manu.,N/A,7,"Farming, Forestry, Fishing, Mining",Occupation,Which of the following best describes your occupation?,"The two categories in CCHS 2001, ""Farming, Forestry, Fishing, Mining"" and ""Processing, Manufacturing, Utilities"", were combined into one category ""Farming, Forestry, Fishing, Mining, Processing, Manufacturing, Utilities"", to harmonize with CCHS 2007-2014" -LBFA_31A_a,LBFA_31A_a_cat5_5,cat,cchs2001_p,[LBFA_31A],cat,5,5,Unique to Prim. Ind./Proc./Manu.,Unique to Prim. Ind./Proc./Manu.,N/A,8,"Processing, Manufacturing, Utilities",Occupation,Which of the following best describes your occupation?,"The two categories in CCHS 2001, ""Farming, Forestry, Fishing, Mining"" and ""Processing, Manufacturing, Utilities"", were combined into one category ""Farming, Forestry, Fishing, Mining, Processing, Manufacturing, Utilities"", to harmonize with CCHS 2007-2015" -LBFA_31A_a,LBFA_31A_a_cat5_NA::b,cat,cchs2001_p,[LBFA_31A],cat,NA::b,5,missing,missing,N/A,9,Other,Occupation,Which of the following best describes your occupation?,"""Other"" has no equivalent in LBSGSOC recoded to 'NA::b' missing" -LBFA_31A_a,LBFA_31A_a_cat5_NA::a,cat,cchs2001_p,[LBFA_31A],cat,NA::a,5,not applicable,not applicable,N/A,96,not applicable,Occupation,Which of the following best describes your occupation?, -LBFA_31A_a,LBFA_31A_a_cat5_NA::b,cat,cchs2001_p,[LBFA_31A],cat,NA::b,5,missing,missing,N/A,"[97,99]",don't know (97); refusal (98); not stated (99),Occupation,Which of the following best describes your occupation?, -LBFA_31A_a,LBFA_31A_a_cat5_NA::b,cat,cchs2001_p,[LBFA_31A],cat,NA::b,5,missing,missing,N/A,else,else,Occupation,Which of the following best describes your occupation?, -LBFA_31A_b,LBFA_31A_b_cat6_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::LBFDGOCG, cchs2017_2018_p::LBFDGOCG, [LBSGSOC]",cat,1,6,"Management, Health, Education, Art, Culture","Management, Health, Education, Art, Culture",N/A,1,"Management, Health, Education, Art, Culture",Occupation,Occupation group - (G), -LBFA_31A_b,LBFA_31A_b_cat6_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::LBFDGOCG, cchs2017_2018_p::LBFDGOCG, [LBSGSOC]",cat,2,6,"Business, Finance, Admin","Business, Finance, Admin",N/A,2,"Business, Finance, Admin",Occupation,Occupation group - (G), -LBFA_31A_b,LBFA_31A_b_cat6_3,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::LBFDGOCG, cchs2017_2018_p::LBFDGOCG, [LBSGSOC]",cat,3,6,Sales or Service,Sales or Service,N/A,3,Sales or Service,Occupation,Occupation group - (G), -LBFA_31A_b,LBFA_31A_b_cat6_4,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::LBFDGOCG, cchs2017_2018_p::LBFDGOCG, [LBSGSOC]",cat,4,6,"Trades, Transport or Equipment Operator","Trades, Transport or Equipment Operator",N/A,4,"Trades, Transport or Equipment Operator",Occupation,Occupation group - (G), -LBFA_31A_b,LBFA_31A_b_cat6_5,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::LBFDGOCG, cchs2017_2018_p::LBFDGOCG, [LBSGSOC]",cat,5,6,Unique to Prim. Ind./Proc./Manu.,Unique to Prim. Ind./Proc./Manu.,N/A,5,Unique to Prim. Ind./Proc./Manu.,Occupation,Occupation group - (G), -LBFA_31A_b,LBFA_31A_b_cat6_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::LBFDGOCG, cchs2017_2018_p::LBFDGOCG, [LBSGSOC]",cat,NA::a,6,not applicable,not applicable,N/A,6,not applicable,Occupation,Occupation group - (G), -LBFA_31A_b,LBFA_31A_b_cat6_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::LBFDGOCG, cchs2017_2018_p::LBFDGOCG, [LBSGSOC]",cat,NA::b,6,missing,missing,N/A,9,not stated,Occupation,Occupation group - (G), -LBFA_31A_b,LBFA_31A_b_cat6_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::LBFDGOCG, cchs2017_2018_p::LBFDGOCG, [LBSGSOC]",cat,NA::b,6,missing,missing,N/A,else,else,Occupation,Occupation group - (G), -LBFA_31A_b,LBFA_31A_b_cat6_1,cat,cchs2001_p,[LBFA_31A],cat,1,6,"Management, Health, Education, Art, Culture","Management, Health, Education, Art, Culture",N/A,1,Management,Occupation,Which of the following best describes your occupation?,"The three categories in CCHS 2001 ""Management, Professional (including accountants), Technologist, Technician or Tech Occ"" were combined into one category ""Management, Health, Education, Art, Culture"" to harmonize with CCHS cycles 2007-2014" -LBFA_31A_b,LBFA_31A_b_cat6_1,cat,cchs2001_p,[LBFA_31A],cat,1,6,"Management, Health, Education, Art, Culture","Management, Health, Education, Art, Culture",N/A,2,Professional (including accountants),Occupation,Which of the following best describes your occupation?,"The three categories in CCHS 2001 ""Management, Professional (including accountants), Technologist, Technician or Tech Occ"" were combined into one category ""Management, Health, Education, Art, Culture"" to harmonize with CCHS cycles 2007-2015" -LBFA_31A_b,LBFA_31A_b_cat6_1,cat,cchs2001_p,[LBFA_31A],cat,1,6,"Management, Health, Education, Art, Culture","Management, Health, Education, Art, Culture",N/A,3,"Technologist, Technician or Tech Occ",Occupation,Which of the following best describes your occupation?,"The three categories in CCHS 2001 ""Management, Professional (including accountants), Technologist, Technician or Tech Occ"" were combined into one category ""Management, Health, Education, Art, Culture"" to harmonize with CCHS cycles 2007-2016" -LBFA_31A_b,LBFA_31A_b_cat6_2,cat,cchs2001_p,[LBFA_31A],cat,2,6,"Business, Finance, Admin","Business, Finance, Admin",N/A,4,"Administrative, Financial or Clerical",Occupation,Which of the following best describes your occupation?, -LBFA_31A_b,LBFA_31A_b_cat6_3,cat,cchs2001_p,[LBFA_31A],cat,3,6,Sales or Service,Sales or Service,N/A,5,Sales or Service,Occupation,Which of the following best describes your occupation?, -LBFA_31A_b,LBFA_31A_b_cat6_4,cat,cchs2001_p,[LBFA_31A],cat,4,6,"Trades, Transport or Equipment Operator","Trades, Transport or Equipment Operator",N/A,6,"Trades, Transport or Equipment Operator",Occupation,Which of the following best describes your occupation?, -LBFA_31A_b,LBFA_31A_b_cat6_5,cat,cchs2001_p,[LBFA_31A],cat,5,6,Unique to Prim. Ind./Proc./Manu.,Unique to Prim. Ind./Proc./Manu.,N/A,7,"Farming, Forestry, Fishing, Mining",Occupation,Which of the following best describes your occupation?,"The two categories in CCHS 2001, ""Farming, Forestry, Fishing, Mining"" and ""Processing, Manufacturing, Utilities"", were combined into one category ""Farming, Forestry, Fishing, Mining, Processing, Manufacturing, Utilities"", to harmonize with CCHS 2007-2014" -LBFA_31A_b,LBFA_31A_b_cat6_5,cat,cchs2001_p,[LBFA_31A],cat,5,6,Unique to Prim. Ind./Proc./Manu.,Unique to Prim. Ind./Proc./Manu.,N/A,8,"Processing, Manufacturing, Utilities",Occupation,Which of the following best describes your occupation?,"The two categories in CCHS 2001, ""Farming, Forestry, Fishing, Mining"" and ""Processing, Manufacturing, Utilities"", were combined into one category ""Farming, Forestry, Fishing, Mining, Processing, Manufacturing, Utilities"", to harmonize with CCHS 2007-2015" -LBFA_31A_b,LBFA_31A_b_cat6_6,cat,cchs2001_p,[LBFA_31A],cat,6,6,Other,Other,N/A,9,Other,Occupation,Which of the following best describes your occupation?, -LBFA_31A_b,LBFA_31A_b_cat6_NA::a,cat,cchs2001_p,[LBFA_31A],cat,NA::a,6,not applicable,not applicable,N/A,96,not applicable,Occupation,Which of the following best describes your occupation?, -LBFA_31A_b,LBFA_31A_b_cat6_NA::b,cat,cchs2001_p,[LBFA_31A],cat,NA::b,6,missing,missing,N/A,"[97,99]",don't know (97); refusal (98); not stated (99),Occupation,Which of the following best describes your occupation?, -LBFA_31A_b,LBFA_31A_b_cat6_NA::b,cat,cchs2001_p,[LBFA_31A],cat,NA::b,6,missing,missing,N/A,else,else,Occupation,Which of the following best describes your occupation?, -low_drink_score,low_drink_score_cat4N/A_Func::low_drink_score_fun,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALWDWKY]",N/A,Func::low_drink_score_fun,N/A,N/A,N/A,N/A,N/A,N/A,Low risk drinking score,Low risk drinking score,"Risk based on Canada's Low Risk Alcohol Drinking Guidelines. Refer to https://osf.io/eprg7/ . Derived from DHH_SEX, ALWDWKY." -low_drink_score,low_drink_score_cat4_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALWDWKY]",N/A,1,4,Low risk,Low risk,N/A,1,Low risk,Low risk drinking score,Low risk drinking score, -low_drink_score,low_drink_score_cat4_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALWDWKY]",N/A,2,4,Marginal risk,Marginal risk,N/A,2,Marginal risk,Low risk drinking score,Low risk drinking score, -low_drink_score,low_drink_score_cat4_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALWDWKY]",N/A,3,4,Medium risk,Medium risk,N/A,3,Medium risk,Low risk drinking score,Low risk drinking score, -low_drink_score,low_drink_score_cat4_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALWDWKY]",N/A,4,4,High risk,High risk,N/A,4,High risk,Low risk drinking score,Low risk drinking score, -low_drink_score,low_drink_score_cat4_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALWDWKY]",N/A,NA::b,4,missing,missing,N/A,N/A,N/A,Low risk drinking score,Low risk drinking score, -low_drink_score1,low_drink_score1_cat5N/A_Func::low_drink_score_fun1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALWDWKY, ALC_005, ALC_1]",N/A,Func::low_drink_score_fun1,N/A,N/A,N/A,N/A,N/A,N/A,Low risk drinking score - former/never drinking categories,Low risk drinking score - former/never drinking categories, -low_drink_score1,low_drink_score1_cat5_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALWDWKY, ALC_005, ALC_1]",N/A,1,5,Low risk - never drank,Low risk - never drank,N/A,1,Low risk - never drank,Low risk drinking score - former/never drinking categories,Low risk drinking score - former/never drinking categories, -low_drink_score1,low_drink_score1_cat5_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALWDWKY, ALC_005, ALC_1]",N/A,2,5,Low risk - former drinker,Low risk - former drinker,N/A,2,Low risk - former drinker,Low risk drinking score - former/never drinking categories,Low risk drinking score - former/never drinking categories, -low_drink_score1,low_drink_score1_cat5_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALWDWKY, ALC_005, ALC_1]",N/A,3,5,Marginal risk,Marginal risk,N/A,3,Marginal risk,Low risk drinking score - former/never drinking categories,Low risk drinking score - former/never drinking categories, -low_drink_score1,low_drink_score1_cat5_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALWDWKY, ALC_005, ALC_1]",N/A,4,5,Medium risk,Medium risk,N/A,4,Medium risk,Low risk drinking score - former/never drinking categories,Low risk drinking score - former/never drinking categories, -low_drink_score1,low_drink_score1_cat5_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALWDWKY, ALC_005, ALC_1]",N/A,5,5,High risk,High risk,N/A,5,High risk,Low risk drinking score - former/never drinking categories,Low risk drinking score - former/never drinking categories, -low_drink_score1,low_drink_score1_cat5_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHH_SEX, ALWDWKY, ALC_005, ALC_1]",N/A,NA::b,5,missing,missing,N/A,N/A,N/A,Low risk drinking score - former/never drinking categories,Low risk drinking score - former/never drinking categories, -MED_1P,MED_1P_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2011_2012_p, cchs2012_p","cchs2001_p::DRGA_1P, cchs2003_p::MEDC_1P, cchs2005_p::MEDE_1P, [MED_1P]",cat,1,2,Yes,Yes,N/A,1,Yes,Medication - sleeping pills,"In the past month, did you take sleeping pills such as Imovane, Nytol or Starnoc?",CCHS 2001 does not provide examples of sleeping pills in its literal question -MED_1P,MED_1P_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2011_2012_p, cchs2012_p","cchs2001_p::DRGA_1P, cchs2003_p::MEDC_1P, cchs2005_p::MEDE_1P, [MED_1P]",cat,2,2,No,No,N/A,2,No,Medication - sleeping pills,"In the past month, did you take sleeping pills such as Imovane, Nytol or Starnoc?", -MED_1P,MED_1P_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2011_2012_p, cchs2012_p","cchs2001_p::DRGA_1P, cchs2003_p::MEDC_1P, cchs2005_p::MEDE_1P, [MED_1P]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Medication - sleeping pills,"In the past month, did you take sleeping pills such as Imovane, Nytol or Starnoc?", -MED_1P,MED_1P_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2011_2012_p, cchs2012_p","cchs2001_p::DRGA_1P, cchs2003_p::MEDC_1P, cchs2005_p::MEDE_1P, [MED_1P]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Medication - sleeping pills,"In the past month, did you take sleeping pills such as Imovane, Nytol or Starnoc?", -MED_1P,MED_1P_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2011_2012_p, cchs2012_p","cchs2001_p::DRGA_1P, cchs2003_p::MEDC_1P, cchs2005_p::MEDE_1P, [MED_1P]",cat,NA::b,2,missing,missing,N/A,else,else,Medication - sleeping pills,"In the past month, did you take sleeping pills such as Imovane, Nytol or Starnoc?", -number_conditions,number_conditions_catN/A_Func::multiple_conditions_fun1,cat,cchs2001_p,"DerivedVar::[CCC_121, CCC_131, CCC_151, CCC_171, resp_condition_der, CCC_051]",N/A,Func::multiple_conditions_fun1,N/A,N/A,N/A,N/A,N/A,N/A,Number of chronic conditions,Number of chronic conditions,"This variable is derived from CCC_121, CCC_131, CCC_151, CCC_171, resp_condition, CCC_050" -number_conditions,number_conditions_catN/A_Func::multiple_conditions_fun2,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","DerivedVar::[CCC_121, CCC_131, CCC_151, CCC_171, CCC_280, resp_condition_der, CCC_051]",N/A,Func::multiple_conditions_fun2,N/A,N/A,N/A,N/A,N/A,N/A,Number of chronic conditions,Number of chronic conditions,"This variable is derived from CCC_121, CCC_131, CCC_151, CCC_171, CCC_280, resp_condition, CCC_051. Variable can be extended to 2018 when bowel condition not included." -number_conditions,number_conditions_cat6_0,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","DerivedVar::[CCC_121, CCC_131, CCC_151, CCC_171, CCC_280, resp_condition_der, CCC_051]",N/A,0,6,0,0,N/A,N/A,0,Number of chronic conditions,Number of chronic conditions, -number_conditions,number_conditions_cat6_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","DerivedVar::[CCC_121, CCC_131, CCC_151, CCC_171, CCC_280, resp_condition_der, CCC_051]",N/A,1,6,1,1,N/A,N/A,1,Number of chronic conditions,Number of chronic conditions, -number_conditions,number_conditions_cat6_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","DerivedVar::[CCC_121, CCC_131, CCC_151, CCC_171, CCC_280, resp_condition_der, CCC_051]",N/A,2,6,2,2,N/A,N/A,2,Number of chronic conditions,Number of chronic conditions, -number_conditions,number_conditions_cat6_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","DerivedVar::[CCC_121, CCC_131, CCC_151, CCC_171, CCC_280, resp_condition_der, CCC_051]",N/A,3,6,3,3,N/A,N/A,3,Number of chronic conditions,Number of chronic conditions, -number_conditions,number_conditions_cat6_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","DerivedVar::[CCC_121, CCC_131, CCC_151, CCC_171, CCC_280, resp_condition_der, CCC_051]",N/A,4,6,4,4,N/A,N/A,4,Number of chronic conditions,Number of chronic conditions, -number_conditions,number_conditions_cat6_5+,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","DerivedVar::[CCC_121, CCC_131, CCC_151, CCC_171, CCC_280, resp_condition_der, CCC_051]",N/A,5+,6,5+,5+,N/A,N/A,5+,Number of chronic conditions,Number of chronic conditions, -PAA_045,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAA_045],cat,copy,N/A,No. hours sweat,No. hours sweat,hours/week,"[0,160]",No. hours sweat,Sports / fitness / rec phys act - 7 d - total - hours,"(18+ years old) In the last 7 days, how much time in total did you spend doing these activities that made you sweat at least a little and breathe harder?", -PAA_045,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAA_045],cat,NA::a,N/A,not applicable,not applicable,hours/week,996,not applicable,Sports / fitness / rec phys act - 7 d - total - hours,"(18+ years old) In the last 7 days, how much time in total did you spend doing these activities that made you sweat at least a little and breathe harder?", -PAA_045,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAA_045],cat,NA::b,N/A,missing,missing,hours/week,"[997,999]",don't know (997); refusal (998); not stated (999),Sports / fitness / rec phys act - 7 d - total - hours,"(18+ years old) In the last 7 days, how much time in total did you spend doing these activities that made you sweat at least a little and breathe harder?", -PAA_045,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAA_045],cat,NA::b,N/A,missing,missing,hours/week,else,else,Sports / fitness / rec phys act - 7 d - total - hours,"(18+ years old) In the last 7 days, how much time in total did you spend doing these activities that made you sweat at least a little and breathe harder?", -PAA_050,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAA_050],cat,copy,N/A,No. minutes sweat,No. minutes sweat,minutes/week,"[0,1680]",No. minutes sweat,Sports / fitness / rec phys act - 7 d - total - minutes,"(18+ years old) In the last 7 days, how much time in total did you spend doing these activities that made you sweat at least a little and breathe harder?", -PAA_050,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAA_050],cat,NA::a,N/A,not applicable,not applicable,minutes/week,9996,not applicable,Sports / fitness / rec phys act - 7 d - total - minutes,"(18+ years old) In the last 7 days, how much time in total did you spend doing these activities that made you sweat at least a little and breathe harder?", -PAA_050,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAA_050],cat,NA::b,N/A,missing,missing,minutes/week,"[9997,9999]",don't know (9997); refusal (9998); not stated (9999),Sports / fitness / rec phys act - 7 d - total - minutes,"(18+ years old) In the last 7 days, how much time in total did you spend doing these activities that made you sweat at least a little and breathe harder?", -PAA_050,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAA_050],cat,NA::b,N/A,missing,missing,minutes/week,else,else,Sports / fitness / rec phys act - 7 d - total - minutes,"(18+ years old) In the last 7 days, how much time in total did you spend doing these activities that made you sweat at least a little and breathe harder?", -PAA_075,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAA_075],cat,copy,N/A,No. hours sweat,No. hours sweat,hours/week,"[0,168]",No. hours sweat,Other physical activities - 7 d - total - hours,"(18+ years old) In the last 7 days, how much time in total did you spend doing these activities that made you sweat at least a little and breathe harder?", -PAA_075,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAA_075],cat,NA::a,N/A,not applicable,not applicable,hours/week,996,not applicable,Other physical activities - 7 d - total - hours,"(18+ years old) In the last 7 days, how much time in total did you spend doing these activities that made you sweat at least a little and breathe harder?", -PAA_075,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAA_075],cat,NA::b,N/A,missing,missing,hours/week,"[997,999]",don't know (997); refusal (998); not stated (999),Other physical activities - 7 d - total - hours,"(18+ years old) In the last 7 days, how much time in total did you spend doing these activities that made you sweat at least a little and breathe harder?", -PAA_075,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAA_075],cat,NA::b,N/A,missing,missing,hours/week,else,else,Other physical activities - 7 d - total - hours,"(18+ years old) In the last 7 days, how much time in total did you spend doing these activities that made you sweat at least a little and breathe harder?", -PAA_080,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAA_080],cat,copy,N/A,No. minutes sweat,No. minutes sweat,minutes/week,"[0,4880]",No. minutes sweat,Other physical activities - 7 d - total - minutes,"(18+ years old) In the last 7 days, how much time in total did you spend doing these activities that made you sweat at least a little and breathe harder?", -PAA_080,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAA_080],cat,NA::a,N/A,not applicable,not applicable,minutes/week,9996,not applicable,Other physical activities - 7 d - total - minutes,"(18+ years old) In the last 7 days, how much time in total did you spend doing these activities that made you sweat at least a little and breathe harder?", -PAA_080,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAA_080],cat,NA::b,N/A,missing,missing,minutes/week,"[9997,9999]",don't know (9997); refusal (9998); not stated (9999),Other physical activities - 7 d - total - minutes,"(18+ years old) In the last 7 days, how much time in total did you spend doing these activities that made you sweat at least a little and breathe harder?", -PAA_080,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAA_080],cat,NA::b,N/A,missing,missing,minutes/week,else,else,Other physical activities - 7 d - total - minutes,"(18+ years old) In the last 7 days, how much time in total did you spend doing these activities that made you sweat at least a little and breathe harder?", -PAADVVIG,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAADVVIG],cont,copy,N/A,No. minutes - vigorous physical activity - 7d,No. minutes - vigorous physical activity - 7d,minutes/week,"[0,6000]",No. minutes - vigorous physical activity - 7d,Total minutes of vigorous activity over a week,(18+ years old) Total minutes of vigorous activity - 7 d - (D), -PAADVVIG,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAADVVIG],cont,NA::a,N/A,not applicable,not applicable,minutes/week,99996,not applicable,Total minutes of vigorous activity over a week,(18+ years old) Total minutes of vigorous activity - 7 d - (D), -PAADVVIG,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAADVVIG],cont,NA::b,N/A,missing,missing,minutes/week,"[99997,99999]",don't know (99997); refusal (99998); not stated (99999),Total minutes of vigorous activity over a week,(18+ years old) Total minutes of vigorous activity - 7 d - (D), -PAADVVIG,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAADVVIG],cont,NA::b,N/A,missing,missing,minutes/week,else,else,Total minutes of vigorous activity over a week,(18+ years old) Total minutes of vigorous activity - 7 d - (D), -PAADVDYS,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAADVDYS],cont,copy,N/A,No. active days - 7d,No. active days - 7d,days,"[0,7]",No. active days - 7d,No. active days - 7d,(18+ years old) Number of active days - 7 d - (D), -PAADVDYS,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAADVDYS],cont,NA::a,N/A,not applicable,not applicable,days,96,not applicable,No. active days - 7d,(18+ years old) Number of active days - 7 d - (D), -PAADVDYS,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAADVDYS],cont,NA::b,N/A,missing,missing,days,"[97,99]",don't know (97); refusal (98); not stated (99),No. active days - 7d,(18+ years old) Number of active days - 7 d - (D), -PAADVDYS,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAADVDYS],cont,NA::b,N/A,missing,missing,days,else,else,No. active days - 7d,(18+ years old) Number of active days - 7 d - (D), -PAC_4A,PAC_4A_cat6_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::PACA_4A, cchs2003_p::PACC_4A, cchs2005_p::PACE_4A",cat,1,6,None,None,hours/week,1,None,No./hours spent - walking work/school,"In a typical week in the past 3 months, how many hours did you usually spend walking to work or to school or while doing errands?", -PAC_4A,PAC_4A_cat6_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::PACA_4A, cchs2003_p::PACC_4A, cchs2005_p::PACE_4A",cat,2,6,Less than one hour,Less than one hour,hours/week,2,Less than one hour,No./hours spent - walking work/school,"In a typical week in the past 3 months, how many hours did you usually spend walking to work or to school or while doing errands?", -PAC_4A,PAC_4A_cat6_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::PACA_4A, cchs2003_p::PACC_4A, cchs2005_p::PACE_4A",cat,3,6,1-5 hours,1-5 hours,hours/week,3,1-5 hours,No./hours spent - walking work/school,"In a typical week in the past 3 months, how many hours did you usually spend walking to work or to school or while doing errands?", -PAC_4A,PAC_4A_cat6_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::PACA_4A, cchs2003_p::PACC_4A, cchs2005_p::PACE_4A",cat,4,6,6-10 hours,6-10 hours,hours/week,4,6-10 hours,No./hours spent - walking work/school,"In a typical week in the past 3 months, how many hours did you usually spend walking to work or to school or while doing errands?", -PAC_4A,PAC_4A_cat6_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::PACA_4A, cchs2003_p::PACC_4A, cchs2005_p::PACE_4A",cat,5,6,11-20 hours,11-20 hours,hours/week,5,11-20 hours,No./hours spent - walking work/school,"In a typical week in the past 3 months, how many hours did you usually spend walking to work or to school or while doing errands?", -PAC_4A,PAC_4A_cat6_6,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::PACA_4A, cchs2003_p::PACC_4A, cchs2005_p::PACE_4A",cat,6,6,More than 20 hours,More than 20 hours,hours/week,6,More than 20 hours,No./hours spent - walking work/school,"In a typical week in the past 3 months, how many hours did you usually spend walking to work or to school or while doing errands?", -PAC_4A,PAC_4A_cat6_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::PACA_4A, cchs2003_p::PACC_4A, cchs2005_p::PACE_4A",cat,NA::a,6,not applicable,not applicable,hours/week,96,not applicable,No./hours spent - walking work/school,"In a typical week in the past 3 months, how many hours did you usually spend walking to work or to school or while doing errands?", -PAC_4A,PAC_4A_cat6_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::PACA_4A, cchs2003_p::PACC_4A, cchs2005_p::PACE_4A",cat,NA::b,6,missing,missing,hours/week,"[97,99]",don't know (97); refusal (98); not stated (99),No./hours spent - walking work/school,"In a typical week in the past 3 months, how many hours did you usually spend walking to work or to school or while doing errands?", -PAC_4A,PAC_4A_cat6_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::PACA_4A, cchs2003_p::PACC_4A, cchs2005_p::PACE_4A",cat,NA::b,6,missing,missing,hours/week,else,else,No./hours spent - walking work/school,"In a typical week in the past 3 months, how many hours did you usually spend walking to work or to school or while doing errands?", -PAC_4B,PAC_4B_cat6_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::PACA_4B, cchs2003_p::PACC_4B, cchs2005_p::PACE_4B",cat,1,6,None,None,hours/week,1,None,No. of hrs. biking - to work/school,"In a typical week, how much time did you usually spend bicycling to work or to school or while doing errands?", -PAC_4B,PAC_4B_cat6_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::PACA_4B, cchs2003_p::PACC_4B, cchs2005_p::PACE_4B",cat,2,6,Less than one hour,Less than one hour,hours/week,2,Less than one hour,No. of hrs. biking - to work/school,"In a typical week, how much time did you usually spend bicycling to work or to school or while doing errands?", -PAC_4B,PAC_4B_cat6_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::PACA_4B, cchs2003_p::PACC_4B, cchs2005_p::PACE_4B",cat,3,6,1-5 hours,1-5 hours,hours/week,3,1-5 hours,No. of hrs. biking - to work/school,"In a typical week, how much time did you usually spend bicycling to work or to school or while doing errands?", -PAC_4B,PAC_4B_cat6_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::PACA_4B, cchs2003_p::PACC_4B, cchs2005_p::PACE_4B",cat,4,6,6-10 hours,6-10 hours,hours/week,4,6-10 hours,No. of hrs. biking - to work/school,"In a typical week, how much time did you usually spend bicycling to work or to school or while doing errands?", -PAC_4B,PAC_4B_cat6_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::PACA_4B, cchs2003_p::PACC_4B, cchs2005_p::PACE_4B",cat,5,6,11-20 hours,11-20 hours,hours/week,5,11-20 hours,No. of hrs. biking - to work/school,"In a typical week, how much time did you usually spend bicycling to work or to school or while doing errands?", -PAC_4B,PAC_4B_cat6_6,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::PACA_4B, cchs2003_p::PACC_4B, cchs2005_p::PACE_4B",cat,6,6,More than 20 hours,More than 20 hours,hours/week,6,More than 20 hours,No. of hrs. biking - to work/school,"In a typical week, how much time did you usually spend bicycling to work or to school or while doing errands?", -PAC_4B,PAC_4B_cat6_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::PACA_4B, cchs2003_p::PACC_4B, cchs2005_p::PACE_4B",cat,NA::a,6,not applicable,not applicable,hours/week,96,not applicable,No. of hrs. biking - to work/school,"In a typical week, how much time did you usually spend bicycling to work or to school or while doing errands?", -PAC_4B,PAC_4B_cat6_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::PACA_4B, cchs2003_p::PACC_4B, cchs2005_p::PACE_4B",cat,NA::b,6,missing,missing,hours/week,"[97,99]",don't know (97); refusal (98); not stated (99),No. of hrs. biking - to work/school,"In a typical week, how much time did you usually spend bicycling to work or to school or while doing errands?", -PAC_4B,PAC_4B_cat6_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::PACA_4B, cchs2003_p::PACC_4B, cchs2005_p::PACE_4B",cat,NA::b,6,missing,missing,hours/week,else,else,No. of hrs. biking - to work/school,"In a typical week, how much time did you usually spend bicycling to work or to school or while doing errands?", -PAC_7,PAC_7_cat3_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_7],cat,1,3,Yes,Yes,N/A,1,Yes,Walked to work or school / last 3 mo.,[Other than the ( X ) times you already reported walking for exercise was there any other time / Was there any time] in the past 3 months when you walked to and from work or school?, -PAC_7,PAC_7_cat3_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_7],cat,2,3,No,No,N/A,2,No,Walked to work or school / last 3 mo.,[Other than the ( X ) times you already reported walking for exercise was there any other time / Was there any time] in the past 3 months when you walked to and from work or school?, -PAC_7,PAC_7_cat3_3,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_7],cat,3,3,No work/no school,No work/no school,N/A,3,No work/no school,Walked to work or school / last 3 mo.,[Other than the ( X ) times you already reported walking for exercise was there any other time / Was there any time] in the past 3 months when you walked to and from work or school?, -PAC_7,PAC_7_cat3_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_7],cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Walked to work or school / last 3 mo.,[Other than the ( X ) times you already reported walking for exercise was there any other time / Was there any time] in the past 3 months when you walked to and from work or school?, -PAC_7,PAC_7_cat3_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_7],cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Walked to work or school / last 3 mo.,[Other than the ( X ) times you already reported walking for exercise was there any other time / Was there any time] in the past 3 months when you walked to and from work or school?, -PAC_7,PAC_7_cat3_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_7],cat,NA::b,3,missing,missing,N/A,else,else,Walked to work or school / last 3 mo.,[Other than the ( X ) times you already reported walking for exercise was there any other time / Was there any time] in the past 3 months when you walked to and from work or school?, -PAC_7A,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_7A],cont,copy,N/A,No. of times/3 mo./walking work/school,No. of times walking work/school,N/A,"[1,270]",No. of times walking work/school,No. of times/3 mo./walking work/school,No. of times/3 mo./walking work/school, -PAC_7A,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_7A],cont,NA::a,N/A,not applicable,not applicable,N/A,996,not applicable,No. of times/3 mo./walking work/school,No. of times/3 mo./walking work/school, -PAC_7A,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_7A],cont,NA::b,N/A,missing,missing,N/A,"[997,999]",don't know (997); refusal (998); not stated (999),No. of times/3 mo./walking work/school,No. of times/3 mo./walking work/school, -PAC_7A,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_7A],cont,NA::b,N/A,missing,missing,N/A,else,else,No. of times/3 mo./walking work/school,No. of times/3 mo./walking work/school, -PAC_7B,PAC_7B_cat4_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_7B],cat,1,4,1 to 15 minutes,1 to 15 minutes,mins,1,1 to 15 minutes,Time spent - walking to go work/school,About how much time did you spend on each occasion?, -PAC_7B,PAC_7B_cat4_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_7B],cat,2,4,16 to 30 minutes,16 to 30 minutes,mins,2,16 to 30 minutes,Time spent - walking to go work/school,About how much time did you spend on each occasion?, -PAC_7B,PAC_7B_cat4_3,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_7B],cat,3,4,31 to 60 minutes,31 to 60 minutes,mins,3,31 to 60 minutes,Time spent - walking to go work/school,About how much time did you spend on each occasion?, -PAC_7B,PAC_7B_cat4_4,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_7B],cat,4,4,More than 1 hour,More than 1 hour,mins,4,More than 1 hour,Time spent - walking to go work/school,About how much time did you spend on each occasion?, -PAC_7B,PAC_7B_cat4_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_7B],cat,NA::a,4,not applicable,not applicable,mins,6,not applicable,Time spent - walking to go work/school,About how much time did you spend on each occasion?, -PAC_7B,PAC_7B_cat4_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_7B],cat,NA::b,4,missing,missing,mins,"[7,9]",don't know (7); refusal (8); not stated (9),Time spent - walking to go work/school,About how much time did you spend on each occasion?, -PAC_7B,PAC_7B_cat4_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_7B],cat,NA::b,4,missing,missing,mins,else,else,Time spent - walking to go work/school,About how much time did you spend on each occasion?, -PAC_8,PAC_8_cat3_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_8],cat,1,3,Yes,Yes,N/A,1,Yes,Bicycled to work or school / last 3 mo.,[Other than the ( X ) times you already reported bicycling was there any other time / Was there any other time] in the past 3 months when you bicycled to and from work or school?, -PAC_8,PAC_8_cat3_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_8],cat,2,3,No,No,N/A,2,No,Bicycled to work or school / last 3 mo.,[Other than the ( X ) times you already reported bicycling was there any other time / Was there any other time] in the past 3 months when you bicycled to and from work or school?, -PAC_8,PAC_8_cat3_3,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_8],cat,3,3,No work/no school,No work/no school,N/A,3,No work/no school,Bicycled to work or school / last 3 mo.,[Other than the ( X ) times you already reported bicycling was there any other time / Was there any other time] in the past 3 months when you bicycled to and from work or school?, -PAC_8,PAC_8_cat3_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_8],cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Bicycled to work or school / last 3 mo.,[Other than the ( X ) times you already reported bicycling was there any other time / Was there any other time] in the past 3 months when you bicycled to and from work or school?, -PAC_8,PAC_8_cat3_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_8],cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Bicycled to work or school / last 3 mo.,[Other than the ( X ) times you already reported bicycling was there any other time / Was there any other time] in the past 3 months when you bicycled to and from work or school?, -PAC_8,PAC_8_cat3_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_8],cat,NA::b,3,missing,missing,N/A,else,else,Bicycled to work or school / last 3 mo.,[Other than the ( X ) times you already reported bicycling was there any other time / Was there any other time] in the past 3 months when you bicycled to and from work or school?, -PAC_8A,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_8A],cont,copy,N/A,No. of times/3 mo./biking work/school,No. of times biking work/school,times/3 mos.,"[1,270]",No. of times biking work/school,No. of times/3 mo./bicycl. work/school,No. of times/3 mo./bicycl. work/school, -PAC_8A,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_8A],cont,NA::a,N/A,not applicable,not applicable,times/3 mos.,996,not applicable,No. of times/3 mo./bicycl. work/school,No. of times/3 mo./bicycl. work/school, -PAC_8A,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_8A],cont,NA::b,N/A,missing,missing,times/3 mos.,"[997,999]",don't know (997); refusal (998); not stated (999),No. of times/3 mo./bicycl. work/school,No. of times/3 mo./bicycl. work/school, -PAC_8A,N/A,cont,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_8A],cont,NA::b,N/A,missing,missing,times/3 mos.,else,else,No. of times/3 mo./bicycl. work/school,No. of times/3 mo./bicycl. work/school, -PAC_8B,PAC_8B_cat4_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_8B],cat,1,4,1 to 15 minutes,1 to 15 minutes,mins,1,1 to 15 minutes,Time spent - bicycl. to go work/school,About how much time did you spend on each occasion?, -PAC_8B,PAC_8B_cat4_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_8B],cat,2,4,16 to 30 minutes,16 to 30 minutes,mins,2,16 to 30 minutes,Time spent - bicycl. to go work/school,About how much time did you spend on each occasion?, -PAC_8B,PAC_8B_cat4_3,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_8B],cat,3,4,31 to 60 minutes,31 to 60 minutes,mins,3,31 to 60 minutes,Time spent - bicycl. to go work/school,About how much time did you spend on each occasion?, -PAC_8B,PAC_8B_cat4_4,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_8B],cat,4,4,More than 1 hour,More than 1 hour,mins,4,More than 1 hour,Time spent - bicycl. to go work/school,About how much time did you spend on each occasion?, -PAC_8B,PAC_8B_cat4_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_8B],cat,NA::a,4,not applicable,not applicable,mins,6,not applicable,Time spent - bicycl. to go work/school,About how much time did you spend on each occasion?, -PAC_8B,PAC_8B_cat4_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_8B],cat,NA::b,4,missing,missing,mins,"[7,9]",don't know (7); refusal (8); not stated (9),Time spent - bicycl. to go work/school,About how much time did you spend on each occasion?, -PAC_8B,PAC_8B_cat4_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",[PAC_8B],cat,NA::b,4,missing,missing,mins,else,else,Time spent - bicycl. to go work/school,About how much time did you spend on each occasion?, -PACDEE,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::PACADEE, cchs2003_p::PACCDEE, cchs2005_p::PACEDEE, [PACDEE]",cont,copy,N/A,Physical Activity,Average daily leisure time energy expenditure in METs,METS,"[0,43.5]",Daily energy expenditure - (D),Physical Activity,Daily energy expenditure - (D),Refer to energy_exp for PACDEE all cycles -PACDEE,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::PACADEE, cchs2003_p::PACCDEE, cchs2005_p::PACEDEE, [PACDEE]",cont,NA::a,N/A,not applicable,not applicable,METS,99.6,Not applicable,Physical Activity,Daily energy expenditure - (D), -PACDEE,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::PACADEE, cchs2003_p::PACCDEE, cchs2005_p::PACEDEE, [PACDEE]",cont,NA::b,N/A,missing,missing,METS,"[99.7,99.9]",don't know (99.7); refusal (99.8); not stated (99.9),Physical Activity,Daily energy expenditure - (D),Don't know (99.7) and refusal (99.8) not included in 2001 CCHS -PACDEE,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::PACADEE, cchs2003_p::PACCDEE, cchs2005_p::PACEDEE, [PACDEE]",cont,NA::b,N/A,missing,missing,METS,else,else,Physical Activity,Daily energy expenditure - (D), -PACDEE_cat3,PACDEE_cat3_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::PACADEE, cchs2003_p::PACCDEE, cchs2005_p::PACEDEE, [PACDEE]",cont,1,3,Inactive,Inactive - leisure activity,METS,"[0,1.5)",Inactive - leisure activity,Categorical physical activity,Categorical daily energy expenditure, -PACDEE_cat3,PACDEE_cat3_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::PACADEE, cchs2003_p::PACCDEE, cchs2005_p::PACEDEE, [PACDEE]",cont,2,3,Moderately active,Moderately active - leisure activity,METS,"[1.5,3)",Moderately active - leisure activity,Categorical physical activity,Categorical daily energy expenditure, -PACDEE_cat3,PACDEE_cat3_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::PACADEE, cchs2003_p::PACCDEE, cchs2005_p::PACEDEE, [PACDEE]",cont,3,3,Active,Active - leisure activity,METS,"[3,43.5]",Active - leisure activity,Categorical physical activity,Categorical daily energy expenditure, -PACDEE_cat3,PACDEE_cat3_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::PACADEE, cchs2003_p::PACCDEE, cchs2005_p::PACEDEE, [PACDEE]",cont,NA::a,3,not applicable,not applicable,METS,99.6,Not applicable,Categorical physical activity,Categorical daily energy expenditure, -PACDEE_cat3,PACDEE_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::PACADEE, cchs2003_p::PACCDEE, cchs2005_p::PACEDEE, [PACDEE]",cont,NA::b,3,missing,missing,METS,"[99.7,99.9]",don't know (99.7); refusal (99.8); not stated (99.9),Categorical physical activity,Categorical daily energy expenditure, -PACDEE_cat3,PACDEE_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::PACADEE, cchs2003_p::PACCDEE, cchs2005_p::PACEDEE, [PACDEE]",cont,NA::b,3,missing,missing,METS,else,else,Categorical physical activity,Categorical daily energy expenditure, -pack_years_der,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","DerivedVar::[SMKDSTY_A, DHHGAGE_cont, time_quit_smoking, SMKG203_cont, SMKG207_cont, SMK_204, SMK_05B, SMK_208, SMK_05C, SMKG01C_cont, SMK_01A]",N/A,Func::pack_years_fun,N/A,N/A,N/A,Years,N/A,N/A,Smoking pack-years,Smoking pack-years,PackYears variable derived from various harmonized smoking variables -pack_years_der,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","DerivedVar::[SMKDSTY_A, DHHGAGE_cont, time_quit_smoking, SMKG203_cont, SMKG207_cont, SMK_204, SMK_05B, SMK_208, SMK_05C, SMKG01C_cont, SMK_01A]",N/A,NA::b,N/A,missing,missing,Years,N/A,N/A,Smoking pack-years,Smoking pack-years, -pack_years_cat,pack_years_catN/A_Func::pack_years_fun_cat,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[pack_years_der],N/A,Func::pack_years_fun_cat,N/A,N/A,N/A,N/A,N/A,N/A,Categorical smoking pack-years,Categorical smoking pack-years, -pack_years_cat,pack_years_cat_cat8_1,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[pack_years_der],N/A,1,8,0,0 pack-years,pack-years,1,0 pack-years,Categorical smoking pack-years,Categorical smoking pack-years, -pack_years_cat,pack_years_cat_cat8_2,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[pack_years_der],N/A,2,8,0 to 0.01,0 to 0.01 pack-years,pack-years,2,0 to 0.01 pack-years,Categorical smoking pack-years,Categorical smoking pack-years, -pack_years_cat,pack_years_cat_cat8_3,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[pack_years_der],N/A,3,8,0.01 to 3.0,0.01 to 3.0 pack-years,pack-years,3,0.01 to 3.0 pack-years,Categorical smoking pack-years,Categorical smoking pack-years, -pack_years_cat,pack_years_cat_cat8_4,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[pack_years_der],N/A,4,8,3.0 to 9.0,3.0 to 9.0 pack-years,pack-years,4,3.0 to 9.0 pack-years,Categorical smoking pack-years,Categorical smoking pack-years, -pack_years_cat,pack_years_cat_cat8_5,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[pack_years_der],N/A,5,8,9.0 to 16.2,9.0 to 16.2 pack-years,pack-years,5,9.0 to 16.2 pack-years,Categorical smoking pack-years,Categorical smoking pack-years, -pack_years_cat,pack_years_cat_cat8_6,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[pack_years_der],N/A,6,8,16.2 to 25.7,16.2 to 25.7 pack-years,pack-years,6,16.2 to 25.7 pack-years,Categorical smoking pack-years,Categorical smoking pack-years, -pack_years_cat,pack_years_cat_cat8_7,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[pack_years_der],N/A,7,8,25.7 to 40.0,25.7 to 40.0 pack-years,pack-years,7,25.7 to 40.0 pack-years,Categorical smoking pack-years,Categorical smoking pack-years, -pack_years_cat,pack_years_cat_cat8_8,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[pack_years_der],N/A,8,8,40.0+,40.0+ pack-years,pack-years,8,40.0+ pack-years,Categorical smoking pack-years,Categorical smoking pack-years, -pack_years_cat,pack_years_cat_cat8_NA::a,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[pack_years_der],N/A,NA::a,8,not applicable,not applicable,pack-years,NA::a,not applicable,Categorical smoking pack-years,Categorical smoking pack-years, -pack_years_cat,pack_years_cat_cat8_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[pack_years_der],N/A,NA::b,8,missing,missing,pack-years,NA::b,missing,Categorical smoking pack-years,Categorical smoking pack-years, -PAYDVTOA,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAYDVTOA],cont,copy,N/A,No. minutes of other activities,No. minutes of other activities,minutes/week,"[0,4980]",No. minutes of other activities,Total minutes of other activities - 7 d,Total minutes of other activities - 7 d - (D), -PAYDVTOA,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAYDVTOA],cont,NA::a,N/A,not applicable,not applicable,minutes/week,99996,not applicable,Total minutes of other activities - 7 d,Total minutes of other activities - 7 d - (D), -PAYDVTOA,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAYDVTOA],cont,NA::b,N/A,missing,missing,minutes/week,"[99997,99999]",don't know (99997); refusal (99998); not stated (99999),Total minutes of other activities - 7 d,Total minutes of other activities - 7 d - (D), -PAYDVTOA,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAYDVTOA],cont,NA::b,N/A,missing,missing,minutes/week,else,else,Total minutes of other activities - 7 d,Total minutes of other activities - 7 d - (D), -PAYDVADL,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAYDVADL],cont,copy,N/A,No. minutes of leisure activities,No. minutes of leisure activities,minutes/week,"[0,4140]",No. minutes of leisure activities,Total minutes of physical activities during leisure over a week,Total minutes - physical activities during leisure - 7 d - (D), -PAYDVADL,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAYDVADL],cont,NA::a,N/A,not applicable,not applicable,minutes/week,99996,not applicable,Total minutes of physical activities during leisure over a week,Total minutes - physical activities during leisure - 7 d - (D), -PAYDVADL,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAYDVADL],cont,NA::b,N/A,missing,missing,minutes/week,"[99997,99999]",don't know (99997); refusal (99998); not stated (99999),Total minutes of physical activities during leisure over a week,Total minutes - physical activities during leisure - 7 d - (D), -PAYDVADL,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAYDVADL],cont,NA::b,N/A,missing,missing,minutes/week,else,else,Total minutes of physical activities during leisure over a week,Total minutes - physical activities during leisure - 7 d - (D), -PAYDVVIG,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAYDVVIG],cont,copy,N/A,No. minutes of vigorous activities,No. minutes of vigorous activities,minutes/week,"[0,2880]",No. minutes of vigorous activities,Total minutes of vigorous physical activity over a week,Total minutes - vigorous physical activity - 7 d - (D), -PAYDVVIG,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAYDVVIG],cont,NA::a,N/A,not applicable,not applicable,minutes/week,99996,not applicable,Total minutes of vigorous physical activity over a week,Total minutes - vigorous physical activity - 7 d - (D), -PAYDVVIG,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAYDVVIG],cont,NA::b,N/A,missing,missing,minutes/week,"[99997,99999]",don't know (99997); refusal (99998); not stated (99999),Total minutes of vigorous physical activity over a week,Total minutes - vigorous physical activity - 7 d - (D), -PAYDVVIG,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAYDVVIG],cont,NA::b,N/A,missing,missing,minutes/week,else,else,Total minutes of vigorous physical activity over a week,, -PAYDVDYS,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAYDVDYS],cont,copy,N/A,No. physically active days,No. physically active days,days,"[0,7]",No. physically active days,Number of days - physically active over a week,, -PAYDVDYS,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAYDVDYS],cont,NA::a,N/A,not applicable,not applicable,days,96,not applicable,Number of days - physically active over a week,Number of days - physically active - 7 d - (D), -PAYDVDYS,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAYDVDYS],cont,NA::b,N/A,missing,missing,days,"[97,99]",don't know (97); refusal (98); not stated (99),Number of days - physically active over a week,Number of days - physically active - 7 d - (D), -PAYDVDYS,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[PAYDVDYS],cont,NA::b,N/A,missing,missing,days,else,else,Number of days - physically active over a week,Number of days - physically active - 7 d - (D), -pct_time_der,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHHGAGE_cont, SDCGCBG, SDCGRES]",N/A,Func::pct_time_fun,N/A,N/A,N/A,%,N/A,N/A,Percent time in Canada,Percentage of time in Canada,"Percent time in Canada derived from Age, immigration status, and time in Canada variables" -pct_time_der,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[DHHGAGE_cont, SDCGCBG, SDCGRES]",N/A,NA::b,N/A,missing,missing,%,N/A,N/A,Percent time in Canada,Percentage of time in Canada, -pct_time_der_cat10,pct_time_der_cat10N/A_Func::pct_time_fun_cat,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[pct_time_der],N/A,Func::pct_time_fun_cat,N/A,N/A,N/A,N/A,N/A,N/A,Categorical percent time in Canada,Categorical percentage of time in Canada,Categorical percent time in Canada derived from pct_time_der -pct_time_der_cat10,pct_time_der_cat10_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[pct_time_der],N/A,1,10,10%,10% time in Canada,%,1,10% time in Canada,Categorical percent time in Canada,Categorical percentage of time in Canada, -pct_time_der_cat10,pct_time_der_cat10_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[pct_time_der],N/A,2,10,20%,20% time in Canada,%,2,20% time in Canada,Categorical percent time in Canada,Categorical percentage of time in Canada, -pct_time_der_cat10,pct_time_der_cat10_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[pct_time_der],N/A,3,10,30%,30% time in Canada,%,3,30% time in Canada,Categorical percent time in Canada,Categorical percentage of time in Canada, -pct_time_der_cat10,pct_time_der_cat10_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[pct_time_der],N/A,4,10,40%,40% time in Canada,%,4,40% time in Canada,Categorical percent time in Canada,Categorical percentage of time in Canada, -pct_time_der_cat10,pct_time_der_cat10_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[pct_time_der],N/A,5,10,50%,50% time in Canada,%,5,50% time in Canada,Categorical percent time in Canada,Categorical percentage of time in Canada, -pct_time_der_cat10,pct_time_der_cat10_6,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[pct_time_der],N/A,6,10,60%,60% time in Canada,%,6,60% time in Canada,Categorical percent time in Canada,Categorical percentage of time in Canada, -pct_time_der_cat10,pct_time_der_cat10_7,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[pct_time_der],N/A,7,10,70%,70% time in Canada,%,7,70% time in Canada,Categorical percent time in Canada,Categorical percentage of time in Canada, -pct_time_der_cat10,pct_time_der_cat10_8,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[pct_time_der],N/A,8,10,80%,80% time in Canada,%,8,80% time in Canada,Categorical percent time in Canada,Categorical percentage of time in Canada, -pct_time_der_cat10,pct_time_der_cat10_9,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[pct_time_der],N/A,9,10,90%,90% time in Canada,%,9,90% time in Canada,Categorical percent time in Canada,Categorical percentage of time in Canada, -pct_time_der_cat10,pct_time_der_cat10_10,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[pct_time_der],N/A,10,10,100%,100% time in Canada,%,10,100% time in Canada,Categorical percent time in Canada,Categorical percentage of time in Canada, -pct_time_der_cat10,pct_time_der_cat10_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[pct_time_der],N/A,NA::a,10,not applicable,not applicable,%,NA::a,not applicable,Categorical percent time in Canada,Categorical percentage of time in Canada, -pct_time_der_cat10,pct_time_der_cat10_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p",DerivedVar::[pct_time_der],N/A,NA::b,10,missing,missing,%,NA::b,missing,Categorical percent time in Canada,Categorical percentage of time in Canada, -RAC_1,RAC_1_cat3_1,cat,"cchs2001_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_1, cchs2003_p::RACC_1, cchs2005_p::RACE_1, [RAC_1]",cat,1,3,Sometimes,Sometimes,N/A,1,Sometimes,Has difficulty with activities,"Do you have any difficulty hearing, seeing, communicating, walking, climbing stairs, bending, learning or doing any similar activities?", -RAC_1,RAC_1_cat3_2,cat,"cchs2001_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_1, cchs2003_p::RACC_1, cchs2005_p::RACE_1, [RAC_1]",cat,2,3,Often,Often,N/A,2,Often,Has difficulty with activities,"Do you have any difficulty hearing, seeing, communicating, walking, climbing stairs, bending, learning or doing any similar activities?", -RAC_1,RAC_1_cat3_3,cat,"cchs2001_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_1, cchs2003_p::RACC_1, cchs2005_p::RACE_1, [RAC_1]",cat,3,3,Never,Never,N/A,3,Never,Has difficulty with activities,"Do you have any difficulty hearing, seeing, communicating, walking, climbing stairs, bending, learning or doing any similar activities?", -RAC_1,RAC_1_cat3_NA::a,cat,"cchs2001_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_1, cchs2005_p::RACE_1, [RAC_1]",cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Has difficulty with activities,"Do you have any difficulty hearing, seeing, communicating, walking, climbing stairs, bending, learning or doing any similar activities?", -RAC_1,RAC_1_cat3_NA::b,cat,"cchs2001_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_1, cchs2005_p::RACE_1, [RAC_1]",cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Has difficulty with activities,"Do you have any difficulty hearing, seeing, communicating, walking, climbing stairs, bending, learning or doing any similar activities?", -RAC_1,RAC_1_cat3_NA::b,cat,"cchs2001_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_1, cchs2005_p::RACE_1, [RAC_1]",cat,NA::b,3,missing,missing,N/A,else,else,Has difficulty with activities,"Do you have any difficulty hearing, seeing, communicating, walking, climbing stairs, bending, learning or doing any similar activities?", -RAC_1,RAC_1_cat3_NA::a,cat,cchs2003_p,cchs2003_p::RACC_1,cat,NA::a,3,not applicable,not applicable,N/A,96,not applicable,Has difficulty with activities,"Do you have any difficulty hearing, seeing, communicating, walking, climbing stairs, bending, learning or doing any similar activities?",CCHS 2003 codes N/A as 96 and missing as 97-99 -RAC_1,RAC_1_cat3_NA::b,cat,cchs2003_p,cchs2003_p::RACC_1,cat,NA::b,3,missing,missing,N/A,"[97,99]",don't know (97); refusal (98); not stated (99),Has difficulty with activities,"Do you have any difficulty hearing, seeing, communicating, walking, climbing stairs, bending, learning or doing any similar activities?", -RAC_1,RAC_1_cat3_NA::b,cat,cchs2003_p,cchs2003_p::RACC_1,cat,NA::b,3,missing,missing,N/A,else,else,Has difficulty with activities,"Do you have any difficulty hearing, seeing, communicating, walking, climbing stairs, bending, learning or doing any similar activities?", -RAC_2A,RAC_2A_cat3_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_2A, cchs2003_p::RACC_2A, cchs2005_p::RACE_2A, [RAC_2A]",cat,1,3,Sometimes,Sometimes,N/A,1,Sometimes,Reduction - activities at home,Does a long-term physical condition or mental condition or health problem reduce the amount or the kind of activity you can do at home?, -RAC_2A,RAC_2A_cat3_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_2A, cchs2003_p::RACC_2A, cchs2005_p::RACE_2A, [RAC_2A]",cat,2,3,Often,Often,N/A,2,Often,Reduction - activities at home,Does a long-term physical condition or mental condition or health problem reduce the amount or the kind of activity you can do at home?, -RAC_2A,RAC_2A_cat3_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_2A, cchs2003_p::RACC_2A, cchs2005_p::RACE_2A, [RAC_2A]",cat,3,3,Never,Never,N/A,3,Never,Reduction - activities at home,Does a long-term physical condition or mental condition or health problem reduce the amount or the kind of activity you can do at home?, -RAC_2A,RAC_2A_cat3_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_2A, cchs2003_p::RACC_2A, cchs2005_p::RACE_2A, [RAC_2A]",cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Reduction - activities at home,Does a long-term physical condition or mental condition or health problem reduce the amount or the kind of activity you can do at home?, -RAC_2A,RAC_2A_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_2A, cchs2003_p::RACC_2A, cchs2005_p::RACE_2A, [RAC_2A]",cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Reduction - activities at home,Does a long-term physical condition or mental condition or health problem reduce the amount or the kind of activity you can do at home?, -RAC_2A,RAC_2A_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_2A, cchs2003_p::RACC_2A, cchs2005_p::RACE_2A, [RAC_2A]",cat,NA::b,3,missing,missing,N/A,else,else,Reduction - activities at home,Does a long-term physical condition or mental condition or health problem reduce the amount or the kind of activity you can do at home?, -RAC_2B,RAC_2B_cat3_1,cat,cchs2001_p,cchs2001_p::RACA_2B,cat,1,3,Sometimes,Sometimes,N/A,1,Sometimes,Reduction - activities at work or school,Does a long-term physical condition or mental condition or health problem reduce the amount or the kind of activity you can do at work or at school?,"In CCHS 2001, work and school reduction were combined into one variable. From CCHS 2003 onwards they were split into 2 variables (RAC_2B1 & RAC_2B2)" -RAC_2B,RAC_2B_cat3_2,cat,cchs2001_p,cchs2001_p::RACA_2B,cat,2,3,Often,Often,N/A,2,Often,Reduction - activities at work or school,Does a long-term physical condition or mental condition or health problem reduce the amount or the kind of activity you can do at work or at school?, -RAC_2B,RAC_2B_cat3_3,cat,cchs2001_p,cchs2001_p::RACA_2B,cat,3,3,Never,Never,N/A,3,Never,Reduction - activities at work or school,Does a long-term physical condition or mental condition or health problem reduce the amount or the kind of activity you can do at work or at school?, -RAC_2B,RAC_2B_cat3_NA::a,cat,cchs2001_p,cchs2001_p::RACA_2B,cat,NA::a,3,not applicable,not applicable,N/A,4,not applicable,Reduction - activities at work or school,Does a long-term physical condition or mental condition or health problem reduce the amount or the kind of activity you can do at work or at school?, -RAC_2B,RAC_2B_cat3_NA::b,cat,cchs2001_p,cchs2001_p::RACA_2B,cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Reduction - activities at work or school,Does a long-term physical condition or mental condition or health problem reduce the amount or the kind of activity you can do at work or at school?, -RAC_2B,RAC_2B_cat3_NA::b,cat,cchs2001_p,cchs2001_p::RACA_2B,cat,NA::b,3,missing,missing,N/A,else,else,Reduction - activities at work or school,Does a long-term physical condition or mental condition or health problem reduce the amount or the kind of activity you can do at work or at school?, -RAC_2B1,RAC_2B1_cat4_1,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACC_2B1, cchs2005_p::RACE_2B1, [RAC_2B1]",cat,1,4,Sometimes,Sometimes,N/A,1,Sometimes,Long-term cond. reduces act. - school,"Does a long-term physical condition or mental condition or health problem, reduce the amount or the kind of activity you can do at school?", -RAC_2B1,RAC_2B1_cat4_2,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACC_2B1, cchs2005_p::RACE_2B1, [RAC_2B1]",cat,2,4,Often,Often,N/A,2,Often,Long-term cond. reduces act. - school,"Does a long-term physical condition or mental condition or health problem, reduce the amount or the kind of activity you can do at school?", -RAC_2B1,RAC_2B1_cat4_3,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACC_2B1, cchs2005_p::RACE_2B1, [RAC_2B1]",cat,3,4,Never,Never,N/A,3,Never,Long-term cond. reduces act. - school,"Does a long-term physical condition or mental condition or health problem, reduce the amount or the kind of activity you can do at school?", -RAC_2B1,RAC_2B1_cat4_4,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACC_2B1, cchs2005_p::RACE_2B1, [RAC_2B1]",cat,4,4,Not attend school,Not attend school,N/A,4,Not attend school,Long-term cond. reduces act. - school,"Does a long-term physical condition or mental condition or health problem, reduce the amount or the kind of activity you can do at school?", -RAC_2B1,RAC_2B1_cat4_NA::a,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACC_2B1, cchs2005_p::RACE_2B1, [RAC_2B1]",cat,NA::a,4,not applicable,not applicable,N/A,6,not applicable,Long-term cond. reduces act. - school,"Does a long-term physical condition or mental condition or health problem, reduce the amount or the kind of activity you can do at school?", -RAC_2B1,RAC_2B1_cat4_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACC_2B1, cchs2005_p::RACE_2B1, [RAC_2B1]",cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Long-term cond. reduces act. - school,"Does a long-term physical condition or mental condition or health problem, reduce the amount or the kind of activity you can do at school?", -RAC_2B1,RAC_2B1_cat4_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACC_2B1, cchs2005_p::RACE_2B1, [RAC_2B1]",cat,NA::b,4,missing,missing,N/A,else,else,Long-term cond. reduces act. - school,"Does a long-term physical condition or mental condition or health problem, reduce the amount or the kind of activity you can do at school?", -RAC_2B2,RAC_2B2_cat4_1,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACC_2B2, cchs2005_p::RACE_2B2, [RAC_2B2]",cat,1,4,Sometimes,missing,N/A,1,Sometimes,Reduction kind/amount act. - at work,"Does a long-term physical condition or mental condition or health problem, reduce the amount or the kind of activity you can do at work?", -RAC_2B2,RAC_2B2_cat4_2,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACC_2B2, cchs2005_p::RACE_2B2, [RAC_2B2]",cat,2,4,Often,Often,N/A,2,Often,Reduction kind/amount act. - at work,"Does a long-term physical condition or mental condition or health problem, reduce the amount or the kind of activity you can do at work?", -RAC_2B2,RAC_2B2_cat4_3,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACC_2B2, cchs2005_p::RACE_2B2, [RAC_2B2]",cat,3,4,Never,Never,N/A,3,Never,Reduction kind/amount act. - at work,"Does a long-term physical condition or mental condition or health problem, reduce the amount or the kind of activity you can do at work?", -RAC_2B2,RAC_2B2_cat4_4,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACC_2B2, cchs2005_p::RACE_2B2, [RAC_2B2]",cat,4,4,Has no job,Has no job,N/A,4,Has no job,Reduction kind/amount act. - at work,"Does a long-term physical condition or mental condition or health problem, reduce the amount or the kind of activity you can do at work?", -RAC_2B2,RAC_2B2_cat4_NA::a,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACC_2B2, cchs2005_p::RACE_2B2, [RAC_2B2]",cat,NA::a,4,not applicable,not applicable,N/A,6,not applicable,Reduction kind/amount act. - at work,"Does a long-term physical condition or mental condition or health problem, reduce the amount or the kind of activity you can do at work?", -RAC_2B2,RAC_2B2_cat4_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACC_2B2, cchs2005_p::RACE_2B2, [RAC_2B2]",cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Reduction kind/amount act. - at work,"Does a long-term physical condition or mental condition or health problem, reduce the amount or the kind of activity you can do at work?", -RAC_2B2,RAC_2B2_cat4_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACC_2B2, cchs2005_p::RACE_2B2, [RAC_2B2]",cat,NA::b,4,missing,missing,N/A,else,else,Reduction kind/amount act. - at work,"Does a long-term physical condition or mental condition or health problem, reduce the amount or the kind of activity you can do at work?", -RAC_2C,RAC_2C_cat3_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_2C, cchs2003_p::RACC_2C, cchs2005_p::RACE_2C, [RAC_2C]",cat,1,3,Sometimes,Sometimes,N/A,1,Sometimes,Reduction - other activities,"Does a long-term physical condition or mental condition or health problem reduce the amount or the kind of activity you can do in other activities, for example, transportation or leisure?", -RAC_2C,RAC_2C_cat3_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_2C, cchs2003_p::RACC_2C, cchs2005_p::RACE_2C, [RAC_2C]",cat,2,3,Often,Often,N/A,2,Often,Reduction - other activities,"Does a long-term physical condition or mental condition or health problem reduce the amount or the kind of activity you can do in other activities, for example, transportation or leisure?", -RAC_2C,RAC_2C_cat3_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_2C, cchs2003_p::RACC_2C, cchs2005_p::RACE_2C, [RAC_2C]",cat,3,3,Never,Never,N/A,3,Never,Reduction - other activities,"Does a long-term physical condition or mental condition or health problem reduce the amount or the kind of activity you can do in other activities, for example, transportation or leisure?", -RAC_2C,RAC_2C_cat3_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_2C, cchs2003_p::RACC_2C, cchs2005_p::RACE_2C, [RAC_2C]",cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Reduction - other activities,"Does a long-term physical condition or mental condition or health problem reduce the amount or the kind of activity you can do in other activities, for example, transportation or leisure?", -RAC_2C,RAC_2C_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_2C, cchs2003_p::RACC_2C, cchs2005_p::RACE_2C, [RAC_2C]",cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Reduction - other activities,"Does a long-term physical condition or mental condition or health problem reduce the amount or the kind of activity you can do in other activities, for example, transportation or leisure?", -RAC_2C,RAC_2C_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACA_2C, cchs2003_p::RACC_2C, cchs2005_p::RACE_2C, [RAC_2C]",cat,NA::b,3,missing,missing,N/A,else,else,Reduction - other activities,"Does a long-term physical condition or mental condition or health problem reduce the amount or the kind of activity you can do in other activities, for example, transportation or leisure?", -RACAG5,RACAG5_cat4_1,cat,cchs2001_p,cchs2001_p::RACAG5,cat,1,4,Injury,Injury,N/A,1,Injury,Cause of health problem - (G),Cause of health problem - (G),"CCHS 2001 has different categories from other cycles, hence a new variable created" -RACAG5,RACAG5_cat4_2,cat,cchs2001_p,cchs2001_p::RACAG5,cat,2,4,Disease/illness,Disease/illness,N/A,2,Disease/illness,Cause of health problem - (G),Cause of health problem - (G), -RACAG5,RACAG5_cat4_3,cat,cchs2001_p,cchs2001_p::RACAG5,cat,3,4,Aging,Aging,N/A,3,Aging,Cause of health problem - (G),Cause of health problem - (G), -RACAG5,RACAG5_cat4_4,cat,cchs2001_p,cchs2001_p::RACAG5,cat,4,4,Other,Other,N/A,4,Other,Cause of health problem - (G),Cause of health problem - (G), -RACAG5,RACAG5_cat4_NA::a,cat,cchs2001_p,cchs2001_p::RACAG5,cat,NA::a,4,not applicable,not applicable,N/A,6,not applicable,Cause of health problem - (G),Cause of health problem - (G), -RACAG5,RACAG5_cat4_NA::b,cat,cchs2001_p,cchs2001_p::RACAG5,cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Cause of health problem - (G),Cause of health problem - (G), -RACAG5,RACAG5_cat4_NA::b,cat,cchs2001_p,cchs2001_p::RACAG5,cat,NA::b,4,missing,missing,N/A,else,else,Cause of health problem - (G),Cause of health problem - (G), -RACDIMP,RACDIMP_cat3_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACADIMP, cchs2003_p::RACCDIMP, cchs2005_p::RACEDIMP, [RACDIMP]",cat,1,3,Sometimes,Sometimes,N/A,1,Sometimes,Impact of health problems,Impact of health problems, -RACDIMP,RACDIMP_cat3_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACADIMP, cchs2003_p::RACCDIMP, cchs2005_p::RACEDIMP, [RACDIMP]",cat,2,3,Often,Often,N/A,2,Often,Impact of health problems,Impact of health problems, -RACDIMP,RACDIMP_cat3_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACADIMP, cchs2003_p::RACCDIMP, cchs2005_p::RACEDIMP, [RACDIMP]",cat,3,3,Never,Never,N/A,3,Never,Impact of health problems,Impact of health problems, -RACDIMP,RACDIMP_cat3_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACADIMP, cchs2003_p::RACCDIMP, cchs2005_p::RACEDIMP, [RACDIMP]",cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Impact of health problems,Impact of health problems, -RACDIMP,RACDIMP_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACADIMP, cchs2003_p::RACCDIMP, cchs2005_p::RACEDIMP, [RACDIMP]",cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Impact of health problems,Impact of health problems, -RACDIMP,RACDIMP_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::RACADIMP, cchs2003_p::RACCDIMP, cchs2005_p::RACEDIMP, [RACDIMP]",cat,NA::b,3,missing,missing,N/A,else,else,Impact of health problems,Impact of health problems, -RACDPAL,RACDPAL_catN/A_Func::RACDPAL_fun,cat,cchs2001_p,"DerivedVar::[RAC_1, RAC_2A, RAC_2B, RAC_2C]",N/A,Func::RACDPAL_fun,N/A,N/A,N/A,N/A,N/A,N/A,Participation and activity limitation,Participation and activity limitation, -RACDPAL,RACDPAL_cat3_1,cat,cchs2001_p,"DerivedVar::[RAC_1, RAC_2A, RAC_2B, RAC_2C]",N/A,1,3,Sometimes,Sometimes,N/A,N/A,Participation and activity limitation,Participation and activity limitation,Participation and activity limitation, -RACDPAL,RACDPAL_cat3_2,cat,cchs2001_p,"DerivedVar::[RAC_1, RAC_2A, RAC_2B, RAC_2C]",N/A,2,3,Often,Often,N/A,N/A,Participation and activity limitation,Participation and activity limitation,Participation and activity limitation, -RACDPAL,RACDPAL_cat3_3,cat,cchs2001_p,"DerivedVar::[RAC_1, RAC_2A, RAC_2B, RAC_2C]",N/A,3,3,Never,Never,N/A,N/A,Participation and activity limitation,Participation and activity limitation,Participation and activity limitation, -RACDPAL,RACDPAL_cat3_NA::b,cat,cchs2001_p,"DerivedVar::[RAC_1, RAC_2A, RAC_2B, RAC_2C]",N/A,NA::b,3,missing,missing,N/A,N/A,Participation and activity limitation,Participation and activity limitation,Participation and activity limitation, -RACDPAL,RACDPAL_cat3_1,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACCDPAL, cchs2005_p::RACEDPAL, [RACDPAL]",cat,1,3,Sometimes,Sometimes,N/A,1,Sometimes,Participation and activity limitation,Participation and activity limitation, -RACDPAL,RACDPAL_cat3_2,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACCDPAL, cchs2005_p::RACEDPAL, [RACDPAL]",cat,2,3,Often,Often,N/A,2,Often,Participation and activity limitation,Participation and activity limitation, -RACDPAL,RACDPAL_cat3_3,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACCDPAL, cchs2005_p::RACEDPAL, [RACDPAL]",cat,3,3,Never,Never,N/A,3,Never,Participation and activity limitation,Participation and activity limitation, -RACDPAL,RACDPAL_cat3_NA::a,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACCDPAL, cchs2005_p::RACEDPAL, [RACDPAL]",cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Participation and activity limitation,Participation and activity limitation, -RACDPAL,RACDPAL_cat3_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACCDPAL, cchs2005_p::RACEDPAL, [RACDPAL]",cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Participation and activity limitation,Participation and activity limitation, -RACDPAL,RACDPAL_cat3_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACCDPAL, cchs2005_p::RACEDPAL, [RACDPAL]",cat,NA::b,3,missing,missing,N/A,else,else,Participation and activity limitation,Participation and activity limitation, -RACG5,RACG5_cat6_1,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACCG5, cchs2005_p::RACEG5, [RACG5]",cat,1,6,Injury,Injury,N/A,1,Injury,Cause of health problem,Cause of health problem, -RACG5,RACG5_cat6_2,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACCG5, cchs2005_p::RACEG5, [RACG5]",cat,2,6,Disease/illness,Disease/illness,N/A,2,Disease/illness,Cause of health problem,Cause of health problem, -RACG5,RACG5_cat6_3,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACCG5, cchs2005_p::RACEG5, [RACG5]",cat,3,6,Aging,Aging,N/A,3,Aging,Cause of health problem,Cause of health problem, -RACG5,RACG5_cat6_4,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACCG5, cchs2005_p::RACEG5, [RACG5]",cat,4,6,Existed at birth,Existed at birth,N/A,4,Existed at birth,Cause of health problem,Cause of health problem, -RACG5,RACG5_cat6_5,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACCG5, cchs2005_p::RACEG5, [RACG5]",cat,5,6,Work conditions,Work conditions,N/A,5,Work conditions,Cause of health problem,Cause of health problem, -RACG5,RACG5_cat6_6,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACCG5, cchs2005_p::RACEG5, [RACG5]",cat,6,6,Other,Other,N/A,6,Other,Cause of health problem,Cause of health problem, -RACG5,RACG5_cat6_NA::a,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACCG5, cchs2005_p::RACEG5, [RACG5]",cat,NA::a,6,not applicable,not applicable,N/A,96,not applicable,Cause of health problem,Cause of health problem, -RACG5,RACG5_cat6_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACCG5, cchs2005_p::RACEG5, [RACG5]",cat,NA::b,6,missing,missing,N/A,"[97,99]",don't know (97); refusal (98); not stated (99),Cause of health problem,Cause of health problem, -RACG5,RACG5_cat6_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::RACCG5, cchs2005_p::RACEG5, [RACG5]",cat,NA::b,6,missing,missing,N/A,else,else,Cause of health problem,Cause of health problem, -resp_condition_der,resp_condition_der_catN/A_Func::resp_condition_fun1,cat,"cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","DerivedVar::[DHHGAGE_cont, CCC_091, CCC_031]",N/A,Func::resp_condition_fun1,N/A,N/A,N/A,N/A,N/A,N/A,Respiratory Condition,Respiratory Condition,"Derived from Bronchitis, COPD and Emphysema variables" -resp_condition_der,resp_condition_der_catN/A_Func::resp_condition_fun2,cat,"cchs2005_p, cchs2007_2008_p","DerivedVar::[DHHGAGE_cont, CCC_91E, CCC_91F, CCC_91A, CCC_031]",N/A,Func::resp_condition_fun2,N/A,N/A,N/A,N/A,N/A,N/A,Respiratory Condition,Respiratory Condition,"Derived from Bronchitis, COPD and Emphysema variables" -resp_condition_der,resp_condition_der_catN/A_Func::resp_condition_fun3,cat,"cchs2001_p, cchs2003_p","DerivedVar::[DHHGAGE_cont, CCC_091, CCC_91A, CCC_031]",N/A,Func::resp_condition_fun3,N/A,N/A,N/A,N/A,N/A,N/A,Respiratory Condition,Respiratory Condition,"Derived from Bronchitis, COPD and Emphysema variables" -resp_condition_der,resp_condition_der_cat3_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","DerivedVar::[DHHGAGE_cont, CCC_091, CCC_91E, CCC_91F, CCC_91A, CCC_031]",N/A,1,3,Over 35 years with condition,Age over 35 years with condition,N/A,N/A,Respiratory Condition,Respiratory Condition,Respiratory Condition, -resp_condition_der,resp_condition_der_cat3_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","DerivedVar::[DHHGAGE_cont, CCC_091, CCC_91E, CCC_91F, CCC_91A, CCC_031]",N/A,2,3,Under 35 years with condition,Age under 35 years with condition,N/A,N/A,Respiratory Condition,Respiratory Condition,Respiratory Condition, -resp_condition_der,resp_condition_der_cat3_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","DerivedVar::[DHHGAGE_cont, CCC_091, CCC_91E, CCC_91F, CCC_91A, CCC_031]",N/A,3,3,No condition,No condition,N/A,N/A,Respiratory Condition,Respiratory Condition,Respiratory Condition, -resp_condition_der,resp_condition_der_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","DerivedVar::[DHHGAGE_cont, CCC_091, CCC_91E, CCC_91F, CCC_91A, CCC_031]",N/A,NA::b,3,missing,missing,N/A,N/A,Respiratory Condition,Respiratory Condition,Respiratory Condition, -resp_condition_der,resp_condition_der_cat3_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","DerivedVar::[DHHGAGE_cont, CCC_091, CCC_91E, CCC_91F, CCC_91A, CCC_031]",N/A,NA::a,3,not applicable,not applicable,N/A,N/A,Respiratory Condition,Respiratory Condition,Respiratory Condition, -SDC_5A_1,SDC_5A_1_cat4_1,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SDC_025, cchs2017_2018_p::SDC_025, [SDC_5A_1]",cat,1,4,English ,English only,N/A,1,English ,Knowledge of official languages,"Of English or French, which language(s) do you speak well enough to conduct a conversation?", -SDC_5A_1,SDC_5A_1_cat4_2,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SDC_025, cchs2017_2018_p::SDC_025, [SDC_5A_1]",cat,2,4,French,French only,N/A,2,French,Knowledge of official languages,"Of English or French, which language(s) do you speak well enough to conduct a conversation?", -SDC_5A_1,SDC_5A_1_cat4_3,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SDC_025, cchs2017_2018_p::SDC_025, [SDC_5A_1]",cat,3,4,English & French,English & French,N/A,3,English & French,Knowledge of official languages,"Of English or French, which language(s) do you speak well enough to conduct a conversation?", -SDC_5A_1,SDC_5A_1_cat4_4,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SDC_025, cchs2017_2018_p::SDC_025, [SDC_5A_1]",cat,4,4,Neither,Neither English nor French,N/A,4,Neither,Knowledge of official languages,"Of English or French, which language(s) do you speak well enough to conduct a conversation?", -SDC_5A_1,SDC_5A_1_cat4_NA::a,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SDC_025, cchs2017_2018_p::SDC_025, [SDC_5A_1]",cat,NA::a,4,not applicable,not applicable,N/A,6,not applicable,Knowledge of official languages,"Of English or French, which language(s) do you speak well enough to conduct a conversation?", -SDC_5A_1,SDC_5A_1_cat4_NA::b,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SDC_025, cchs2017_2018_p::SDC_025, [SDC_5A_1]",cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Knowledge of official languages,"Of English or French, which language(s) do you speak well enough to conduct a conversation?", -SDC_5A_1,SDC_5A_1_cat4_NA::b,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SDC_025, cchs2017_2018_p::SDC_025, [SDC_5A_1]",cat,NA::b,4,missing,missing,N/A,else,else,Knowledge of official languages,"Of English or French, which language(s) do you speak well enough to conduct a conversation?", -SDCDFOLS,SDCDFOLS_cat4_1,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SDCDVFLS, cchs2017_2018_p::SDCDVFLS, [SDCDFOLS]",cat,1,4,English ,English only,N/A,1,English ,First official language spoken,First official language spoken, -SDCDFOLS,SDCDFOLS_cat4_2,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SDCDVFLS, cchs2017_2018_p::SDCDVFLS, [SDCDFOLS]",cat,2,4,French,French only,N/A,2,French,First official language spoken,First official language spoken, -SDCDFOLS,SDCDFOLS_cat4_3,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SDCDVFLS, cchs2017_2018_p::SDCDVFLS, [SDCDFOLS]",cat,3,4,English & French,English & French,N/A,3,English & French,First official language spoken,First official language spoken, -SDCDFOLS,SDCDFOLS_cat4_4,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SDCDVFLS, cchs2017_2018_p::SDCDVFLS, [SDCDFOLS]",cat,4,4,Neither,Neither English nor French,N/A,4,Neither,First official language spoken,First official language spoken, -SDCDFOLS,SDCDFOLS_cat4_NA::a,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SDCDVFLS, cchs2017_2018_p::SDCDVFLS, [SDCDFOLS]",cat,NA::a,4,not applicable,not applicable,N/A,6,not applicable,First official language spoken,First official language spoken,"CCHS2015_2016 and CCHS2017_2018 does not have not applicable (6), don't know (7) or refusal (8)" -SDCDFOLS,SDCDFOLS_cat4_NA::b,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SDCDVFLS, cchs2017_2018_p::SDCDVFLS, [SDCDFOLS]",cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),First official language spoken,First official language spoken,"CCHS2015_2016 and CCHS2017_2018 does not have not applicable (6), don't know (7) or refusal (8)" -SDCDFOLS,SDCDFOLS_cat4_NA::b,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SDCDVFLS, cchs2017_2018_p::SDCDVFLS, [SDCDFOLS]",cat,NA::b,4,missing,missing,N/A,else,else,First official language spoken,First official language spoken, -SDCFIMM,SDCFIMM_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SDCAFIMM, cchs2003_p::SDCCFIMM, cchs2005_p::SDCEFIMM, cchs2015_2016_p::SDCDVIMM, cchs2017_2018_p::SDCDVIMM, [SDCFIMM]",cat,1,2,Yes,Yes,N/A,1,Yes,Immigrant status (D),Are you an immigrant?, -SDCFIMM,SDCFIMM_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SDCAFIMM, cchs2003_p::SDCCFIMM, cchs2005_p::SDCEFIMM, cchs2015_2016_p::SDCDVIMM, cchs2017_2018_p::SDCDVIMM, [SDCFIMM]",cat,2,2,No,No,N/A,2,No,Immigrant status (D),Are you an immigrant?, -SDCFIMM,SDCFIMM_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SDCAFIMM, cchs2003_p::SDCCFIMM, cchs2005_p::SDCEFIMM, cchs2015_2016_p::SDCDVIMM, cchs2017_2018_p::SDCDVIMM, [SDCFIMM]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Immigrant status (D),Are you an immigrant?, -SDCFIMM,SDCFIMM_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SDCAFIMM, cchs2003_p::SDCCFIMM, cchs2005_p::SDCEFIMM, cchs2015_2016_p::SDCDVIMM, cchs2017_2018_p::SDCDVIMM, [SDCFIMM]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Immigrant status (D),Are you an immigrant?, -SDCFIMM,SDCFIMM_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SDCAFIMM, cchs2003_p::SDCCFIMM, cchs2005_p::SDCEFIMM, cchs2015_2016_p::SDCDVIMM, cchs2017_2018_p::SDCDVIMM, [SDCFIMM]",cat,NA::b,2,missing,missing,N/A,else,else,Immigrant status (D),Are you an immigrant?, -SDCGCBG,SDCGCBG_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SDCAGCBG, cchs2003_p::SDCCGCBG, cchs2005_p::SDCEGCBG, cchs2011_2012_p::SDCGCB12, cchs2012_p::SDCGCB12, cchs2013_2014_p::SDCGCB13, cchs2014_p::SDCGCB13, cchs2015_2016_p::SDCDGCB, cchs2017_2018_p::SDCDGCB, [SDCGCBG]",cat,1,2,Canada,Canada,N/A,1,Canada,Country of birth - (G),Country of birth - (G), -SDCGCBG,SDCGCBG_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SDCAGCBG, cchs2003_p::SDCCGCBG, cchs2005_p::SDCEGCBG, cchs2011_2012_p::SDCGCB12, cchs2012_p::SDCGCB12, cchs2013_2014_p::SDCGCB13, cchs2014_p::SDCGCB13, cchs2015_2016_p::SDCDGCB, cchs2017_2018_p::SDCDGCB, [SDCGCBG]",cat,2,2,Other,Other,N/A,2,Other,Country of birth - (G),Country of birth - (G), -SDCGCBG,SDCGCBG_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SDCAGCBG, cchs2003_p::SDCCGCBG, cchs2005_p::SDCEGCBG, cchs2011_2012_p::SDCGCB12, cchs2012_p::SDCGCB12, cchs2013_2014_p::SDCGCB13, cchs2014_p::SDCGCB13, cchs2015_2016_p::SDCDGCB, cchs2017_2018_p::SDCDGCB, [SDCGCBG]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Country of birth - (G),Country of birth - (G), -SDCGCBG,SDCGCBG_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SDCAGCBG, cchs2003_p::SDCCGCBG, cchs2005_p::SDCEGCBG, cchs2011_2012_p::SDCGCB12, cchs2012_p::SDCGCB12, cchs2013_2014_p::SDCGCB13, cchs2014_p::SDCGCB13, cchs2015_2016_p::SDCDGCB, cchs2017_2018_p::SDCDGCB, [SDCGCBG]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Country of birth - (G),Country of birth - (G),CCHS 2001 does not have don't know (7) or refusal (8) -SDCGCBG,SDCGCBG_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SDCAGCBG, cchs2003_p::SDCCGCBG, cchs2005_p::SDCEGCBG, cchs2011_2012_p::SDCGCB12, cchs2012_p::SDCGCB12, cchs2013_2014_p::SDCGCB13, cchs2014_p::SDCGCB13, cchs2015_2016_p::SDCDGCB, cchs2017_2018_p::SDCDGCB, [SDCGCBG]",cat,NA::b,2,missing,missing,N/A,else,else,Country of birth - (G),Country of birth - (G), -SDCGCGT,SDCGCGT_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SDCAGRAC, cchs2003_p::SDCCGRAC, cchs2005_p::SDCEGCGT, cchs2015_2016_p::SDCDGCGT, cchs2017_2018_p::SDCDGCGT, [SDCGCGT]",cat,1,2,White,White,N/A,1,White,Ethnicity,"Cultural or racial origin - (D, G)", -SDCGCGT,SDCGCGT_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SDCAGRAC, cchs2003_p::SDCCGRAC, cchs2005_p::SDCEGCGT, cchs2015_2016_p::SDCDGCGT, cchs2017_2018_p::SDCDGCGT, [SDCGCGT]",cat,2,2,Non-white,Non-white,N/A,2,Visible minority,Ethnicity,"Cultural or racial origin - (D, G)", -SDCGCGT,SDCGCGT_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SDCAGRAC, cchs2003_p::SDCCGRAC, cchs2005_p::SDCEGCGT, cchs2015_2016_p::SDCDGCGT, cchs2017_2018_p::SDCDGCGT, [SDCGCGT]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Ethnicity,"Cultural or racial origin - (D, G)", -SDCGCGT,SDCGCGT_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SDCAGRAC, cchs2003_p::SDCCGRAC, cchs2005_p::SDCEGCGT, cchs2015_2016_p::SDCDGCGT, cchs2017_2018_p::SDCDGCGT, [SDCGCGT]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Ethnicity,"Cultural or racial origin - (D, G)","CCHS 2001 missing don't know (7), refusal (8)" -SDCGCGT,SDCGCGT_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SDCAGRAC, cchs2003_p::SDCCGRAC, cchs2005_p::SDCEGCGT, cchs2015_2016_p::SDCDGCGT, cchs2017_2018_p::SDCDGCGT, [SDCGCGT]",cat,NA::b,2,missing,missing,N/A,else,else,Ethnicity,"Cultural or racial origin - (D, G)", -SDCGLHM,SDCGLHM_cat4_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SDCDGLHM, cchs2017_2018_p::SDCDGLHM, [SDCGLHM]",cat,1,4,English w/ or w/o other,English with or without other language,N/A,1,English with or without other language,Language(s) spoken at home,Language(s) spoken at home, -SDCGLHM,SDCGLHM_cat4_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SDCDGLHM, cchs2017_2018_p::SDCDGLHM, [SDCGLHM]",cat,2,4,French w/ or w/o other,French with or without other language,N/A,2,French with or without other language,Language(s) spoken at home,Language(s) spoken at home, -SDCGLHM,SDCGLHM_cat4_3,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SDCDGLHM, cchs2017_2018_p::SDCDGLHM, [SDCGLHM]",cat,3,4,English & French w/ or w/o other,English & French with or without other language,N/A,3,English & French with or without other language,Language(s) spoken at home,Language(s) spoken at home, -SDCGLHM,SDCGLHM_cat4_4,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SDCDGLHM, cchs2017_2018_p::SDCDGLHM, [SDCGLHM]",cat,4,4,Neither,Neither English nor French (other),N/A,4,Neither English nor French (other),Language(s) spoken at home,Language(s) spoken at home, -SDCGLHM,SDCGLHM_cat4_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SDCDGLHM, cchs2017_2018_p::SDCDGLHM, [SDCGLHM]",cat,NA::a,4,not applicable,not applicable,N/A,6,not applicable,Language(s) spoken at home,Language(s) spoken at home, -SDCGLHM,SDCGLHM_cat4_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SDCDGLHM, cchs2017_2018_p::SDCDGLHM, [SDCGLHM]",cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Language(s) spoken at home,Language(s) spoken at home, -SDCGLHM,SDCGLHM_cat4_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SDCDGLHM, cchs2017_2018_p::SDCDGLHM, [SDCGLHM]",cat,NA::b,4,missing,missing,N/A,else,else,Language(s) spoken at home,Language(s) spoken at home, -SDCGLNG,SDCGLNG_cat4_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p","cchs2001_p::SDCAGLNG, cchs2003_p::SDCCGLNG, cchs2005_p::SDCEGLNG, [SDCGLNG]",cat,1,4,English w/ or w/o other,English with or without other language,N/A,1,English with or without other language,Languages - can converse in,Languages - can converse in, -SDCGLNG,SDCGLNG_cat4_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p","cchs2001_p::SDCAGLNG, cchs2003_p::SDCCGLNG, cchs2005_p::SDCEGLNG, [SDCGLNG]",cat,2,4,French w/ or w/o other,French with or without other language,N/A,2,French with or without other language,Languages - can converse in,Languages - can converse in, -SDCGLNG,SDCGLNG_cat4_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p","cchs2001_p::SDCAGLNG, cchs2003_p::SDCCGLNG, cchs2005_p::SDCEGLNG, [SDCGLNG]",cat,3,4,English & French w/ or w/o other,English & French with or without other language,N/A,3,English & French with or without other language,Languages - can converse in,Languages - can converse in, -SDCGLNG,SDCGLNG_cat4_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p","cchs2001_p::SDCAGLNG, cchs2003_p::SDCCGLNG, cchs2005_p::SDCEGLNG, [SDCGLNG]",cat,4,4,Neither,Neither English nor French (other),N/A,4,Neither English nor French (other),Languages - can converse in,Languages - can converse in, -SDCGLNG,SDCGLNG_cat4_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p","cchs2001_p::SDCAGLNG, cchs2003_p::SDCCGLNG, cchs2005_p::SDCEGLNG, [SDCGLNG]",cat,NA::a,4,not applicable,not applicable,N/A,6,not applicable,Languages - can converse in,Languages - can converse in, -SDCGLNG,SDCGLNG_cat4_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p","cchs2001_p::SDCAGLNG, cchs2003_p::SDCCGLNG, cchs2005_p::SDCEGLNG, [SDCGLNG]",cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Languages - can converse in,Languages - can converse in, -SDCGLNG,SDCGLNG_cat4_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p","cchs2001_p::SDCAGLNG, cchs2003_p::SDCCGLNG, cchs2005_p::SDCEGLNG, [SDCGLNG]",cat,NA::b,4,missing,missing,N/A,else,else,Languages - can converse in,Languages - can converse in, -SDCGRES,SDCGRES_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SDCAGRES, cchs2003_p::SDCCGRES, cchs2005_p::SDCEGRES, cchs2015_2016_p::SDCDGRES, cchs2017_2018_p::SDCDGRES, [SDCGRES]",cat,1,2,0 to 9 years,0 to 9 years,N/A,1,0 to 9 years,Length in Canada,"Length/time in Canada since imm. (D, G)", -SDCGRES,SDCGRES_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SDCAGRES, cchs2003_p::SDCCGRES, cchs2005_p::SDCEGRES, cchs2015_2016_p::SDCDGRES, cchs2017_2018_p::SDCDGRES, [SDCGRES]",cat,2,2,10 years or more,10 years or more,N/A,2,10 years or more,Length in Canada,"Length/time in Canada since imm. (D, G)", -SDCGRES,SDCGRES_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SDCAGRES, cchs2003_p::SDCCGRES, cchs2005_p::SDCEGRES, cchs2015_2016_p::SDCDGRES, cchs2017_2018_p::SDCDGRES, [SDCGRES]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Length in Canada,"Length/time in Canada since imm. (D, G)", -SDCGRES,SDCGRES_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SDCAGRES, cchs2003_p::SDCCGRES, cchs2005_p::SDCEGRES, cchs2015_2016_p::SDCDGRES, cchs2017_2018_p::SDCDGRES, [SDCGRES]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Length in Canada,"Length/time in Canada since imm. (D, G)","CCHS 2001 missing don't know (7), refusal (8)" -SDCGRES,SDCGRES_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SDCAGRES, cchs2003_p::SDCCGRES, cchs2005_p::SDCEGRES, cchs2015_2016_p::SDCDGRES, cchs2017_2018_p::SDCDGRES, [SDCGRES]",cat,NA::b,2,missing,missing,N/A,else,else,Length in Canada,"Length/time in Canada since imm. (D, G)", -SLP_02,SLP_02_cat5_1,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_010, cchs2017_2018_p::SLP_010, [SLP_02]",cat,1,5,None of the time,None of the time,N/A,1,None of the time,Freq. - trouble sleeping,How often do you have trouble going to sleep or staying asleep?, -SLP_02,SLP_02_cat5_2,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_010, cchs2017_2018_p::SLP_010, [SLP_02]",cat,2,5,Little of the time,Little of the time,N/A,2,Little of the time,Freq. - trouble sleeping,How often do you have trouble going to sleep or staying asleep?, -SLP_02,SLP_02_cat5_3,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_010, cchs2017_2018_p::SLP_010, [SLP_02]",cat,3,5,Some of the time,Some of the time,N/A,3,Some of the time,Freq. - trouble sleeping,How often do you have trouble going to sleep or staying asleep?, -SLP_02,SLP_02_cat5_4,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_010, cchs2017_2018_p::SLP_010, [SLP_02]",cat,4,5,Most of the time,Most of the time,N/A,4,Most of the time,Freq. - trouble sleeping,How often do you have trouble going to sleep or staying asleep?, -SLP_02,SLP_02_cat5_5,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_010, cchs2017_2018_p::SLP_010, [SLP_02]",cat,5,5,All the time,All the time,N/A,5,All the time,Freq. - trouble sleeping,How often do you have trouble going to sleep or staying asleep?, -SLP_02,SLP_02_cat5_NA::a,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_010, cchs2017_2018_p::SLP_010, [SLP_02]",cat,NA::a,5,not applicable,not applicable,N/A,6,not applicable,Freq. - trouble sleeping,How often do you have trouble going to sleep or staying asleep?, -SLP_02,SLP_02_cat5_NA::b,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_010, cchs2017_2018_p::SLP_010, [SLP_02]",cat,NA::b,5,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Freq. - trouble sleeping,How often do you have trouble going to sleep or staying asleep?, -SLP_02,SLP_02_cat5_NA::b,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_010, cchs2017_2018_p::SLP_010, [SLP_02]",cat,NA::b,5,missing,missing,N/A,else,else,Freq. - trouble sleeping,How often do you have trouble going to sleep or staying asleep?, -SLP_02_A,SLP_02_A_cat3_1,cat,cchs2001_p,[GENA_04],cat,1,3,Most of the time,Most of the time,N/A,1,Most of the time,Freq. - trouble sleeping,How often do you have trouble going to sleep or staying asleep?,CCHS 2001 has different categories from other cycles -SLP_02_A,SLP_02_A_cat3_2,cat,cchs2001_p,[GENA_04],cat,2,3,Sometimes,Sometimes,N/A,2,Sometimes,Freq. - trouble sleeping,How often do you have trouble going to sleep or staying asleep?, -SLP_02_A,SLP_02_A_cat3_3,cat,cchs2001_p,[GENA_04],cat,3,3,Never,Never,N/A,3,Never,Freq. - trouble sleeping,How often do you have trouble going to sleep or staying asleep?, -SLP_02_A,SLP_02_A_cat3_NA::a,cat,cchs2001_p,[GENA_04],cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Freq. - trouble sleeping,How often do you have trouble going to sleep or staying asleep?, -SLP_02_A,SLP_02_A_cat3_NA::b,cat,cchs2001_p,[GENA_04],cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Freq. - trouble sleeping,How often do you have trouble going to sleep or staying asleep?, -SLP_02_A,SLP_02_A_cat3_NA::b,cat,cchs2001_p,[GENA_04],cat,NA::b,3,missing,missing,N/A,else,else,Freq. - trouble sleeping,How often do you have trouble going to sleep or staying asleep?, -SLP_03,SLP_03_cat5_1,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_015, cchs2017_2018_p::SLP_015, [SLP_03]",cat,1,5,None of the time,None of the time,N/A,1,None of the time,Frequency - find sleep refreshing,How often do you find your sleep refreshing?, -SLP_03,SLP_03_cat5_2,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_015, cchs2017_2018_p::SLP_015, [SLP_03]",cat,2,5,Little of the time,Little of the time,N/A,2,Little of the time,Frequency - find sleep refreshing,How often do you find your sleep refreshing?, -SLP_03,SLP_03_cat5_3,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_015, cchs2017_2018_p::SLP_015, [SLP_03]",cat,3,5,Some of the time,Some of the time,N/A,3,Some of the time,Frequency - find sleep refreshing,How often do you find your sleep refreshing?, -SLP_03,SLP_03_cat5_4,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_015, cchs2017_2018_p::SLP_015, [SLP_03]",cat,4,5,Most of the time,Most of the time,N/A,4,Most of the time,Frequency - find sleep refreshing,How often do you find your sleep refreshing?, -SLP_03,SLP_03_cat5_5,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_015, cchs2017_2018_p::SLP_015, [SLP_03]",cat,5,5,All the time,All the time,N/A,5,All the time,Frequency - find sleep refreshing,How often do you find your sleep refreshing?, -SLP_03,SLP_03_cat3_NA::a,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_015, cchs2017_2018_p::SLP_015, [SLP_03]",cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Frequency - find sleep refreshing,How often do you find your sleep refreshing?, -SLP_03,SLP_03_cat3_NA::b,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_015, cchs2017_2018_p::SLP_015, [SLP_03]",cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Frequency - find sleep refreshing,How often do you find your sleep refreshing?, -SLP_03,SLP_03_cat3_NA::b,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_015, cchs2017_2018_p::SLP_015, [SLP_03]",cat,NA::b,3,missing,missing,N/A,else,else,Frequency - find sleep refreshing,How often do you find your sleep refreshing?, -SLP_03_A,SLP_03_A_cat3_1,cat,cchs2001_p,[GENA_05],cat,1,3,Most of the time,Most of the time,N/A,1,Most of the time,Freq. - find sleep refreshing,How often do you find your sleep refreshing?,CCHS 2001 has different categories from other cycles -SLP_03_A,SLP_03_A_cat3_2,cat,cchs2001_p,[GENA_05],cat,2,3,Sometimes,Sometimes,N/A,2,Sometimes,Freq. - find sleep refreshing,How often do you find your sleep refreshing?, -SLP_03_A,SLP_03_A_cat3_3,cat,cchs2001_p,[GENA_05],cat,3,3,Never,Never,N/A,3,Never,Freq. - find sleep refreshing,How often do you find your sleep refreshing?, -SLP_03_A,SLP_03_A_cat3_NA::a,cat,cchs2001_p,[GENA_05],cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Freq. - find sleep refreshing,How often do you find your sleep refreshing?, -SLP_03_A,SLP_03_A_cat3_NA::b,cat,cchs2001_p,[GENA_05],cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Freq. - find sleep refreshing,How often do you find your sleep refreshing?, -SLP_03_A,SLP_03_A_cat3_NA::b,cat,cchs2001_p,[GENA_05],cat,NA::b,3,missing,missing,N/A,else,else,Freq. - find sleep refreshing,How often do you find your sleep refreshing?, -SLP_04,SLP_04_cat5_1,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_020, cchs2017_2018_p::SLP_020, [SLP_04]",cat,1,5,None of the time,None of the time,N/A,1,None of the time,Frequency - difficult to stay awake,How often do you find it difficult to stay awake when you want to?, -SLP_04,SLP_04_cat5_2,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_020, cchs2017_2018_p::SLP_020, [SLP_04]",cat,2,5,Little of the time,Little of the time,N/A,2,Little of the time,Frequency - difficult to stay awake,How often do you find it difficult to stay awake when you want to?, -SLP_04,SLP_04_cat5_3,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_020, cchs2017_2018_p::SLP_020, [SLP_04]",cat,3,5,Some of the time,Some of the time,N/A,3,Some of the time,Frequency - difficult to stay awake,How often do you find it difficult to stay awake when you want to?, -SLP_04,SLP_04_cat5_4,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_020, cchs2017_2018_p::SLP_020, [SLP_04]",cat,4,5,Most of the time,Most of the time,N/A,4,Most of the time,Frequency - difficult to stay awake,How often do you find it difficult to stay awake when you want to?, -SLP_04,SLP_04_cat5_5,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_020, cchs2017_2018_p::SLP_020, [SLP_04]",cat,5,5,All the time,All the time,N/A,5,All the time,Frequency - difficult to stay awake,How often do you find it difficult to stay awake when you want to?, -SLP_04,SLP_04_cat5_NA::a,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_020, cchs2017_2018_p::SLP_020, [SLP_04]",cat,NA::a,5,not applicable,not applicable,N/A,6,not applicable,Frequency - difficult to stay awake,How often do you find it difficult to stay awake when you want to?, -SLP_04,SLP_04_cat5_NA::b,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_020, cchs2017_2018_p::SLP_020, [SLP_04]",cat,NA::b,5,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Frequency - difficult to stay awake,How often do you find it difficult to stay awake when you want to?, -SLP_04,SLP_04_cat5_NA::b,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLP_020, cchs2017_2018_p::SLP_020, [SLP_04]",cat,NA::b,5,missing,missing,N/A,else,else,Frequency - difficult to stay awake,How often do you find it difficult to stay awake when you want to?, -SLP_04_A,SLP_04_A_cat3_1,cat,cchs2001_p,[GENA_06],cat,1,3,Most of the time,Most of the time,N/A,1,Most of the time,Freq. - find it difficult to stay awake,How often do you find it difficult to stay awake when you want to?,CCHS 2001 has different categories from other cycles -SLP_04_A,SLP_04_A_cat3_2,cat,cchs2001_p,[GENA_06],cat,2,3,Sometimes,Sometimes,N/A,2,Sometimes,Freq. - find it difficult to stay awake,How often do you find it difficult to stay awake when you want to?, -SLP_04_A,SLP_04_A_cat3_3,cat,cchs2001_p,[GENA_06],cat,3,3,Never,Never,N/A,3,Never,Freq. - find it difficult to stay awake,How often do you find it difficult to stay awake when you want to?, -SLP_04_A,SLP_04_A_cat3_NA::a,cat,cchs2001_p,[GENA_06],cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Freq. - find it difficult to stay awake,How often do you find it difficult to stay awake when you want to?, -SLP_04_A,SLP_04_A_cat3_NA::b,cat,cchs2001_p,[GENA_06],cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Freq. - find it difficult to stay awake,How often do you find it difficult to stay awake when you want to?, -SLP_04_A,SLP_04_A_cat3_NA::b,cat,cchs2001_p,[GENA_06],cat,NA::b,3,missing,missing,N/A,else,else,Freq. - find it difficult to stay awake,How often do you find it difficult to stay awake when you want to?, -SLPG01,SLPG01_cat11_1,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,1,11,<3 hours,<3 hours,Hours,1,<3 hours,Number of hours spent sleeping per night,How long do you usually spend sleeping each night?,CCHS 2011-2012 onwards omitted 2-<3 hours category -SLPG01,SLPG01_cat11_2,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,2,11,3-<4 hours,3-<4 hours,Hours,2,3-<4 hours,Number of hours spent sleeping per night,How long do you usually spend sleeping each night?, -SLPG01,SLPG01_cat11_3,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,3,11,4-<5 hours,4-<5 hours,Hours,3,4-<5 hours,Number of hours spent sleeping per night,How long do you usually spend sleeping each night?, -SLPG01,SLPG01_cat11_4,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,4,11,5-<6 hours,5-<6 hours,Hours,4,5-<6 hours,Number of hours spent sleeping per night,How long do you usually spend sleeping each night?, -SLPG01,SLPG01_cat11_5,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,5,11,6-<7 hours,6-<7 hours,Hours,5,6-<7 hours,Number of hours spent sleeping per night,How long do you usually spend sleeping each night?, -SLPG01,SLPG01_cat11_6,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,6,11,7-<8 hours,7-<8 hours,Hours,6,7-<8 hours,Number of hours spent sleeping per night,How long do you usually spend sleeping each night?, -SLPG01,SLPG01_cat11_7,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,7,11,8-<9 hours,8-<9 hours,Hours,7,8-<9 hours,Number of hours spent sleeping per night,How long do you usually spend sleeping each night?, -SLPG01,SLPG01_cat11_8,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,8,11,9-<10 hours,9-<10 hours,Hours,8,9-<10 hours,Number of hours spent sleeping per night,How long do you usually spend sleeping each night?, -SLPG01,SLPG01_cat11_9,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,9,11,10-<11 hours,10-<11 hours,Hours,9,10-<11 hours,Number of hours spent sleeping per night,How long do you usually spend sleeping each night?, -SLPG01,SLPG01_cat11_10,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,10,11,11-<12 hours,11-<12 hours,Hours,10,11-<12 hours,Number of hours spent sleeping per night,How long do you usually spend sleeping each night?, -SLPG01,SLPG01_cat11_11,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,11,11,>= 12 hours,>= 12 hours,Hours,11,>= 12 hours,Number of hours spent sleeping per night,How long do you usually spend sleeping each night?, -SLPG01,SLPG01_cat11_NA::a,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,NA::a,11,not applicable,not applicable,Hours,96,not applicable,Number of hours spent sleeping per night,How long do you usually spend sleeping each night?, -SLPG01,SLPG01_cat11_NA::b,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,NA::b,11,missing,missing,Hours,"[97,99]",don't know (97); refusal (98); not stated (99),Number of hours spent sleeping per night,How long do you usually spend sleeping each night?, -SLPG01,SLPG01_cat11_NA::b,cat,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,NA::b,11,missing,missing,Hours,else,else,Number of hours spent sleeping per night,How long do you usually spend sleeping each night?, -SLPG01_A,SLPG01_A_cat12_1,cat,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,1,12,<2 hours,<2 hours,Hours,1,<2 hours,No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_A,SLPG01_A_cat12_2,cat,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,2,12,2-<3 hours,2-<3 hours,Hours,2,2-<3 hours,No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_A,SLPG01_A_cat12_3,cat,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,3,12,3-<4 hours,3-<4 hours,Hours,3,3-<4 hours,No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_A,SLPG01_A_cat12_4,cat,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,4,12,4-<5 hours,4-<5 hours,Hours,4,4-<5 hours,No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_A,SLPG01_A_cat12_5,cat,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,5,12,5-<6 hours,5-<6 hours,Hours,5,5-<6 hours,No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_A,SLPG01_A_cat12_6,cat,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,6,12,6-<7 hours,6-<7 hours,Hours,6,6-<7 hours,No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_A,SLPG01_A_cat12_7,cat,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,7,12,7-<8 hours,7-<8 hours,Hours,7,7-<8 hours,No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_A,SLPG01_A_cat12_8,cat,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,8,12,8-<9 hours,8-<9 hours,Hours,8,8-<9 hours,No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_A,SLPG01_A_cat12_9,cat,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,9,12,9-<10 hours,9-<10 hours,Hours,9,9-<10 hours,No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_A,SLPG01_A_cat12_10,cat,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,10,12,10-<11 hours,10-<11 hours,Hours,10,10-<11 hours,No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_A,SLPG01_A_cat12_11,cat,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,11,12,11-<12 hours,11-<12 hours,Hours,11,11-<12 hours,No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_A,SLPG01_A_cat12_12,cat,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,12,12,>= 12 hours,>= 12 hours,Hours,12,>= 12 hours,No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_A,SLPG01_A_cat12_NA::a,cat,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,NA::a,12,not applicable,not applicable,Hours,96,not applicable,No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_A,SLPG01_A_cat12_NA::b,cat,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,NA::b,12,missing,missing,Hours,"[97,99]",don't know (97); refusal (98); not stated (99),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_A,SLPG01_A_cat12_NA::b,cat,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,NA::b,12,missing,missing,Hours,else,else,No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,1,N/A,Hours,converted hours (<2 hours),Hours,1,converted hours (<2 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,2.5,N/A,Hours,convereted hours (2-<3 hours),Hours,2,convereted hours (2-<3 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,3.5,N/A,Hours,converted hours (3-<4 hours),Hours,3,converted hours (3-<4 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,4.5,N/A,Hours,converted hours (4-<5 hours),Hours,4,converted hours (4-<5 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,5.5,N/A,Hours,converted hours (5-<6 hours),Hours,5,converted hours (5-<6 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,6.5,N/A,Hours,converted hours (6-<7 hours),Hours,6,converted hours (6-<7 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,7.5,N/A,Hours,converted hours (7-<8 hours),Hours,7,converted hours (7-<8 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,8.5,N/A,Hours,converted hours (8-<9 hours),Hours,8,converted hours (8-<9 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,9.5,N/A,Hours,converted hours (9-<10 hours),Hours,9,converted hours (9-<10 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,10.5,N/A,Hours,converted hours (10-<11 hours),Hours,10,converted hours (10-<11 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,11.5,N/A,Hours,converted hours (11-<12 hours),Hours,11,converted hours (11-<12 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,13,N/A,Hours,converted hours (>= 12 hours),Hours,12,converted hours (>= 12 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,NA::a,N/A,not applicable,not applicable,Hours,96,not applicable,No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,NA::b,N/A,missing,missing,Hours,"[97,99]",don't know (97); refusal (98); not stated (99),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2001_p, cchs2007_2008_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01",cat,NA::b,N/A,missing,missing,Hours,else,else,No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,1.5,11,<3 hours,converted hours (<2 hours),Hours,1,converted hours (<2 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,3.5,11,3-<4 hours,converted hours (3-<4 hours),Hours,2,converted hours (3-<4 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,4.5,11,4-<5 hours,converted hours (4-<5 hours),Hours,3,converted hours (4-<5 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,5.5,11,5-<6 hours,converted hours (5-<6 hours),Hours,4,converted hours (5-<6 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,6.5,11,6-<7 hours,converted hours (6-<7 hours),Hours,5,converted hours (6-<7 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,7.5,11,7-<8 hours,converted hours (7-<8 hours),Hours,6,converted hours (7-<8 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,8.5,11,8-<9 hours,converted hours (8-<9 hours),Hours,7,converted hours (8-<9 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,9.5,11,9-<10 hours,converted hours (9-<10 hours),Hours,8,converted hours (9-<10 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,10.5,11,10-<11 hours,converted hours (10-<11 hours),Hours,9,converted hours (10-<11 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,11.5,11,11-<12 hours,converted hours (11-<12 hours),Hours,10,converted hours (11-<12 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,13,11,>= 12 hours,converted hours (>= 12 hours),Hours,11,converted hours (>= 12 hours),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,NA::a,11,not applicable,not applicable,Hours,96,not applicable,No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,NA::b,11,missing,missing,Hours,"[97,99]",don't know (97); refusal (98); not stated (99),No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SLPG01_cont,N/A,cont,"cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SLPG005, cchs2017_2018_p::SLPG005, [SLPG01]",cat,NA::b,11,missing,missing,Hours,else,else,No./hours spent sleeping each night,How long do you usually spend sleeping each night?, -SMK_01A,SMK_01A_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SMKA_01A, cchs2003_p::SMKC_01A, cchs2005_p::SMKE_01A, cchs2015_2016_p::SMK_020, cchs2017_2018_p::SMK_020, [SMK_01A]",cat,1,2,yes,yes,N/A,1,Yes,s100,"In lifetime, smoked 100 or more cigarettes", -SMK_01A,SMK_01A_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SMKA_01A, cchs2003_p::SMKC_01A, cchs2005_p::SMKE_01A, cchs2015_2016_p::SMK_020, cchs2017_2018_p::SMK_020, [SMK_01A]",cat,2,2,no,no,N/A,2,No,s100,"In lifetime, smoked 100 or more cigarettes", -SMK_01A,SMK_01A_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SMKA_01A, cchs2003_p::SMKC_01A, cchs2005_p::SMKE_01A, cchs2015_2016_p::SMK_020, cchs2017_2018_p::SMK_020, [SMK_01A]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,s100,"In lifetime, smoked 100 or more cigarettes", -SMK_01A,SMK_01A_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SMKA_01A, cchs2003_p::SMKC_01A, cchs2005_p::SMKE_01A, cchs2015_2016_p::SMK_020, cchs2017_2018_p::SMK_020, [SMK_01A]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),s100,"In lifetime, smoked 100 or more cigarettes", -SMK_01A,SMK_01A_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SMKA_01A, cchs2003_p::SMKC_01A, cchs2005_p::SMKE_01A, cchs2015_2016_p::SMK_020, cchs2017_2018_p::SMK_020, [SMK_01A]",cat,NA::b,2,missing,missing,N/A,else,else,s100,"In lifetime, smoked 100 or more cigarettes", -SMK_05B,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SMKA_05B, cchs2003_p::SMKC_05B, cchs2005_p::SMKE_05B, cchs2015_2016_p::SMK_050, cchs2017_2018_p::SMK_050, [SMK_05B]",cont,copy,N/A,Cigarettes/day - occasional,# of cigarettes smoked daily - daily smoker,cigarettes,"[1,99]",# of cigarettes smoked daily - occasional smoker,cigdayo,# of cigarettes smoked daily - occasional smoker, -SMK_05B,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SMKA_05B, cchs2003_p::SMKC_05B, cchs2005_p::SMKE_05B, cchs2015_2016_p::SMK_050, cchs2017_2018_p::SMK_050, [SMK_05B]",cont,NA::a,N/A,not applicable,not applicable,cigarettes,996,not applicable,cigdayo,# of cigarettes smoked daily - occasional smoker, -SMK_05B,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SMKA_05B, cchs2003_p::SMKC_05B, cchs2005_p::SMKE_05B, cchs2015_2016_p::SMK_050, cchs2017_2018_p::SMK_050, [SMK_05B]",cont,NA::b,N/A,missing,missing,cigarettes,"[997,999]",don't know (997); refusal (998); not stated (999),cigdayo,# of cigarettes smoked daily - occasional smoker, -SMK_05B,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SMKA_05B, cchs2003_p::SMKC_05B, cchs2005_p::SMKE_05B, cchs2015_2016_p::SMK_050, cchs2017_2018_p::SMK_050, [SMK_05B]",cont,NA::b,N/A,missing,missing,cigarettes,else,else,cigdayo,# of cigarettes smoked daily - occasional smoker, -SMK_05C,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SMKA_05C, cchs2003_p::SMKC_05C, cchs2005_p::SMKE_05C, cchs2015_2016_p::SMK_055, cchs2017_2018_p::SMK_055, [SMK_05C]",cont,copy,N/A,# days smoked at least 1 cigarette,# days smoked at least 1 cigarette,days,"[0,31]",# days smoked at least 1 cigarette,Number of days - smoked 1 cigarette or more (occ. smoker),"In the past month, on how many days have you smoked 1 or more cigarettes?", -SMK_05C,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SMKA_05C, cchs2003_p::SMKC_05C, cchs2005_p::SMKE_05C, cchs2015_2016_p::SMK_055, cchs2017_2018_p::SMK_055, [SMK_05C]",cont,NA::a,N/A,not applicable,not applicable,days,96,not applicable,Number of days - smoked 1 cigarette or more (occ. smoker),"In the past month, on how many days have you smoked 1 or more cigarettes?", -SMK_05C,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SMKA_05C, cchs2003_p::SMKC_05C, cchs2005_p::SMKE_05C, cchs2015_2016_p::SMK_055, cchs2017_2018_p::SMK_055, [SMK_05C]",cont,NA::b,N/A,missing,missing,days,"[97,99]",don't know (97); refusal (98); not stated (99),Number of days - smoked 1 cigarette or more (occ. smoker),"In the past month, on how many days have you smoked 1 or more cigarettes?", -SMK_05C,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SMKA_05C, cchs2003_p::SMKC_05C, cchs2005_p::SMKE_05C, cchs2015_2016_p::SMK_055, cchs2017_2018_p::SMK_055, [SMK_05C]",cont,NA::b,N/A,missing,missing,days,else,else,Number of days - smoked 1 cigarette or more (occ. smoker),"In the past month, on how many days have you smoked 1 or more cigarettes?", -SMK_05D,SMK_05D_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SMKA_05D, cchs2003_p::SMKC_05D, cchs2005_p::SMKE_05D, cchs2015_2016_p::SMK_030, cchs2017_2018_p::SMK_030, [SMK_05D]",cat,1,2,yes,Occasional smoker who previously smoked daily,N/A,1,Yes,evd,Ever smoked cigarettes daily - occasional smoker,2015 onward looks at occasional/former smokers -SMK_05D,SMK_05D_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SMKA_05D, cchs2003_p::SMKC_05D, cchs2005_p::SMKE_05D, cchs2015_2016_p::SMK_030, cchs2017_2018_p::SMK_030, [SMK_05D]",cat,2,2,no,Occasional smoker never daily,N/A,2,No,evd,Ever smoked cigarettes daily - occasional smoker, -SMK_05D,SMK_05D_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SMKA_05D, cchs2003_p::SMKC_05D, cchs2005_p::SMKE_05D, cchs2015_2016_p::SMK_030, cchs2017_2018_p::SMK_030, [SMK_05D]",cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,evd,Ever smoked cigarettes daily - occasional smoker, -SMK_05D,SMK_05D_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SMKA_05D, cchs2003_p::SMKC_05D, cchs2005_p::SMKE_05D, cchs2015_2016_p::SMK_030, cchs2017_2018_p::SMK_030, [SMK_05D]",cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),evd,Ever smoked cigarettes daily - occasional smoker, -SMK_05D,SMK_05D_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SMKA_05D, cchs2003_p::SMKC_05D, cchs2005_p::SMKE_05D, cchs2015_2016_p::SMK_030, cchs2017_2018_p::SMK_030, [SMK_05D]",cat,NA::b,2,missing,missing,N/A,else,else,evd,Ever smoked cigarettes daily - occasional smoker, -SMK_06A_A,SMK_06A_A_cat4_1,cat,cchs2001_p,cchs2001_p::SMKA_06A,cat,1,4,<1 year,Less than one year ago,years,1,Less than one year ago,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_A,SMK_06A_A_cat4_2,cat,cchs2001_p,cchs2001_p::SMKA_06A,cat,2,4,1 to 2 years,1 year to 2 years ago,years,2,1 year to 2 years ago,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_A,SMK_06A_A_cat4_3,cat,cchs2001_p,cchs2001_p::SMKA_06A,cat,3,4,3 to 5 years,3 years to 5 years ago,years,3,3 years to 5 years ago,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_A,SMK_06A_A_cat4_4,cat,cchs2001_p,cchs2001_p::SMKA_06A,cat,4,4,>5 years,More than 5 years ago,years,4,More than 5 years ago,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_A,SMK_06A_A_cat4_NA::a,cat,cchs2001_p,cchs2001_p::SMKA_06A,cat,NA::a,4,not applicable,not applicable,years,6,not applicable,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_A,SMK_06A_A_cat4_NA::b,cat,cchs2001_p,cchs2001_p::SMKA_06A,cat,NA::b,4,missing,missing,years,"[7,9]",don't know (7); refusal (8); not stated (9),Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_A,SMK_06A_A_cat4_NA::b,cat,cchs2001_p,cchs2001_p::SMKA_06A,cat,NA::b,4,missing,missing,years,else,else,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_B,SMK_06A_B_cat4_1,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_06A, cchs2005_p::SMKE_06A, cchs2015_2016_p::SMK_100, cchs2017_2018_p::SMK_100, [SMK_06A]",cat,1,4,<1 year,Less than one year ago,years,1,Less than one year,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_B,SMK_06A_B_cat4_2,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_06A, cchs2005_p::SMKE_06A, cchs2015_2016_p::SMK_100, cchs2017_2018_p::SMK_100, [SMK_06A]",cat,2,4,1 to 2 years,1 year to less than 2 years ago,years,2,1 year to < 2 years,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_B,SMK_06A_B_cat4_3,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_06A, cchs2005_p::SMKE_06A, cchs2015_2016_p::SMK_100, cchs2017_2018_p::SMK_100, [SMK_06A]",cat,3,4,2 to 3 years,2 years to less than 3 years ago,years,3,2 years to < 3 years,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_B,SMK_06A_B_cat4_4,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_06A, cchs2005_p::SMKE_06A, cchs2015_2016_p::SMK_100, cchs2017_2018_p::SMK_100, [SMK_06A]",cat,4,4,>= 3 years,3 or more years ago,years,4,3 or more years,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_B,SMK_06A_B_cat4_NA::a,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_06A, cchs2005_p::SMKE_06A, cchs2015_2016_p::SMK_100, cchs2017_2018_p::SMK_100, [SMK_06A]",cat,NA::a,4,not applicable,not applicable,years,6,not applicable,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_B,SMK_06A_B_cat4_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_06A, cchs2005_p::SMKE_06A, cchs2015_2016_p::SMK_100, cchs2017_2018_p::SMK_100, [SMK_06A]",cat,NA::b,4,missing,missing,years,"[7,9]",don't know (7); refusal (8); not stated (9),Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_B,SMK_06A_B_cat4_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_06A, cchs2005_p::SMKE_06A, cchs2015_2016_p::SMK_100, cchs2017_2018_p::SMK_100, [SMK_06A]",cat,NA::b,4,missing,missing,years,else,else,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_cont,N/A,cont,cchs2001_p,cchs2001_p::SMKA_06A,cat,0.5,N/A,stpn,converted age - Less than one year ago,years,1,Less than one year ago,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_cont,N/A,cont,cchs2001_p,cchs2001_p::SMKA_06A,cat,1.5,N/A,stpn,converted age - 1 year to 2 years ago,years,2,1 year to 2 years ago,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_cont,N/A,cont,cchs2001_p,cchs2001_p::SMKA_06A,cat,4,N/A,stpn,converted age - 3 years to 5 years ago,years,3,3 years to 5 years ago,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_cont,N/A,cont,cchs2001_p,cchs2001_p::SMKA_06A,cat,6,N/A,stpn,converted age - More than 5 years ago,years,4,More than 5 years ago,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_cont,N/A,cont,cchs2001_p,cchs2001_p::SMKA_06A,cat,NA::a,N/A,not applicable,not applicable,years,6,not applicable,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_cont,N/A,cont,cchs2001_p,cchs2001_p::SMKA_06A,cat,NA::b,N/A,missing,missing,years,"[7,9]",don't know (7); refusal (8); not stated (9),Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_cont,N/A,cont,cchs2001_p,cchs2001_p::SMKA_06A,cat,NA::b,N/A,missing,missing,years,else,else,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_cont,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_06A, cchs2005_p::SMKE_06A, cchs2015_2016_p::SMK_100, cchs2017_2018_p::SMK_100, [SMK_06A]",cat,0.5,N/A,stpn,converted age - Less than one year ago,years,1,Less than one year,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_cont,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_06A, cchs2005_p::SMKE_06A, cchs2015_2016_p::SMK_100, cchs2017_2018_p::SMK_100, [SMK_06A]",cat,1.5,N/A,stpn,converted age - 1 year to less than 2 years ago,years,2,1 year to < 2 years,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_cont,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_06A, cchs2005_p::SMKE_06A, cchs2015_2016_p::SMK_100, cchs2017_2018_p::SMK_100, [SMK_06A]",cat,2.5,N/A,stpn,converted age - 2 years to less than 3 years ago,years,3,2 years to < 3 years,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_cont,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_06A, cchs2005_p::SMKE_06A, cchs2015_2016_p::SMK_100, cchs2017_2018_p::SMK_100, [SMK_06A]",cat,4,N/A,stpn,converted age - 3 or more years ago,years,4,3 or more years,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_cont,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_06A, cchs2005_p::SMKE_06A, cchs2015_2016_p::SMK_100, cchs2017_2018_p::SMK_100, [SMK_06A]",cat,NA::a,N/A,not applicable,not applicable,years,6,not applicable,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_cont,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_06A, cchs2005_p::SMKE_06A, cchs2015_2016_p::SMK_100, cchs2017_2018_p::SMK_100, [SMK_06A]",cat,NA::b,N/A,missing,missing,years,"[7,9]",don't know (7); refusal (8); not stated (9),Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_06A_cont,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_06A, cchs2005_p::SMKE_06A, cchs2015_2016_p::SMK_100, cchs2017_2018_p::SMK_100, [SMK_06A]",cat,NA::b,N/A,missing,missing,years,else,else,Stopped smoking - when (was never a daily smoker),"When did you stop smoking? Was it: (less than one year ago, 1 year to less than 2 years ago, 2 years to less than 3 years ago, 3 or more years ago)?", -SMK_09A_A,SMK_09A_A_cat4_1,cat,cchs2001_p,cchs2001_p::SMKA_09A,cat,1,4,<1 year,Less than one year ago,years,1,Less than one year ago,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_A,SMK_09A_A_cat4_2,cat,cchs2001_p,cchs2001_p::SMKA_09A,cat,2,4,1 to 2 years,1 year to 2 years ago,years,2,1 year to 2 years ago,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_A,SMK_09A_A_cat4_3,cat,cchs2001_p,cchs2001_p::SMKA_09A,cat,3,4,3 to 5 years,3 years to 5 years ago,years,3,3 years to 5 years ago,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_A,SMK_09A_A_cat4_4,cat,cchs2001_p,cchs2001_p::SMKA_09A,cat,4,4,>5 years,More than 5 years ago,years,4,More than 5 years ago,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_A,SMK_09A_A_cat4_NA::a,cat,cchs2001_p,cchs2001_p::SMKA_09A,cat,NA::a,4,not applicable,not applicable,years,6,not applicable,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_A,SMK_09A_A_cat4_NA::b,cat,cchs2001_p,cchs2001_p::SMKA_09A,cat,NA::b,4,missing,missing,years,"[7,9]",don't know (7); refusal (8); not stated (9),stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_A,SMK_09A_A_cat4_NA::b,cat,cchs2001_p,cchs2001_p::SMKA_09A,cat,NA::b,4,missing,missing,years,else,else,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_B,SMK_09A_B_cat4_1,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, cchs2015_2016_p::SMK_080, cchs2017_2018_p::SMK_080, [SMK_09A]",cat,1,4,<1 year,Less than one year ago,years,1,Less than 1 year,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_B,SMK_09A_B_cat4_2,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, cchs2015_2016_p::SMK_080, cchs2017_2018_p::SMK_080, [SMK_09A]",cat,2,4,1 to <2 years,1 year to less than 2 years ago,years,2,1 to <2 years,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_B,SMK_09A_B_cat4_3,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, cchs2015_2016_p::SMK_080, cchs2017_2018_p::SMK_080, [SMK_09A]",cat,3,4,2 to <3 years,2 years to less than 3 years ago,years,3,2 to <3 years,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_B,SMK_09A_B_cat4_4,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, cchs2015_2016_p::SMK_080, cchs2017_2018_p::SMK_080, [SMK_09A]",cat,4,4,>= 3 years,3 or more years ago,years,4,3 years or more,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_B,SMK_09A_B_cat4_NA::a,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, cchs2015_2016_p::SMK_080, cchs2017_2018_p::SMK_080, [SMK_09A]",cat,NA::a,4,not applicable,not applicable,years,6,not applicable,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_B,SMK_09A_B_cat4_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, cchs2015_2016_p::SMK_080, cchs2017_2018_p::SMK_080, [SMK_09A]",cat,NA::b,4,missing,missing,years,"[7,9]",don't know (7); refusal (8); not stated (9),stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_B,SMK_09A_B_cat4_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, cchs2015_2016_p::SMK_080, cchs2017_2018_p::SMK_080, [SMK_09A]",cat,NA::b,4,missing,missing,years,else,else,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_cont,N/A,cont,cchs2001_p,cchs2001_p::SMKA_09A,cat,0.5,N/A,stpo,converted age - Less than one year ago,years,1,Less than one year ago,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_cont,N/A,cont,cchs2001_p,cchs2001_p::SMKA_09A,cat,1.5,N/A,stpo,converted age - 1 year to 2 years ago,years,2,1 year to 2 years ago,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_cont,N/A,cont,cchs2001_p,cchs2001_p::SMKA_09A,cat,4,N/A,stpo,converted age - 3 years to 5 years ago,years,3,3 years to 5 years ago,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_cont,N/A,cont,cchs2001_p,cchs2001_p::SMKA_09A,cat,6,N/A,stpo,converted age - More than 5 years ago,years,4,More than 5 years ago,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_cont,N/A,cont,cchs2001_p,cchs2001_p::SMKA_09A,cat,NA::a,N/A,not applicable,not applicable,years,6,not applicable,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_cont,N/A,cont,cchs2001_p,cchs2001_p::SMKA_09A,cat,NA::b,N/A,missing,missing,years,"[7,9]",don't know (7); refusal (8); not stated (9),stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_cont,N/A,cont,cchs2001_p,cchs2001_p::SMKA_09A,cat,NA::b,N/A,missing,missing,years,else,else,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_cont,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, cchs2015_2016_p::SMK_080, cchs2017_2018_p::SMK_080, [SMK_09A]",cat,0.5,N/A,stpo,converted age - Less than one year ago,years,1,Less than 1 year,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_cont,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, cchs2015_2016_p::SMK_080, cchs2017_2018_p::SMK_080, [SMK_09A]",cat,1.5,N/A,stpo,converted age - 1 year to less than 2 years ago,years,2,1 to <2 years,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_cont,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, cchs2015_2016_p::SMK_080, cchs2017_2018_p::SMK_080, [SMK_09A]",cat,2.5,N/A,stpo,converted age - 2 years to less than 3 years ago,years,3,2 to <3 years,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_cont,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, cchs2015_2016_p::SMK_080, cchs2017_2018_p::SMK_080, [SMK_09A]",cat,4,N/A,stpo,converted age - 3 or more years ago,years,4,3 years or more,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_cont,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, cchs2015_2016_p::SMK_080, cchs2017_2018_p::SMK_080, [SMK_09A]",cat,NA::a,N/A,not applicable,not applicable,years,6,not applicable,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_cont,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, cchs2015_2016_p::SMK_080, cchs2017_2018_p::SMK_080, [SMK_09A]",cat,NA::b,N/A,missing,missing,years,"[7,9]",don't know (7); refusal (8); not stated (9),stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_09A_cont,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, cchs2015_2016_p::SMK_080, cchs2017_2018_p::SMK_080, [SMK_09A]",cat,NA::b,N/A,missing,missing,years,else,else,stpd,When did you stop smoking daily - former daily smoker - (G), -SMK_204,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SMKA_204, cchs2003_p::SMKC_204, cchs2005_p::SMKE_204, cchs2015_2016_p::SMK_045, cchs2017_2018_p::SMK_045, [SMK_204]",cont,copy,N/A,Cigarettes/day - daily,# of cigarettes smoked daily - daily smoker,cigarettes,"[1,99]",# of cigarettes smoked daily - daily smoker,# of cigarettes smoked daily - daily smoker,How many cigarettes did you usually smoke each day?, -SMK_204,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SMKA_204, cchs2003_p::SMKC_204, cchs2005_p::SMKE_204, cchs2015_2016_p::SMK_045, cchs2017_2018_p::SMK_045, [SMK_204]",cont,NA::a,N/A,not applicable,not applicable,cigarettes,996,not applicable,# of cigarettes smoked daily - daily smoker,How many cigarettes did you usually smoke each day?, -SMK_204,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SMKA_204, cchs2003_p::SMKC_204, cchs2005_p::SMKE_204, cchs2015_2016_p::SMK_045, cchs2017_2018_p::SMK_045, [SMK_204]",cont,NA::b,N/A,missing,missing,cigarettes,"[997,999]",don't know (997); refusal (998); not stated (999),# of cigarettes smoked daily - daily smoker,How many cigarettes did you usually smoke each day?, -SMK_204,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::SMKA_204, cchs2003_p::SMKC_204, cchs2005_p::SMKE_204, cchs2015_2016_p::SMK_045, cchs2017_2018_p::SMK_045, [SMK_204]",cont,NA::b,N/A,missing,missing,cigarettes,else,else,# of cigarettes smoked daily - daily smoker,How many cigarettes did you usually smoke each day?, -SMK_208,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKA_208, cchs2003_p::SMKC_208, cchs2005_p::SMKE_208, [SMK_208]",cont,copy,N/A,Cigarettes/day - former daily,Cigarettes/day - former daily,cigarettes,"[1,80]",# of cigarettes smoke each day - former daily,# of cigarettes smoked daily - former daily smoker,How many cigarettes did you usually smoke each day?, -SMK_208,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKA_208, cchs2003_p::SMKC_208, cchs2005_p::SMKE_208, [SMK_208]",cont,NA::a,N/A,not applicable,not applicable,cigarettes,996,not applicable,# of cigarettes smoked daily - former daily smoker,How many cigarettes did you usually smoke each day?, -SMK_208,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKA_208, cchs2003_p::SMKC_208, cchs2005_p::SMKE_208, [SMK_208]",cont,NA::b,N/A,missing,missing,cigarettes,"[997,999]",don't know (997); refusal (998); not stated (999),# of cigarettes smoked daily - former daily smoker,How many cigarettes did you usually smoke each day?, -SMK_208,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKA_208, cchs2003_p::SMKC_208, cchs2005_p::SMKE_208, [SMK_208]",cont,NA::b,N/A,missing,missing,cigarettes,else,else,# of cigarettes smoked daily - former daily smoker,How many cigarettes did you usually smoke each day?, -SMKDSTY_A,SMKDSTY_A_cat6_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,1,6,Daily,Daily smoker,N/A,1,Daily,Smoke status,Type of smoker - (D), -SMKDSTY_A,SMKDSTY_A_cat6_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,2,6,Occasional (former daily),Former daily current occasional smoker,N/A,2,Occasional,Smoke status,Type of smoker - (D), -SMKDSTY_A,SMKDSTY_A_cat6_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,3,6,Always occasional,Never daily current occasional smoker,N/A,3,Always occasional,Smoke status,Type of smoker - (D), -SMKDSTY_A,SMKDSTY_A_cat6_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,4,6,Former daily,Former daily current nonsmoker,N/A,4,Former daily,Smoke status,Type of smoker - (D), -SMKDSTY_A,SMKDSTY_A_cat6_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,5,6,Former occasional,Never daily current nonsmoker (former occasional),N/A,5,Former occasional,Smoke status,Type of smoker - (D), -SMKDSTY_A,SMKDSTY_A_cat6_6,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,6,6,Never smoked,Never smoked,N/A,6,Never smoked,Smoke status,Type of smoker - (D), -SMKDSTY_A,SMKDSTY_A_cat6_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,NA::a,6,not applicable,not applicable,N/A,96,not applicable,Smoke status,Type of smoker - (D), -SMKDSTY_A,SMKDSTY_A_cat6_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,NA::b,6,missing,missing,N/A,"[97,99]",don't know (97); refusal (98); not stated (99),Smoke status,Type of smoker - (D), -SMKDSTY_A,SMKDSTY_A_cat6_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,NA::b,6,missing,missing,N/A,else,else,Smoke status,Type of smoker - (D), -SMKDSTY_cat3,SMKDSTY_cat3_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,1,3,Current,Current smoker,N/A,"[1,3]",Daily (1); Occasional (2); Always occasional (3),Smoke status,Type of smoker - (D), -SMKDSTY_cat3,SMKDSTY_cat3_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,2,3,Former,Former smoker,N/A,"[4,5]",Former daily(4); Former occasional (5),Smoke status,Type of smoker - (D), -SMKDSTY_cat3,SMKDSTY_cat3_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,3,3,Never smoked,Never smoked,N/A,6,Never smoked,Smoke status,Type of smoker - (D), -SMKDSTY_cat3,SMKDSTY_cat3_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,NA::a,3,not applicable,not applicable,N/A,96,not applicable,Smoke status,Type of smoker - (D), -SMKDSTY_cat3,SMKDSTY_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,NA::b,3,missing,missing,N/A,"[97,99]",don't know (97); refusal (98); not stated (99),Smoke status,Type of smoker - (D), -SMKDSTY_cat3,SMKDSTY_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,NA::b,3,missing,missing,N/A,else,else,Smoke status,Type of smoker - (D), -SMKDSTY_cat3,SMKDSTY_cat3_1,cat,"ccsh2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,1,3,Current,Current smoker,N/A,"[1,2]",Daily (1); Occasional (2),Smoke status,Type of smoker - (D), -SMKDSTY_cat3,SMKDSTY_cat3_2,cat,"ccsh2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,2,3,Former,Former smoker,N/A,"[3,5]",Former daily (3); Former occasional (4); Experimental (5),Smoke status,Type of smoker - (D), -SMKDSTY_cat3,SMKDSTY_cat3_3,cat,"ccsh2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,3,3,Never smoked,Never smoked,N/A,6,Never smoked,Smoke status,Type of smoker - (D), -SMKDSTY_cat3,SMKDSTY_cat3_NA::a,cat,"ccsh2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,NA::a,3,not applicable,not applicable,N/A,96,not applicable,Smoke status,Type of smoker - (D), -SMKDSTY_cat3,SMKDSTY_cat3_NA::b,cat,"ccsh2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,NA::b,3,missing,missing,N/A,"[97,99]",don't know (97); refusal (98); not stated (99),Smoke status,Type of smoker - (D), -SMKDSTY_cat3,SMKDSTY_cat3_NA::b,cat,"ccsh2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,NA::b,3,missing,missing,N/A,else,else,Smoke status,Type of smoker - (D), -SMKDSTY_B,SMKDSTY_B_cat6_1,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,1,6,Daily,Current daily smoker,N/A,1,Daily,Smoke status,Type of smoker - (D), -SMKDSTY_B,SMKDSTY_B_cat6_2,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,2,6,Occasional,Current occasional smoker,N/A,2,Occasional,Smoke status,Type of smoker - (D), -SMKDSTY_B,SMKDSTY_B_cat6_3,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,3,6,Former daily,Former daily smoker (non-smoker now),N/A,3,Former daily,Smoke status,Type of smoker - (D), -SMKDSTY_B,SMKDSTY_B_cat6_4,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,4,6,Former occasional,Former occasional (non-smoker now),N/A,4,Former occasional,Smoke status,Type of smoker - (D), -SMKDSTY_B,SMKDSTY_B_cat6_5,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,5,6,Experimental,"Experimental smoker (at least 1 cig, non-smoker now)",N/A,5,Experimental,Smoke status,Type of smoker - (D),"2015 onwards for smoke status still has 6 categories, but removed 'always occasional' (Never daily current occasional smoker) and added 'experimental' (at least 1 cig, non-smoker now)" -SMKDSTY_B,SMKDSTY_B_cat6_6,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,6,6,Never smoked,Never smoked,N/A,6,Never smoked,Smoke status,Type of smoker - (D), -SMKDSTY_B,SMKDSTY_B_cat6_NA::a,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,NA::a,6,not applicable,not applicable,N/A,96,not applicable,Smoke status,Type of smoker - (D), -SMKDSTY_B,SMKDSTY_B_cat6_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,NA::b,6,missing,missing,N/A,"[97,99]",don't know (97); refusal (98); not stated (99),Smoke status,Type of smoker - (D), -SMKDSTY_B,SMKDSTY_B_cat6_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,NA::b,6,missing,missing,N/A,else,else,Smoke status,Type of smoker - (D), -SMKDSTY_cat5,SMKDSTY_cat5_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,1,5,Daily,Current daily smoker,N/A,1,Daily,Smoke status,Type of smoker - (D), -SMKDSTY_cat5,SMKDSTY_cat5_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,2,5,Occasional,Current occasional smoker,N/A,"[2,3]",Occasional,Smoke status,Type of smoker - (D),"SMKDSTY_cat5 is a 5 category variable for smoking status for cycles up to 2018. Prior to 2015, 'occasional' and 'always occasional' are combined to form the current 'occasional' category. 2015 onwards, 'former occasional' and 'experimental' are combined to form the current 'former occasional' category" -SMKDSTY_cat5,SMKDSTY_cat5_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,3,5,Former daily,Former daily smoker,N/A,4,Former daily,Smoke status,Type of smoker - (D), -SMKDSTY_cat5,SMKDSTY_cat5_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,4,5,Former occasional,Former occasional,N/A,5,Former occasional,Smoke status,Type of smoker - (D), -SMKDSTY_cat5,SMKDSTY_cat5_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,5,5,Never smoked,Never smoked,N/A,6,Never smoked,Smoke status,Type of smoker - (D), -SMKDSTY_cat5,SMKDSTY_cat5_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,NA::a,5,not applicable,not applicable,N/A,96,not applicable,Smoke status,Type of smoker - (D), -SMKDSTY_cat5,SMKDSTY_cat5_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,NA::b,5,missing,missing,N/A,"[97,99]",don't know (97); refusal (98); not stated (99),Smoke status,Type of smoker - (D), -SMKDSTY_cat5,SMKDSTY_cat5_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,NA::b,5,missing,missing,N/A,else,else,Smoke status,Type of smoker - (D), -SMKDSTY_cat5,SMKDSTY_cat5_1,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,1,5,Daily,Current daily smoker,N/A,1,Daily,Smoke status,Type of smoker - (D), -SMKDSTY_cat5,SMKDSTY_cat5_2,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,2,5,Occasional,Current occasional smoker,N/A,2,Occasional,Smoke status,Type of smoker - (D), -SMKDSTY_cat5,SMKDSTY_cat5_3,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,3,5,Former daily,Former daily smoker,N/A,3,Former daily,Smoke status,Type of smoker - (D), -SMKDSTY_cat5,SMKDSTY_cat5_4,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,4,5,Former occasional,Former occasional,N/A,"[4,5]",Former occasional,Smoke status,Type of smoker - (D),"SMKDSTY_cat5 is a 5 category variable for smoking status for cycles up to 2018. Prior to 2015, 'occasional' and 'always occasional' are combined to form the current 'occasional' category. 2015 onwards, 'former occasional' and 'experimental' are combined to form the current 'former occasional' category" -SMKDSTY_cat5,SMKDSTY_cat5_5,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,5,5,Never smoked,Never smoked,N/A,6,Never smoked,Smoke status,Type of smoker - (D), -SMKDSTY_cat5,SMKDSTY_cat5_NA::a,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,NA::a,5,not applicable,not applicable,N/A,96,not applicable,Smoke status,Type of smoker - (D), -SMKDSTY_cat5,SMKDSTY_cat5_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,NA::b,5,missing,missing,N/A,"[97,99]",don't know (97); refusal (98); not stated (99),Smoke status,Type of smoker - (D), -SMKDSTY_cat5,SMKDSTY_cat5_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY",cat,NA::b,5,missing,missing,N/A,else,else,Smoke status,Type of smoker - (D), -SMKG01C_A,SMKG01C_A_cat10_1,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,1,10,5 To 11 Years,age smoked first whole cigarette (5 to 11),years,1,5 To 11 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_A,SMKG01C_A_cat10_2,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,2,10,12 To 14 Years,age smoked first whole cigarette (12 to 14),years,2,12 To 14 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_A,SMKG01C_A_cat10_3,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,3,10,15 To 19 Years,age smoked first whole cigarette (18 to 19),years,3,15 To 19 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_A,SMKG01C_A_cat10_4,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,4,10,20 To 24 Years,age smoked first whole cigarette (20 to 24),years,4,20 To 24 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_A,SMKG01C_A_cat10_5,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,5,10,25 To 29 Years,age smoked first whole cigarette (25 to 29),years,5,25 To 29 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_A,SMKG01C_A_cat10_6,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,6,10,30 To 34 Years,age smoked first whole cigarette (30 to 34),years,6,30 To 34 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_A,SMKG01C_A_cat10_7,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,7,10,35 To 39 Years,age smoked first whole cigarette (35 to 39),years,7,35 To 39 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_A,SMKG01C_A_cat10_8,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,8,10,40 To 44 Years,age smoked first whole cigarette (40 to 44),years,8,40 To 44 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_A,SMKG01C_A_cat10_9,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,9,10,45 To 49 Years,age smoked first whole cigarette (45 to 49),years,9,45 To 49 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_A,SMKG01C_A_cat10_10,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,10,10,50 Years or more,age smoked first whole cigarette (50 plus),years,10,50 Years or more,agec1,Age smoked first whole cigarette - (G), -SMKG01C_A,SMKG01C_A_cat10_NA::a,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,NA::a,10,not applicable,not applicable,years,96,not applicable,agec1,Age smoked first whole cigarette - (G), -SMKG01C_A,SMKG01C_A_cat10_NA::b,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,NA::b,10,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),agec1,Age smoked first whole cigarette - (G), -SMKG01C_A,SMKG01C_A_cat10_NA::b,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,NA::b,10,missing,missing,years,else,else,agec1,Age smoked first whole cigarette - (G), -SMKG01C_B,SMKG01C_B_cat11_1,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,1,11,5 To 11 Years,age smoked first whole cigarette (5 to 11),years,1,5 To 11 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_B,SMKG01C_B_cat11_2,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,2,11,12 To 14 Years,age smoked first whole cigarette (12 to 14),years,2,12 To 14 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_B,SMKG01C_B_cat11_3,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,3,11,15 To 17 Years,age smoked first whole cigarette (15 to 17),years,3,15 To 17 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_B,SMKG01C_B_cat11_4,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,4,11,18 To 19 Years,age smoked first whole cigarette (18 to 19),years,4,18 To 19 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_B,SMKG01C_B_cat11_5,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,5,11,20 To 24 Years,age smoked first whole cigarette (20 to 24),years,5,20 To 24 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_B,SMKG01C_B_cat11_6,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,6,11,25 To 29 Years,age smoked first whole cigarette (25 to 29),years,6,25 To 29 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_B,SMKG01C_B_cat11_7,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,7,11,30 To 34 Years,age smoked first whole cigarette (30 to 34),years,7,30 To 34 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_B,SMKG01C_B_cat11_8,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,8,11,35 To 39 Years,age smoked first whole cigarette (35 to 39),years,8,35 To 39 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_B,SMKG01C_B_cat11_9,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,9,11,40 To 44 Years,age smoked first whole cigarette (40 to 44),years,9,40 To 44 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_B,SMKG01C_B_cat11_10,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,10,11,45 To 49 Years,age smoked first whole cigarette (45 to 49),years,10,45 To 49 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_B,SMKG01C_B_cat11_11,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,11,11,50 Years or more,age smoked first whole cigarette (50 plus),years,11,50 Years or more,agec1,Age smoked first whole cigarette - (G), -SMKG01C_B,SMKG01C_B_cat10_NA::a,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,NA::a,10,not applicable,not applicable,years,96,not applicable,agec1,Age smoked first whole cigarette - (G), -SMKG01C_B,SMKG01C_B_cat10_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,NA::b,10,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),agec1,Age smoked first whole cigarette - (G), -SMKG01C_B,SMKG01C_B_cat11_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,NA::b,11,missing,missing,years,else,else,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,8,N/A,agec1,converted categorical age smoked first whole cigarette (5 to 11),years,1,5 To 11 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,13,N/A,agec1,converted categorical age smoked first whole cigarette (12 to 14),years,2,12 To 14 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,17,N/A,agec1,converted categorical age smoked first whole cigarette (18 to 19),years,3,15 To 19 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,22,N/A,agec1,converted categorical age smoked first whole cigarette (20 to 24),years,4,20 To 24 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,27,N/A,agec1,converted categorical age smoked first whole cigarette (25 to 29),years,5,25 To 29 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,32,N/A,agec1,converted categorical age smoked first whole cigarette (30 to 34),years,6,30 To 34 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,37,N/A,agec1,converted categorical age smoked first whole cigarette (35 to 39),years,7,35 To 39 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,42,N/A,agec1,converted categorical age smoked first whole cigarette (40 to 44),years,8,40 To 44 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,47,N/A,agec1,converted categorical age smoked first whole cigarette (45 to 49),years,9,45 To 49 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,55,N/A,agec1,converted categorical age smoked first whole cigarette (50 plus),years,10,50 Years or more,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,NA::a,N/A,not applicable,not applicable,years,96,not applicable,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,NA::b,N/A,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C",cat,NA::b,N/A,missing,missing,years,else,else,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,8,N/A,agec1,converted categorical age smoked first whole cigarette (5 to 11),years,1,5 To 11 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,13,N/A,agec1,converted categorical age smoked first whole cigarette (12 to 14),years,2,12 To 14 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,16,N/A,agec1,converted categorical age smoked first whole cigarette (15 to 17),years,3,15 To 17 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,18.5,N/A,agec1,converted categorical age smoked first whole cigarette (18 to 19),years,4,18 To 19 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,22,N/A,agec1,converted categorical age smoked first whole cigarette (20 to 24),years,5,20 To 24 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,27,N/A,agec1,converted categorical age smoked first whole cigarette (25 to 29),years,6,25 To 29 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,32,N/A,agec1,converted categorical age smoked first whole cigarette (30 to 34),years,7,30 To 34 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,37,N/A,agec1,converted categorical age smoked first whole cigarette (35 to 39),years,8,35 To 39 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,42,N/A,agec1,converted categorical age smoked first whole cigarette (40 to 44),years,9,40 To 44 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,47,N/A,agec1,converted categorical age smoked first whole cigarette (45 to 49),years,10,45 To 49 Years,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,55,N/A,agec1,converted categorical age smoked first whole cigarette (50 plus),years,11,50 Years or more,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,NA::a,10,not applicable,not applicable,years,96,not applicable,agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,NA::b,10,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),agec1,Age smoked first whole cigarette - (G), -SMKG01C_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, [SMKG01C]",cat,NA::b,N/A,missing,missing,years,else,else,agec1,Age smoked first whole cigarette - (G), -SMKG06C,SMKG06C_cat3_1,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::SMKCG06C, cchs2005_p::SMKEG06C, [SMKG06C]",cat,1,3,3 to 5 years,3 to 5 years,years,1,3 to 5 years,stpny,Years since stopped smoking daily - never daily, -SMKG06C,SMKG06C_cat3_2,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::SMKCG06C, cchs2005_p::SMKEG06C, [SMKG06C]",cat,2,3,6 to 10 years,6 to 10 years,years,2,6 to 10 years,stpny,Years since stopped smoking daily - never daily, -SMKG06C,SMKG06C_cat3_3,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::SMKCG06C, cchs2005_p::SMKEG06C, [SMKG06C]",cat,3,3,11+ years,11 or more years,years,3,11 or more years,stpny,Years since stopped smoking daily - never daily, -SMKG06C,SMKG06C_cat3_NA::a,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::SMKCG06C, cchs2005_p::SMKEG06C, [SMKG06C]",cat,NA::a,3,not applicable,not applicable,years,6,not applicable,stpny,Years since stopped smoking daily - never daily, -SMKG06C,SMKG06C_cat3_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::SMKCG06C, cchs2005_p::SMKEG06C, [SMKG06C]",cat,NA::b,3,missing,missing,years,"[7,9]",don't know (7); refusal (8); not stated (9),stpny,Years since stopped smoking daily - never daily, -SMKG06C,SMKG06C_cat3_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::SMKCG06C, cchs2005_p::SMKEG06C, [SMKG06C]",cat,NA::b,3,missing,missing,years,else,else,stpny,Years since stopped smoking daily - never daily, -SMKG09C,SMKG09C_cat3_1,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKCG09C, cchs2005_p::SMKEG09C, cchs2015_2016_p::SMKG090, cchs2017_2018_p::SMKG090, [SMKG09C]",cat,1,3,3 to 5 years,3 to 5 years,years,1,3 to 5 years,stpdy,Years since stopped smoking daily - former daily, -SMKG09C,SMKG09C_cat3_2,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKCG09C, cchs2005_p::SMKEG09C, cchs2015_2016_p::SMKG090, cchs2017_2018_p::SMKG090, [SMKG09C]",cat,2,3,6 to 10 years,6 to 10 years,years,2,6 to 10 years,stpdy,Years since stopped smoking daily - former daily, -SMKG09C,SMKG09C_cat3_3,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKCG09C, cchs2005_p::SMKEG09C, cchs2015_2016_p::SMKG090, cchs2017_2018_p::SMKG090, [SMKG09C]",cat,3,3,11+ years,11 or more years,years,3,11 or more years,stpdy,Years since stopped smoking daily - former daily, -SMKG09C,SMKG09C_cat3_NA::a,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKCG09C, cchs2005_p::SMKEG09C, cchs2015_2016_p::SMKG090, cchs2017_2018_p::SMKG090, [SMKG09C]",cat,NA::a,3,not applicable,not applicable,years,6,not applicable,stpdy,Years since stopped smoking daily - former daily, -SMKG09C,SMKG09C_cat3_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKCG09C, cchs2005_p::SMKEG09C, cchs2015_2016_p::SMKG090, cchs2017_2018_p::SMKG090, [SMKG09C]",cat,NA::b,3,missing,missing,years,"[7,9]",don't know (7); refusal (8); not stated (9),stpdy,Years since stopped smoking daily - former daily,Don't know (7) and refusal (8) not included in CCHS 2015-2016 and CCHS 2017-2018 -SMKG09C,SMKG09C_cat3_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2003_p::SMKCG09C, cchs2005_p::SMKEG09C, cchs2015_2016_p::SMKG090, cchs2017_2018_p::SMKG090, [SMKG09C]",cat,NA::b,3,missing,missing,years,else,else,stpdy,Years since stopped smoking daily - former daily, -SMKG203_A,SMKG203_A_cat10_1,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,1,10,5 To 11 Years,age (5 to 11) started smoking daily - daily smoker,years,1,5 To 11 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_A,SMKG203_A_cat10_2,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,2,10,12 To 14 Years,age (12 to 14) started smoking daily - daily smoker,years,2,12 To 14 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_A,SMKG203_A_cat10_3,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,3,10,15 to 19 Years,age (15 to 19) started smoking daily - daily smoker,years,3,15 to 19 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_A,SMKG203_A_cat10_4,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,4,10,20 To 24 Years,age (20 to 24) started smoking daily - daily smoker,years,4,20 To 24 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_A,SMKG203_A_cat10_5,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,5,10,25 To 29 Years,age (25 to 29) started smoking daily - daily smoker,years,5,25 To 29 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_A,SMKG203_A_cat10_6,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,6,10,30 To 34 Years,age (30 to 34) started smoking daily - daily smoker,years,6,30 To 34 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_A,SMKG203_A_cat10_7,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,7,10,35 To 39 Years,age (35 to 39) started smoking daily - daily smoker,years,7,35 To 39 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_A,SMKG203_A_cat10_8,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,8,10,40 To 44 Years,age (40 to 44) started smoking daily - daily smoker,years,8,40 To 44 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_A,SMKG203_A_cat10_9,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,9,10,45 To 49 Years,age (45 to 49) started smoking daily - daily smoker,years,9,45 To 49 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_A,SMKG203_A_cat10_10,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,10,10,50 Years or more,age (50 or more) started smoking daily - daily smoker,years,10,50 Years or more,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_A,SMKG203_A_cat10_NA::a,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,NA::a,10,not applicable,not applicable,years,96,not applicable,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_A,SMKG203_A_cat10_NA::b,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,NA::b,10,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_A,SMKG203_A_cat10_NA::b,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,NA::b,10,missing,missing,years,else,else,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_B,SMKG203_B_cat11_1,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,1,11,5 To 11 Years,age (5 to 11) started smoking daily - daily smoker,years,1,5 To 11 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_B,SMKG203_B_cat11_2,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,2,11,12 To 14 Years,age (12 to 14) started smoking daily - daily smoker,years,2,12 To 14 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_B,SMKG203_B_cat11_3,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,3,11,15 To 17 Years,age (15 to 17) started smoking daily - daily smoker,years,3,15 To 17 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_B,SMKG203_B_cat11_4,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,4,11,18 To 19 Years,age (18 to 19) started smoking daily - daily smoker,years,4,18 To 19 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_B,SMKG203_B_cat11_5,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,5,11,20 To 24 Years,age (20 to 24) started smoking daily - daily smoker,years,5,20 To 24 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_B,SMKG203_B_cat11_6,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,6,11,25 To 29 Years,age (25 to 29) started smoking daily - daily smoker,years,6,25 To 29 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_B,SMKG203_B_cat11_7,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,7,11,30 To 34 Years,age (30 to 34) started smoking daily - daily smoker,years,7,30 To 34 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_B,SMKG203_B_cat11_8,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,8,11,35 To 39 Years,age (35 to 39) started smoking daily - daily smoker,years,8,35 To 39 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_B,SMKG203_B_cat11_9,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,9,11,40 To 44 Years,age (40 to 44) started smoking daily - daily smoker,years,9,40 To 44 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_B,SMKG203_B_cat11_10,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,10,11,45 To 49 Years,age (45 to 49) started smoking daily - daily smoker,years,10,45 To 49 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_B,SMKG203_B_cat11_11,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,11,11,50 Years or more,age (50 plus) started smoking daily - daily smoker,years,11,50 Years or more,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_B,SMKG203_B_cat11_NA::a,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,NA::a,11,not applicable,not applicable,years,96,not applicable,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_B,SMKG203_B_cat11_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,NA::b,11,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),agecigd,Age started to smoke daily - daily smoker (G),Don't know (97) and refusal (98) not included in CCHS 2015-2016 and CCHS 2017-2018 -SMKG203_B,SMKG203_B_cat11_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,NA::b,11,missing,missing,years,else,else,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,8,N/A,agecigd,converted categorical age (5 to 11) started smoking daily - daily smoker,years,1,5 To 11 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,13,N/A,agecigd,converted categorical age (12 to 14) started smoking daily - daily smoker,years,2,12 To 14 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,17,N/A,agecigd,converted categorical age (15 to 19) started smoking daily - daily smoker,years,3,15 to 19 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,22,N/A,agecigd,converted categorical age (20 to 24) started smoking daily - daily smoker,years,4,20 To 24 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,27,N/A,agecigd,converted categorical age (25 to 29) started smoking daily - daily smoker,years,5,25 To 29 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,32,N/A,agecigd,converted categorical age (30 to 34) started smoking daily - daily smoker,years,6,30 To 34 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,37,N/A,agecigd,converted categorical age (35 to 39) started smoking daily - daily smoker,years,7,35 To 39 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,42,N/A,agecigd,converted categorical age (40 to 44) started smoking daily - daily smoker,years,8,40 To 44 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,47,N/A,agecigd,converted categorical age (45 to 49) started smoking daily - daily smoker,years,9,45 To 49 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,55,N/A,agecigd,converted categorical age (50 or more) started smoking daily - daily smoker,years,10,50 Years or more,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,NA::a,N/A,not applicable,not applicable,years,96,not applicable,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,NA::b,N/A,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203",cat,NA::b,N/A,missing,missing,years,else,else,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,8,N/A,agecigd,converted categorical age (5 to 11) started smoking daily - daily smoker,years,1,5 To 11 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,13,N/A,agecigd,converted categorical age (12 to 14) started smoking daily - daily smoker,years,2,12 To 14 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,16,N/A,agecigd,converted categorical age (15 to 17) started smoking daily - daily smoker,years,3,15 To 17 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,18.5,N/A,agecigd,converted categorical age (18 to 19) started smoking daily - daily smoker,years,4,18 To 19 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,22,N/A,agecigd,converted categorical age (20 to 24) started smoking daily - daily smoker,years,5,20 To 24 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,27,N/A,agecigd,converted categorical age (25 to 29) started smoking daily - daily smoker,years,6,25 To 29 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,32,N/A,agecigd,converted categorical age (30 to 34) started smoking daily - daily smoker,years,7,30 To 34 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,37,N/A,agecigd,converted categorical age (35 to 39) started smoking daily - daily smoker,years,8,35 To 39 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,42,N/A,agecigd,converted categorical age (40 to 44) started smoking daily - daily smoker,years,9,40 To 44 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,47,N/A,agecigd,converted categorical age (45 to 49) started smoking daily - daily smoker,years,10,45 To 49 Years,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,55,N/A,agecigd,converted categorical age (50 plus) started smoking daily - daily smoker,years,11,50 Years or more,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,NA::a,N/A,not applicable,not applicable,years,96,not applicable,agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,NA::b,N/A,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),agecigd,Age started to smoke daily - daily smoker (G), -SMKG203_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG203, [SMKG203]",cat,NA::b,N/A,missing,missing,years,else,else,agecigd,Age started to smoke daily - daily smoker (G), -SMKG207_A,SMKG207_A_cat10_1,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,1,10,5 To 11 Years,age (5 to 11) started smoking daily - daily smoker,years,1,5 To 11 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_A,SMKG207_A_cat10_2,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,2,10,12 To 14 Years,age (12 to 14) started smoking daily - daily smoker,years,2,12 To 14 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_A,SMKG207_A_cat10_3,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,3,10,15 to 19 Years,age (15 to 19) started smoking daily - daily smoker,years,3,15 to 19 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_A,SMKG207_A_cat10_4,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,4,10,20 To 24 Years,age (20 to 24) started smoking daily - daily smoker,years,4,20 To 24 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_A,SMKG207_A_cat10_5,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,5,10,25 To 29 Years,age (25 to 29) started smoking daily - daily smoker,years,5,25 To 29 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_A,SMKG207_A_cat10_6,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,6,10,30 To 34 Years,age (30 to 34) started smoking daily - daily smoker,years,6,30 To 34 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_A,SMKG207_A_cat10_7,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,7,10,35 To 39 Years,age (35 to 39) started smoking daily - daily smoker,years,7,35 To 39 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_A,SMKG207_A_cat10_8,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,8,10,40 To 44 Years,age (40 to 44) started smoking daily - daily smoker,years,8,40 To 44 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_A,SMKG207_A_cat10_9,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,9,10,45 To 49 Years,age (45 to 49) started smoking daily - daily smoker,years,9,45 To 49 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_A,SMKG207_A_cat10_10,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,10,10,50 Years or more,age (50 or more) started smoking daily - daily smoker,years,10,50 Years or more,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_A,SMKG207_A_cat10_NA::a,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,NA::a,10,not applicable,not applicable,years,96,not applicable,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_A,SMKG207_A_cat10_NA::b,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,NA::b,10,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_A,SMKG207_A_cat10_NA::b,cat,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,NA::b,10,missing,missing,years,else,else,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_B,SMKG207_B_cat11_1,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,1,11,5 To 11 Years,age (5 to 11) started smoking daily - former daily smoker,years,1,5 To 11 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_B,SMKG207_B_cat11_2,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,2,11,12 To 14 Years,age (12 to 14) started smoking daily - former daily smoker,years,2,12 To 14 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_B,SMKG207_B_cat11_3,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,3,11,15 To 17 Years,age (15 to 17) started smoking daily - former daily smoker,years,3,15 To 17 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_B,SMKG207_B_cat11_4,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,4,11,18 To 19 Years,age (18 to 19) started smoking daily - former daily smoker,years,4,18 To 19 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_B,SMKG207_B_cat11_5,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,5,11,20 To 24 Years,age (20 to 24) started smoking daily - former daily smoker,years,5,20 To 24 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_B,SMKG207_B_cat11_6,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,6,11,25 To 29 Years,age (25 to 29) started smoking daily - former daily smoker,years,6,25 To 29 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_B,SMKG207_B_cat11_7,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,7,11,30 To 34 Years,age (30 to 34) started smoking daily - former daily smoker,years,7,30 To 34 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_B,SMKG207_B_cat11_8,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,8,11,35 To 39 Years,age (35 to 39) started smoking daily - former daily smoker,years,8,35 To 39 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_B,SMKG207_B_cat11_9,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,9,11,40 To 44 Years,age (40 to 44) started smoking daily - former daily smoker,years,9,40 To 44 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_B,SMKG207_B_cat11_10,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,10,11,45 To 49 Years,age (45 to 49) started smoking daily - former daily smoker,years,10,45 To 49 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_B,SMKG207_B_cat11_11,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,11,11,50 Years or more,age (50 plus) started smoking daily - former daily smoker,years,11,50 Years or more,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_B,SMKG207_B_cat11_NA::a,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,NA::a,11,not applicable,not applicable,years,96,not applicable,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_B,SMKG207_B_cat11_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,NA::b,11,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_B,SMKG207_B_cat11_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,NA::b,11,missing,missing,years,else,else,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,8,N/A,agecigd,converted categorical age (5 to 11) started smoking daily - daily smoker,years,1,5 To 11 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,13,N/A,agecigd,converted categorical age (12 to 14) started smoking daily - daily smoker,years,2,12 To 14 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,17,N/A,agecigd,converted categorical age (15 to 19) started smoking daily - daily smoker,years,3,15 to 19 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,22,N/A,agecigd,converted categorical age (20 to 24) started smoking daily - daily smoker,years,4,20 To 24 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,27,N/A,agecigd,converted categorical age (25 to 29) started smoking daily - daily smoker,years,5,25 To 29 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,32,N/A,agecigd,converted categorical age (30 to 34) started smoking daily - daily smoker,years,6,30 To 34 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,37,N/A,agecigd,converted categorical age (35 to 39) started smoking daily - daily smoker,years,7,35 To 39 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,42,N/A,agecigd,converted categorical age (40 to 44) started smoking daily - daily smoker,years,8,40 To 44 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,47,N/A,agecigd,converted categorical age (45 to 49) started smoking daily - daily smoker,years,9,45 To 49 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,55,N/A,agecigd,converted categorical age (50 or more) started smoking daily - daily smoker,years,10,50 Years or more,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,NA::a,N/A,not applicable,not applicable,years,96,not applicable,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,NA::b,N/A,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",cat,NA::b,N/A,missing,missing,years,else,else,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,8,N/A,agecigd,converted categorical age (5 to 11) started smoking daily - daily smoker,years,1,5 To 11 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,13,N/A,agecigd,converted categorical age (12 to 14) started smoking daily - daily smoker,years,2,12 To 14 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,16,N/A,agecigd,converted categorical age (15 to 17) started smoking daily - daily smoker,years,3,15 To 17 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,18.5,N/A,agecigd,converted categorical age (18 to 19) started smoking daily - daily smoker,years,4,18 To 19 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,22,N/A,agecigd,converted categorical age (20 to 24) started smoking daily - daily smoker,years,5,20 To 24 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,27,N/A,agecigd,converted categorical age (25 to 29) started smoking daily - daily smoker,years,6,25 To 29 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,32,N/A,agecigd,converted categorical age (30 to 34) started smoking daily - daily smoker,years,7,30 To 34 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,37,N/A,agecigd,converted categorical age (35 to 39) started smoking daily - daily smoker,years,8,35 To 39 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?,Missing 2001 Data -SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,42,N/A,agecigd,converted categorical age (40 to 44) started smoking daily - daily smoker,years,9,40 To 44 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?,Missing 2001 Data -SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,47,N/A,agecigd,converted categorical age (45 to 49) started smoking daily - daily smoker,years,10,45 To 49 Years,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?,Missing 2001 Data -SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,55,N/A,agecigd,converted categorical age (50 plus) started smoking daily - daily smoker,years,11,50 Years or more,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?,Missing 2001 Data -SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,NA::a,N/A,not applicable,not applicable,years,96,not applicable,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?,Missing 2001 Data -SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,NA::b,N/A,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",cat,NA::b,N/A,missing,missing,years,else,else,Age started to smoke daily - former daily (G),At what age did you begin to smoke cigarettes daily?, -SMKG040,SMKG040_cat11_1,cat,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,1,11,5 To 11 Years,age (5 to 11) started smoking daily - daily/former daily smoker,years,1,5 To 11 Years,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040,SMKG040_cat11_2,cat,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,2,11,12 To 14 Years,age (12 to 14) started smoking daily - daily/former daily smoker,years,2,12 To 14 Years,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040,SMKG040_cat11_3,cat,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,3,11,15 To 17 Years,age (15 to 17) started smoking daily - daily/former daily smoker,years,3,15 To 17 Years,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040,SMKG040_cat11_4,cat,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,4,11,18 To 19 Years,age (18 to 19) started smoking daily - daily/former daily smoker,years,4,18 To 19 Years,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040,SMKG040_cat11_5,cat,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,5,11,20 To 24 Years,age (20 to 24) started smoking daily - daily/former daily smoker,years,5,20 To 24 Years,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040,SMKG040_cat11_6,cat,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,6,11,25 To 29 Years,age (25 to 29) started smoking daily - daily/former daily smoker,years,6,25 To 29 Years,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040,SMKG040_cat11_7,cat,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,7,11,30 To 34 Years,age (30 to 34) started smoking daily - daily/former daily smoker,years,7,30 To 34 Years,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040,SMKG040_cat11_8,cat,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,8,11,35 To 39 Years,age (35 to 39) started smoking daily - daily/former daily smoker,years,8,35 To 39 Years,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040,SMKG040_cat11_9,cat,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,9,11,40 To 44 Years,age (40 to 44) started smoking daily - daily/former daily smoker,years,9,40 To 44 Years,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040,SMKG040_cat11_10,cat,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,10,11,45 To 49 Years,age (45 to 49) started smoking daily - daily/former daily smoker,years,10,45 To 49 Years,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040,SMKG040_cat11_11,cat,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,11,11,50 Years or more,age (50 or more) started smoking daily - daily/former daily smoker,years,11,50 Years or more,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040,SMKG040_cat11_NA::a,cat,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,NA::a,11,not applicable,not applicable,years,96,not applicable,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040,SMKG040_cat11_NA::a,cat,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,NA::b,11,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?,Don't know (97) and refusal (98) not included in CCHS 2015-2016 and CCHS 2017-2018 -SMKG040,SMKG040_cat11_NA::a,cat,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,NA::b,11,missing,missing,years,else,else,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","DerivedVar::[SMKG203_cont, SMKG207_cont]",N/A,Func::SMKG040_fun,N/A,N/A,N/A,years,N/A,N/A,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","DerivedVar::[SMKG203_cont, SMKG207_cont]",N/A,NA::b,N/A,missing,missing,years,N/A,N/A,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,8,N/A,agecigdfd,converted categorical age (5 to 11) started smoking daily - daily/former daily smoker,years,1,5 To 11 Years,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,13,N/A,agecigdfd,converted categorical age (12 to 14) started smoking daily - daily/former daily smoker,years,2,12 To 14 Years,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,16,N/A,agecigdfd,converted categorical age (15 to 17) started smoking daily - daily/former daily smoker,years,3,15 To 17 Years,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,18.5,N/A,agecigdfd,converted categorical age (18 to 19) started smoking daily - daily/former daily smoker,years,4,18 To 19 Years,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,22,N/A,agecigdfd,converted categorical age (20 to 24) started smoking daily - daily/former daily smoker,years,5,20 To 24 Years,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,27,N/A,agecigdfd,converted categorical age (25 to 29) started smoking daily - daily/former daily smoker,years,6,25 To 29 Years,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,32,N/A,agecigdfd,converted categorical age (30 to 34) started smoking daily - daily/former daily smoker,years,7,30 To 34 Years,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,37,N/A,agecigdfd,converted categorical age (35 to 39) started smoking daily - daily/former daily smoker,years,8,35 To 39 Years,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,42,N/A,agecigdfd,converted categorical age (40 to 44) started smoking daily - daily/former daily smoker,years,9,40 To 44 Years,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,47,N/A,agecigdfd,converted categorical age (45 to 49) started smoking daily - daily/former daily smoker,years,10,45 To 49 Years,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,55,N/A,agecigdfd,converted categorical age (50 or more) started smoking daily - daily/former daily smoker,years,11,50 Years or more,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,NA::a,N/A,not applicable,not applicable,years,96,not applicable,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -SMKG040_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,NA::b,N/A,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?,Don't know (97) and refusal (98) not included in CCHS 2015-2016 and CCHS 2017-2018 -SMKG040_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p",[SMKG040],cat,NA::b,N/A,missing,missing,years,else,else,Age started to smoke daily - daily/former daily,At what age did you begin to smoke cigarettes daily?, -smoke_simple,smoke_simple_catN/A_Func::smoke_simple_fun,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[SMKDSTY_cat5, time_quit_smoking]",N/A,Func::smoke_simple_fun,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A, -smoke_simple,smoke_simple_cat4_1,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[SMKDSTY_cat5, time_quit_smoking]",N/A,0,4,Non-smoker (never smoked),Non-smoker (never smoked),N/A,N/A,N/A,N/A,N/A, -smoke_simple,smoke_simple_cat4_2,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[SMKDSTY_cat5, time_quit_smoking]",N/A,1,4,Current smoker (daily and occasional),Current smoker (daily and occasional),N/A,N/A,N/A,N/A,N/A, -smoke_simple,smoke_simple_cat4_3,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[SMKDSTY_cat5, time_quit_smoking]",N/A,2,4,Former daily smoker quit less than 5 years or former occasional smoker ,Former daily smoker quit less than 5 years or former occasional smoker ,N/A,N/A,N/A,N/A,N/A, -smoke_simple,smoke_simple_cat4_4,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[SMKDSTY_cat5, time_quit_smoking]",N/A,3,4,Former daily smoker quit >5 years,Former daily smoker quit >5 years,N/A,N/A,N/A,N/A,N/A, -smoke_simple,smoke_simple_cat4_NA::a,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[SMKDSTY_cat5, time_quit_smoking]",N/A,NA::a,4,not applicable,not applicable,N/A,N/A,N/A,N/A,N/A, -smoke_simple,smoke_simple_cat4_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[SMKDSTY_cat5, time_quit_smoking]",N/A,NA::b,4,missing,missing,N/A,N/A,N/A,N/A,N/A, -time_quit_smoking,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[SMK_09A_B, SMKG09C]",N/A,Func::time_quit_smoking_fun,N/A,N/A,N/A,Years,N/A,N/A,Time since quit,Time since quit smoking,Variable derived from various harmonized smoking variables -time_quit_smoking,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[SMK_09A_B, SMKG09C]",N/A,NA::a,N/A,not applicable,not applicable,Years,N/A,N/A,Time since quit,Time since quit smoking, -time_quit_smoking,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","DerivedVar::[SMK_09A_B, SMKG09C]",N/A,NA::b,N/A,missing,missing,Years,N/A,N/A,Time since quit,Time since quit smoking, -WTS_M,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p","cchs2001_p::WTSAM, cchs2003_p::WTSC_M, cchs2005_p::WTSE_M, [WTS_M]",N/A,copy,N/A,N/A,N/A,N/A,"[1.07,26332.62]",N/A,Weights,Weights - Master, \ No newline at end of file diff --git a/Worksheets/phiatyll_variables.csv b/Worksheets/phiatyll_variables.csv deleted file mode 100644 index 11945b9..0000000 --- a/Worksheets/phiatyll_variables.csv +++ /dev/null @@ -1,160 +0,0 @@ -variable,role,label,labelLong,section,subject,variableType,units,databaseStart,variableStart,description -ADL_01,"intermediate, outcome_sec, table1_master",Help preparing meals,Needs help - preparing meals,Health status,ADL,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::RACA_6A, cchs2003_p::RACC_6A, cchs2005_p::RACE_6A, cchs2007_2008_p::RAC_6A, [ADL_01]", -ADL_02,"intermediate, outcome_sec, table1_master",Help appointments/errands,Needs help - getting to appointments/errands,Health status,ADL,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::RACA_6B, cchs2003_p::RACC_6B1, cchs2005_p::RACE_6B1, cchs2007_2008_p::RAC_6B1, [ADL_02]", -ADL_03,"intermediate, outcome_sec, table1_master",Help housework,Needs help - doing housework,Health status,ADL,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::RACA_6C, cchs2003_p::RACC_6C, cchs2005_p::RACE_6C, cchs2007_2008_p::RAC_6C, [ADL_03]", -ADL_04,"intermediate, outcome_sec, table1_master",Help personal care,Needs help - personal care,Health status,ADL,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::RACA_6E, cchs2003_p::RACC_6E, cchs2005_p::RACE_6E, cchs2007_2008_p::RAC_6E, [ADL_04]", -ADL_05,"intermediate, outcome_sec, table1_master",Help move inside house,Needs help - moving about inside house,Health status,ADL,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::RACA_6F, cchs2003_p::RACC_6F, cchs2005_p::RACE_6F, cchs2007_2008_p::RAC_6F, [ADL_05]", -ADL_06,"intermediate, outcome_sec, table1_master",Help personal finances,Needs help - looking after finances,Health status,ADL,Categorical,N/A,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2003_p::RACC_6G, cchs2005_p::RACE_6G, cchs2007_2008_p::RAC_6G, [ADL_06]", -ADL_07,"intermediate, outcome_sec, table1_master",Help heavy household chores,Needs help - heavy household chores,Health status,ADL,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::RACA_6D, cchs2003_p::RACC_6D, cchs2005_p::RACE_6D", -ADLF6R,Drop,Help tasks,Needs help with at least one task - (F),Health status,ADL,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::RACAF6, cchs2003_p::RACCF6R, cchs2005_p::RACEF6R, cchs2007_2008_p::RACF6R, [ADLF6R]", -ADL_der,"predictor, table1_short, outcome_sec, table1_master",Help tasks,Needs help with tasks,Health status,ADL,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05]", -ADM_RNO,stratifier,Sequential record number,Sequential record number,N/A,N/A,Continuous,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::ADMA_RNO, cchs2003_p::ADMC_RNO, cchs2005_p::ADME_RNO, [ADM_RNO]", -ALC_1,intermediate,Alcohol past year,"Past year, have you drank alcohol",Health behaviour,Alcohol,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::ALCA_1, cchs2003_p::ALCC_1, cchs2005_p::ALCE_1, [ALC_1]", -ALCDTTM,"predictor, table1_short, table1_master",Drinker type (last 12 months),Type of drinker (last 12 months),Health behaviour,Alcohol,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP, [ALCDTTM]", -ALW_1,intermediate,Any alcohol past week,"Past week, had any alcohol",Health behaviour,Alcohol,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::ALCA_5, cchs2003_p::ALCC_5, cchs2005_p::ALCE_5, [ALW_1]", -ALW_2A1,intermediate,DailyConsumptionSunday,Number of drinks on Sunday,Health behaviour,Alcohol,Continuous,drinks,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::ALCA_5A1, cchs2003_p::ALCC_5A1, cchs2005_p::ALCE_5A1, [ALW_2A1]", -ALW_2A2,intermediate,# of drinks - Monday,Number of drinks on Monday,Health behaviour,Alcohol,Continuous,drinks,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::ALCA_5A2, cchs2003_p::ALCC_5A2, cchs2005_p::ALCE_5A2, [ALW_2A2]", -ALW_2A3,intermediate,# of drinks - Sunday,Number of drinks on Tuesday,Health behaviour,Alcohol,Continuous,drinks,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::ALCA_5A3, cchs2003_p::ALCC_5A3, cchs2005_p::ALCE_5A3, [ALW_2A3]", -ALW_2A4,intermediate,# of drinks - Sunday,Number of drinks on Wednesday,Health behaviour,Alcohol,Continuous,drinks,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::ALCA_5A4, cchs2003_p::ALCC_5A4, cchs2005_p::ALCE_5A4, [ALW_2A4]", -ALW_2A5,intermediate,# of drinks - Sunday,Number of drinks on Thursday,Health behaviour,Alcohol,Continuous,drinks,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::ALCA_5A5, cchs2003_p::ALCC_5A5, cchs2005_p::ALCE_5A5, [ALW_2A5]", -ALW_2A6,intermediate,# of drinks - Sunday,Number of drinks on Friday,Health behaviour,Alcohol,Continuous,drinks,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::ALCA_5A6, cchs2003_p::ALCC_5A6, cchs2005_p::ALCE_5A6, [ALW_2A6]", -ALW_2A7,intermediate,# of drinks - Sunday,Number of drinks on Saturday,Health behaviour,Alcohol,Continuous,drinks,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::ALCA_5A7, cchs2003_p::ALCC_5A7, cchs2005_p::ALCE_5A7, [ALW_2A7]", -ALWDWKY,"predictor, table1_long, table1_master",Drinks last week,Weekly consumption of alcohol,Health behaviour,Alcohol,Continuous,drinks/week,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::ALCADWKY, cchs2003_p::ALCCDWKY, cchs2005_p::ALCEDWKY, [ALWDWKY]", -binge_drinker,"predictor, table1_long, table1_master",Binge Drinker,Binge Drinker,Health behaviour,Alcohol,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p, cchs2015","DerivedVar::[DHH_SEX, ALW_1, ALW_2A1, ALW_2A2, ALW_2A3, ALW_2A4, ALW_2A5, ALW_2A6, ALW_2A7]", -CCC_031,"predictor, table1_long, table1_master",Asthma,Do you have asthma?,Health status,Chronic condition,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::CCCA_031, cchs2003_p::CCCC_031, cchs2005_p::CCCE_031, [CCC_031]", -CCC_041,Drop,Fibromyalgia,Do you have Fibromyalgia?,Health status,Chronic condition,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2014_p","cchs2001_p::CCCA_041, cchs2003_p::CCCC_041, cchs2005_p::CCCE_041, [CCC_041]", -CCC_051,"predictor, table1_short, table1_master, outcome_sec",Arthritis/Rheumatism,Do you have arthritis or rheumatism?,Health status,Chronic condition,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::CCCA_051, cchs2003_p::CCCC_051, cchs2005_p::CCCE_051, [CCC_051]", -CCC_061,"predictor, table1_short, table1_master, outcome_sec",Back problems,Do you have back problems?,Health status,Chronic condition,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::CCCA_061, cchs2003_p::CCCC_061, cchs2005_p::CCCE_061, [CCC_061]", -CCC_071,"predictor, table1_short, table1_master, outcome_sec",Hypertension,Do you have high blood pressure,Health status,Chronic condition,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::CCCA_071, cchs2003_p::CCCC_071, cchs2005_p::CCCE_071, [CCC_071]", -CCC_073,Drop,Hypertension medication,In the past month have you taken any medicine for high blood pressure?,Health status,Chronic condition,Categorical,N/A,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2005_p::CCCE_073, [CCC_073]", -CCC_091,Drop,COPD/Emphysema,"Do you have COPD (eg bronchitis, emphysema)",Health status,Chronic condition,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::CCCA_91B, cchs2003_p::CCCC_91B, [CCC_091]", -CCC_101,"predictor, table1_short, table1_master, outcome_sec",Diabetes,Do you have diabetes,Health status,Chronic condition,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::CCCA_101, cchs2003_p::CCCC_101, cchs2005_p::CCCE_101, [CCC_101]", -CCC_121,"predictor, table1_short, table1_master, outcome_sec",Heart Disease,Do you have heart disease,Health status,Chronic condition,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::CCCA_121, cchs2003_p::CCCC_121, cchs2005_p::CCCE_121, [CCC_121]", -CCC_131,"predictor, table1_short, table1_master, outcome_sec",Active Cancer,Do you have cancer,Health status,Chronic condition,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::CCCA_131, cchs2003_p::CCCC_131, cchs2005_p::CCCE_131, [CCC_131]", -CCC_151,"predictor, table1_short, table1_master, outcome_sec",Stroke,Do you suffer from effects of stroke,Health status,Chronic condition,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::CCCA_151, cchs2003_p::CCCC_151, cchs2005_p::CCCE_151, [CCC_151]", -CCC_171,"predictor, table1_short, table1_master, outcome_sec",Bowel disorder,Do you have a bowel disorder such as Crohn's disease or colitis?,Health status,Chronic condition,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::CCCA_171, cchs2003_p::CCCC_171, cchs2005_p::CCCE_171, [CCC_171]", -CCC_251,Drop,Chronic fatigue,Do you have chronic fatigue syndrome?,Health status,Chronic condition,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::CCCA_251, cchs2003_p::CCCC_251, cchs2005_p::CCCE_251, [CCC_251]", -CCC_280,"predictor, table1_short, table1_master, outcome_sec",Mood disorder,Do you have a mood disorder,Health status,Chronic condition,Categorical,N/A,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2003_p::CCCC_280, cchs2005_p::CCCE_280, [CCC_280]", -CCC_31A,"predictor, table1_long, table1_master",Cancer diagnosis,Have you ever been diagnosed with cancer?,Health status,Chronic condition,Categorical,N/A,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2005_p::CCCE_31A, [CCC_31A]", -CCC_91A,"predictor, table1_long, table1_master",Bronchitis,Do you have chronic bronchitis?,Health status,Chronic condition,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2001_p::CCCA_91A, cchs2003_p::CCCC_91A, cchs2005_p::CCCE_91A, [CCC_91A]", -CCC_91E,Drop,Emphysema,Do you have emphysema?,Health status,Chronic condition,Categorical,N/A,"cchs2005_p, cchs2007_2008_p","cchs2005_p::CCCE_91E, cchs2007_2008_p::CCC_91E", -CCC_91F,Drop,COPD,Do you have COPD?,Health status,Chronic condition,Categorical,N/A,"cchs2005_p, cchs2007_2008_p","cchs2005_p::CCCE_91F, cchs2007_2008_p::CCC_91F", -COPD_Emph_der,"predictor, table1_long, table1_master",COPD/Emphysema,COPD/Emphysema,Health status,Chronic condition,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","DerivedVar::[DHHGAGE_cont, CCC_91E, CCC_91F], DerivedVar::[DHHGAGE_cont, CCC_091]", -DHH_OWN,"predictor, table1_long, table1_master",Home ownership,Dwelling - owned by a member of hsld,Sociodemographics,Home ownership,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::DHHA_OWN, cchs2003_p::DHHC_OWN, cchs2005_p::DHHE_OWN, [DHH_OWN]", -DHH_SEX,"predictor, table1_short, stratifier, table1_master",Sex,Sex,Demographics,Sex,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::DHHA_SEX, cchs2003_p::DHHC_SEX, cchs2005_p::DHHE_SEX, [DHH_SEX]", -DHHGAGE_C,"predictor, table1_short, table1_master",Categorical Age,Categorical age,Demographics,Age,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p",DerivedVar::[DHHHGAGE_cont], -DHHGAGE_cont,"predictor, table1_short, table1_master",Continuous Age,Converted categorical age,Demographics,Age,Continuous,Years,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::DHHAGAGE, cchs2003_p::DHHCGAGE, cchs2005_p::DHHEGAGE, [DHHGAGE]",Continuous age variable -DHHGHSZ,"intermediate, table1_master",Household size,Household size,Sociodemographics,Household size,Categorical,N/A,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2003_p::DHHCGHSZ, cchs2005_p::DHHEGHSZ, [DHHGHSZ]", -DHHGMS,"predictor, table1_short, table1_master",Marital status,Marital status - (G),Sociodemographics,Marital Status,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::DHHAGMS, cchs2003_p::DHHCGMS, cchs2005_p::DHHEGMS, [DHHGMS]", -diet_score,"predictor, table1_short, table1_master",Diet score ,"Diet score (0 to 10) based on daily consumption of fruit, vegetables and fruit juice",Health behaviour,Diet,Continuous,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","DerivedVar::[FVCDFRU, FVCDSAL, FVCDPOT, FVCDCAR, FVCDVEG, FVCDJUI, DHH_SEX]","A derived diet variable based on daily consumption of ""fruit, salad, potatoes, carrots, other vegetables, and juice"". Two baseline points plus summation of total points for diet attributes with penalty for high potato intake, no carrot intake and high juice consumption (negative overall scores are recoded to 0, resulting in a range from 0 to 10)." -DPSDSF,"predictor, table1_short, table1_master, outcome_sec",Depression Scale - Short Form Score,Depression Scale - Short Form Score,Health status,Chronic condition,Continuous,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::DPSADSF, cchs2003_p::DPSCDSF, cchs2005_p::DPSEDSF, [DPSDSF]", -EDUDR04,"predictor, table1_short, table1_master",Highest education,Highest level/education,Sociodemographics,Education,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::EDUADR04, cchs2003_p::EDUCDR04, cchs2005_p::EDUEDR04, [EDUDR04]", -FINF1,intermediate,Food insecurity 12M,Some food insecurity in past 12 months,Sociodemographics,Food security,Categorical,N/A,"cchs2001_p, cchs2003_p","cchs2001_p::FINAF1, cchs2003_p::FINCF1", -FLU_160,"table1_long, table1_master",Ever had a flu shot,Have you ever had a flu shot?,Health care use,Vaccination,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::FLUA_160, cchs2003_p::FLUC_160, cchs2005_p::FLUE_160, [FLU_160]", -FLU_162,"table1_long, table1_master",Last time had flu shot,When did you have your last flu shot?,Health care use,Vaccination,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::FLUA_162, cchs2003_p::FLUC_162, cchs2005_p::FLUE_162, [FLU_162]", -food_insecurity_der,"predictor, table1_master",Food insecurity (last 12 months),Derived food insecurity,Sociodemographics,Food security,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","DerivedVar::[FINF1], DerivedVar::[FSCDHFS], DerivedVar::[FSCDHFS2]", -FSCDHFS,"table1_long, table1_master",Food security,Household food security status - (D),Sociodemographics,Food security,Categorical,N/A,cchs2005_p,[FSCEDHFS], -FSCDHFS2,intermediate,HC food security,Household food security status - (HC),Sociodemographics,Food security,Categorical,N/A,"cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p",[FSCDHFS2], -FVCDCAR,"intermediate, z_score",Carrot consumption,Daily consumption - carrots (D),Health behaviour,Diet,Continuous,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::FVCADCAR, cchs2003_p::FVCCDCAR, cchs2005_p::FVCEDCAR, [FVCDCAR]", -FVCDFRU,"intermediate, z_score",Fruit consumption,Daily consumption - fruit - (D),Health behaviour,Diet,Continuous,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::FVCADFRU, cchs2003_p::FVCCDFRU, cchs2005_p::FVCEDFRU, [FVCDFRU]", -FVCDJUI,"intermediate, z_score",Juice consumption,Daily consumption - fruit juice (D),Health behaviour,Diet,Continuous,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::FVCADJUI, cchs2003_p::FVCCDJUI, cchs2005_p::FVCEDJUI, [FVCDJUI]", -FVCDPOT,"intermediate, z_score",Potato consumption,Daily consumption - potatoes (D),Health behaviour,Diet,Continuous,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::FVCADPOT, cchs2003_p::FVCCDPOT, cchs2005_p::FVCEDPOT, [FVCDPOT]", -FVCDSAL,"intermediate, z_score",Salad consumption,Daily consumption - green salad - (D),Health behaviour,Diet,Continuous,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::FVCADSAL, cchs2003_p::FVCCDSAL, cchs2005_p::FVCEDSAL, [FVCDSAL]", -FVCDTOT,"table1_long, table1_master",Total fruit/veg consumption,Daily consumptoin - total fruits and veg. - (D),Health behaviour,Diet,Continuous,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::FVCADTOT, cchs2003_p::FVCCDTOT, cchs2005_p::FVCEDTOT, [FVCDTOT]", -FVCDVEG,"intermediate, z_score",Other veg consumption,Daily consumption other vegetables - (D),Health behaviour,Diet,Continuous,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::FVCADVEG, cchs2003_p::FVCCDVEG, cchs2005_p::FVCEDVEG, [FVCDVEG]", -GEN_01,"predictor, table1_short, outcome_sec, table1_master",Self perceived health,Self perceived health,Health behaviour,Self-perceived health,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::GENA_01, cchs2003_p::GENC_01, cchs2005_p::GENE_01, [GEN_01]", -GEN_02A,"predictor, outcome_sec, table1_master, table1_long",Life satisfaction_cat,Satisfaction with life,Health behaviour,Life satisfaction,Categorical,N/A,"cchs2003_p, cchs2005_p, cchs2007_2008_p","cchs2003_p::GENC_02A, cchs2005_p::GENE_02A, [GEN_02A]", -GEN_02A2,"predictor, outcome_sec, table1_master",Life satisfaction_cont,Satisfaction with life in general,Health behaviour,Life satisfaction,Continuous,N/A,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2003_p::GENC_02A, cchs2005_p::GENE_02A, cchs2007_2008_p::GEN_02A, [GEN_02A2]", -GEN_02B,"predictor, outcome_sec, table1_master, table1_long",Self-perceived mental health,Self-perceived mental health,Health behaviour,Mental health,Categorical,N/A,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2003_p::GENC_02B, cchs2005_p::GENE_02B, [GEN_02B]", -GEN_07,"predictor, outcome_sec, table1_master, table1_long",Self-perceived life stress,Self perceived life stress,Health behaviour,Mental health,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::GENA_07, cchs2003_p::GENC_07, cchs2005_p::GENE_07, [GEN_07]", -GEN_09,"predictor, outcome_sec, table1_master, table1_long",Self-perceived work stress,Self perceived work stress,Health behaviour,Mental health,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::GENA_09, cchs2003_p::GENC_09, cchs2005_p::GENE_09, [GEN_09]", -GEN_10,"predictor, outcome_sec, table1_master, table1_long",Sense of belonging,Sense of belonging in the community,Health behaviour,Mental health,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::GENA_10, cchs2003_p::GENC_10, cchs2005_p::GENE_10, [GEN_10]", -GEOGPRV,"stratifier, table1_master",Province,Province of residence of respondent (G),Province,Province,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::GEOAGPRV, cchs2003_p::GEOCGPRV, cchs2005_p::GEOEGPRV, [GEOGPRV]", -HCU_1AA,"predictor, table1_master, table1_short",Has regular medical doctor,Do you have a regular medical doctor?,Health care use,Medical care,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::TWDA_5, cchs2003_p::HCUC_1AA, cchs2005_p::HCUE_1AA, [HCU_1AA]", -HUIDCOG,"outcome_sec, table1_master, table1_long",HUI Cognition,Cognition prob. - function code - (D),Health status,HUI Cognition,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2013_2014_p","cchs2001_p::HUIADCOG, cchs2003_p::HUICDCOG, cchs2005_p::HUIEDCOG, [HUIDCOG]", -HUIDEMO,"outcome_sec, table1_master, table1_long",HUI Emotion,Emotional problems - function code - (D),Health status,HUI Emotion,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2013_2014_p","cchs2001_p::HUIADEMO, cchs2003_p::HUICDEMO, cchs2005_p::HUIEDEMO, [HUIDEMO]", -HUIDHSI,"outcome, table1_short, table1_master",Overall HUI,Health Utility Index (HUI3) - (D),Health status,Health utility index,Continuous,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2013_2014_p","cchs2001_p::HUIADHSI, cchs2003_p::HUICDHSI, cchs2005_p::HUIEDHSI, [HUIDHSI]", -HUIGDEX,"outcome_sec, table1_master, table1_long",HUI Dexterity,"Dexterity trouble - function code (D, G)",Health status,HUI Dexterity,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2013_2014_p","cchs2001_p::HUIAGDEX, cchs2003_p::HUICGDEX, cchs2005_p::HUIEGDEX, [HUIGDEX]", -HUIGHER,"outcome_sec, table1_master, table1_long",HUI Hearing,"Hearing problems - function code (D, G)",Health status,HUI Hearing,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2013_2014_p","cchs2001_p::HUIAGHER, cchs2003_p::HUICGHER, cchs2005_p::HUIEGHER, [HUIGHER]", -HUIGMOB,"outcome_sec, table1_master, table1_long",HUI Mobility,"Mobility trouble - function code (D, G)",Health status,HUI Mobility,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2013_2014_p","cchs2001_p::HUIAGMOB, cchs2003_p::HUICGMOB, cchs2005_p::HUIEGMOB, [HUIGMOB]", -HUIGSPE,"outcome_sec, table1_master, table1_long",HUI Speech,"Speech trouble - function code - (D, G)",Health status,HUI Speech,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2013_2014_p","cchs2001_p::HUIAGSPE, cchs2003_p::HUICGSPE, cchs2005_p::HUIEGSPE, [HUIGSPE]", -HUIGVIS,"outcome_sec, table1_master, table1_long",HUI Vision,"Vision trouble - function code - (D, G)",Health status,HUI Vision,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2013_2014_p","cchs2001_p::HUIAGVIS, cchs2003_p::HUICGVIS, cchs2005_p::HUIEGVIS, [HUIGVIS]", -HUPDPAD,"outcome_sec, table1_master, table1_long",HUI Pain,Act. prevent/pain - function code - (D),Health status,HUI Pain,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2013_2014_p","cchs2001_p::HUIADPAD, cchs2003_p::HUICDPAD, cchs2005_p::HUIEDPAD, [HUPDPAD]", -HWTGBMI_der,"predictor, table1_short, table1_master",Derived BMI,Derived Body Mass Index,Health status,BMI,Continuous,kg/m2,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","DerivedVar::[HWTGHTM, HWTGWTK]", -HWTGHTM,intermediate,Height,"Height (metres)/self-reported - (D,G)",Health status,Height,Continuous,meters,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT, cchs2005_p::HWTEGHTM, [HWTGHTM]", -HWTGWTK,intermediate,Weight,"Weight - kilograms (D, G)",Health status,Weight,Continuous,kg,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::HWTAGWTK, cchs2003_p::HWTCGWTK, cchs2005_p::HWTEGWTK, [HWTGWTK]", -id_year,id,Unique ID,Unique ID,N/A,N/A,Continuous,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","DerivedVar::[data_name, ADM_RNO]", -INCDRCA,"predictor, table1_short, table1_master",Household income distribution,Household income distribution - (D),Sociodemographics,Income,Categorical,N/A,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2005_p::INCEDRCA, [INCDRCA]", -INCDRPR,"table1_long, table1_master",Household income distribution provincial level,Hhld inc. distribution-prov. level - (D),Sociodemographics,Income,Categorical,N/A,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2005_p::INCEDRPR, [INCDRPR]", -INCGHH_cont,"table1_long, table1_master",Household income,Total household income from all sources - continuous,Sociodemographics,Income,Continuous,$/year,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::INCAGHH, cchs2003_p::INCCGHH, cchs2005_p::INCEGHH, [INCGHH]", -INCGPER_cont,"table1_long, table1_master",Personal Income,"Total pers. inc. from all sources (D, G)",Sociodemographics,Income,Continuous,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::INCAGPER, cchs2003_p::INCCGPER, cchs2005_p::INCEGPER, [INCGPER]", -LBFA_31A_a,"table1_long, table1_master",Occupation group (5 categories),Occupation group (5 categories),Sociodemographics,Occupation,Categorical,N/A,"cchs2001_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::LBFA_31A, [LBSGSOC]", -number_conditions,"predictor, table1_short, table1_master",Number of chronic conditions,Number of chronic conditions,Health status,Chronic condition,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","DerivedVar::[CCC_121, CCC_131, CCC_151, CCC_171, CCC_280, resp_condition, CCC_051]", -PAC_4A,intermediate,Time walk work/school in week,"In a typical week in the past 3 months, how many hours did you usually spend walking to work or to school or while doing errands",Health behaviour,Exercise,Categorical,hours/week,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::PACA_4A, cchs2003_p::PACC_4A, cchs2005_p::PACE_4A", -PAC_4B,intermediate,Time bike work/school in week,"In a typical week in the past 3 months, how many hours did you usually spend walking to work or to school or while doing errands",Health behaviour,Exercise,Categorical,hours/week,"cchs2001_p, cchs2003_p, cchs2005_p","cchs2001_p::PACA_4B, cchs2003_p::PACC_4B, cchs2005_p::PACE_4B", -PAC_7,intermediate,Walk to work/school,Walked to work or school / last 3 mo.,Health behaviour,Exercise,Categorical,N/A,"cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p",[PAC_7], -PAC_7A,intermediate,Number times walk work/school,No. of times/3 mo./walking work/school,Health behaviour,Exercise,Continuous,N/A,"cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p",[PAC_7A], -PAC_7B,intermediate,Time walk work/school,Time spent - walking to go work/school,Health behaviour,Exercise,Categorical,mins,"cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p",[PAC_7B], -PAC_8,intermediate,Bike to work/school,Bicycled to work or school / last 3 mo.,Health behaviour,Exercise,Categorical,N/A,"cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p",[PAC_8], -PAC_8A,intermediate,Number times bike work/school,No. of times/3 mo./bicycl. work/school,Health behaviour,Exercise,Continuous,times/3 mos.,"cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p",[PAC_8A], -PAC_8B,intermediate,Time bike work/school,Time spent - walking to go work/school,Health behaviour,Exercise,Categorical,N/A,"cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p",[PAC_8B], -PACDEE,"predictor, table1_short, table1_master",Physical activity,Daily energy expenditure - (D),Health behaviour,Exercise,Continuous,METS,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::PACADEE, cchs2003_p::PACCDEE, cchs2005_p::PACEDEE, [PACDEE]", -pack_years_der,"predictor, table1_long, table1_master",Smoking pack-years,Smoking pack-years,Health behaviour,Smoking,Continuous,Years,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","DerivedVar::[SMKDSTY_A, DHHGAGE_cont, time_quit_smoking, SMKG203_cont, SMKG207_cont, SMK_204, SMK_05B, SMK_208, SMK_05C, SMKG01C_cont, SMK_01A]", -pct_time_der,"predictor, table1_long, table1_master",Percent time in Canada,Percentage of time in Canada,Sociodemographics,Migration,Continuous,%,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","DerivedVar::[DHHGAGE_cont, SDCGCBG, SDCGRES]", -RAC_1,"intermediate, outcome_sec, table1_master",Difficulty activities,Has difficulty with activities,Health status,ADL,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::RACA_1, cchs2003_p::RACC_1, cchs2005_p::RACE_1, [RAC_1]", -RAC_2A,"intermediate, outcome_sec, table1_master",Reduction activities at home,Reduction - activities at home,Health status,ADL,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::RACA_2A, cchs2003_p::RACC_2A, cchs2005_p::RACE_2A, [RAC_2A]", -RAC_2B,"intermediate, outcome_sec, table1_master",Reduction activities at school or work,Long-term cond. reduces act. - school or work,Health status,ADL,Categorical,N/A,cchs2001_p,cchs2001_p::RACA_2B, -RAC_2B1,"intermediate, outcome_sec, table1_master",Reduction activities at school,Long-term cond. reduces act. - school,Health status,ADL,Categorical,N/A,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2003_p::RACC_2B1, cchs2005_p::RACE_2B1, [RAC_2B1]", -RAC_2B2,"intermediate, outcome_sec, table1_master",Reduction activities at work,Reduction kind/amount act. - at work,Health status,ADL,Categorical,N/A,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2003_p::RACC_2B2, cchs2005_p::RACE_2B2, [RAC_2B2]", -RAC_2C,"intermediate, outcome_sec, table1_master",Reduction other activities,Reduction - other activities,Health status,ADL,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::RACA_2C, cchs2003_p::RACC_2C, cchs2005_p::RACE_2C, [RAC_2C]", -RACDIMP,"predictor, table1_short, outcome_sec, table1_master",Impact health problem,Impact of health problems,Health status,Chronic condition,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::RACADIMP, cchs2003_p::RACCDIMP, cchs2005_p::RACEDIMP, [RACDIMP]", -RACDPAL,"predictor, table1_short, outcome_sec, table1_master",Particpation/activity limitation,Participation and activity limitation,Health status,ADL,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::[DerivedVar::[RAC_1, RAC_2A, RAC_2B, RAC_2C]], cchs2003_p::RACCDPAL, cchs2005_p::RACEDPAL, [RACDPAL]", -RACG5,"predictor, table1_short, table1_master",Cause health problem,Cause of Health problem,Health status,Chronic condition,Categorical,N/A,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2003_p::RACCG5, cchs2005_p::RACEG5, [RACG5]", -resp_condition_der,"predictor, table1_short, table1_master",Respiratory Condition,Respiratory condition,Health status,Chronic condition,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","DerivedVar::[DHHGAGE_cont, CCC_091], DerivedVar::[DHHGAGE_cont, CCC_91E, CCC_91F, CCC_91A], DerivedVar::[DHHGAGE_cont, CCC_091, CCC_91A]", -SDCFIMM,"predictor, table1_short, table1_master",Immigrant status,Immigrant Status (D),Sociodemographics,Migration,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::SDCAFIMM, cchs2003_p::SDCCFIMM, cchs2005_p::SDCEFIMM, [SDCFIMM]", -SDCGCBG,"predictor, table1_short, table1_master",Country of birth,Country of birth - (G),Sociodemographics,Migration,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::SDCAGCBG, cchs2003_p::SDCCGCBG, cchs2005_p::SDCEGCBG, cchs2011_2012_p::SDCGCB12::SDCGCB12, cchs2013_2014_p::SDCGCB13::SDCGCB13, [SDCGCBG]", -SDCGCGT,"predictor, table1_short, table1_master",Ethnicity,"Cultural or racial origin - (D, G)",Sociodemographics,Ethnicity,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::SDCAGRAC, cchs2003_p::SDCCGRAC, cchs2005_p::SDCEGCGT, [SDCGCGT]", -SDCGRES,intermediate,Time in Canada,"Length/time in Canada since imm. (D, G)",Sociodemographics,Migration,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::SDCAGRES, cchs2003_p::SDCCGRES, cchs2005_p::SDCEGRES, [SDCGRES]", -SLPG01_cont,"predictor, table1_long, table1_master",Hours sleep,No./hours spent sleeping each night,Health behaviour,Sleep,Continuous,N/A,"cchs2001_p, cchs2007_2008_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::GENA_03, cchs2007_2008_p::SLP_01, [SLPG01]", -SMK_01A,intermediate,s100,"In lifetime, smoked 100 or more cigarettes",Health behaviour,Smoking,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::SMKA_01A, cchs2003_p::SMKC_01A, cchs2005_p::SMKE_01A, [SMK_01A]", -SMK_05B,intermediate,cigdayo,# of cigarettes smoked daily - occasional smoker,Health behaviour,Smoking,Continuous,cigarettes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::SMKA_05B, cchs2003_p::SMKC_05B, cchs2005_p::SMKE_05B, [SMK_05B]", -SMK_05C,intermediate,dayocc,# days smoked at least 1 cigarette,Health behaviour,Smoking,Continuous,days,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::SMKA_05C, cchs2003_p::SMKC_05C, cchs2005_p::SMKE_05C, [SMK_05C]", -SMK_05D,intermediate,evd,Ever smoked cigarettes daily - occasional smoker,Health behaviour,Smoking,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::SMKA_05D, cchs2003_p::SMKC_05D, cchs2005_p::SMKE_05D, [SMK_05D]", -SMK_06A_A,intermediate,stpn,When did you stop smoking daily - never daily,Health behaviour,Smoking,Categorical,Years,cchs2001_p,cchs2001_p::SMKA_06A, -SMK_06A_B,intermediate,stpn,When did you stop smoking daily - occasional,Health behaviour,Smoking,Categorical,Years,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2003_p::SMKC_06A, cchs2005_p::SMKE_06A, [SMK_06A]", -SMK_06A_cont,intermediate,stpn,When did you stop smoking daily - occasional,Health behaviour,Smoking,Continuous,Years,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::SMKA_06A, cchs2003_p::SMKC_06A, cchs2005_p::SMKE_06A, [SMK_06A]", -SMK_09A_A,intermediate,stpd,When did you stop smoking daily - former daily,Health behaviour,Smoking,Categorical,Years,cchs2001_p,cchs2001_p::SMKA_09A, -SMK_09A_B,intermediate,stpd,When did you stop smoking daily - former daily,Health behaviour,Smoking,Categorical,Years,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, [SMK_09A]", -SMK_09A_cont,intermediate,stpd,When did you stop smoking daily - former daily,Health behaviour,Smoking,Continuous,Years,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::SMKA_09A, cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, [SMK_09A]", -SMK_204,intermediate,cigdayd,# of cigarettes smoked daily - daily smoker,Health behaviour,Smoking,Continuous,cigarettes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::SMKA_204, cchs2003_p::SMKC_204, cchs2005_p::SMKE_204, [SMK_204]", -SMK_208,intermediate,cigdayf,# of cigarettes smoke each day - former daily,Health behaviour,Smoking,Continuous,cigarettes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::SMKA_208, cchs2003_p::SMKC_208, cchs2005_p::SMKE_208, [SMK_208]", -SMKDSTY,Drop,Smoking status,Type of smoker,Health behaviour,Smoking,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]", -SMKDSTY_A,intermediate,Smoking status,"Type of smoker: daily, occasional, always occasional, former daily, former occasional, never",Health behaviour,Smoking,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]","2015 onwards for smoke status still has 6 categories, but removed 'always occasional' (Never daily current occasional smoker) and added 'experimental' (at least 1 cig, non-smoker now)" -SMKG01C_A,intermediate,agec1,Age smoked first cigarette,Health behaviour,Smoking,Categorical,Years,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C", -SMKG01C_B,intermediate,agec1,Age smoked first cigarette,Health behaviour,Smoking,Categorical,Years,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2005_p::SMKEG01C, [SMKG01C]", -SMKG01C_cont,intermediate,agec1,Age smoked first cigarette,Health behaviour,Smoking,Continuous,Years,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C, cchs2005_p::SMKEG01C, [SMKG01C]", -SMKG06C,intermediate,stpny,Years since stopped smoking daily - never daily,Health behaviour,Smoking,Categorical,Years,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2003_p::SMKCG06C, cchs2005_p::SMKEG06C, [SMKG06C]", -SMKG09C,intermediate,stpdy,Years since stopped smoking daily - former daily,Health behaviour,Smoking,Categorical,Years,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2003_p::SMKCG09C, cchs2005_p::SMKEG09C, [SMKG09C]", -SMKG203_A,intermediate,agecigd,Age started to smoke daily - daily smoker (G),Health behaviour,Smoking,Categorical,Years,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203", -SMKG203_B,intermediate,agecigd,Age started to smoke daily - daily smoker (G),Health behaviour,Smoking,Categorical,Years,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2005_p::SMKEG203, [SMKG203]", -SMKG203_cont,intermediate,agecigd,Age started to smoke daily - daily smoker (G),Health behaviour,Smoking,Continuous,Years,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2005_p::SMKEG203, [SMKG203]", -SMKG207_A,intermediate,agecigfd,Age started to smoke daily - former daily smoker,Health behaviour,Smoking,Categorical,Years,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207", -SMKG207_B,intermediate,agecigfd,Age started to smoke daily - former daily smoker,Health behaviour,Smoking,Categorical,Years,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2005_p::SMKEG207, [SMKG207]", -SMKG207_cont,Drop,agecigfd,Age started to smoke daily - former daily smoker,Health behaviour,Smoking,Continuous,Years,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207, cchs2005_p::SMKEG207, [SMKG207]", -smoke_simple,"predictor, table1_short, table1_master",Simple smoking status,Simple smoking status,Health behaviour,Smoking,Categorical,N/A,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s","DerivedVar::[SMKDSTY_cat5, time_quit_smoking]", -SurveyCycle,survey-cycle,Survey year,Represents the survey cycle from where the observation came from,N/A,N/A,Categorical,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[data_name], -time_quit_smoking,"intermediate, table1_master",Time since quit,Time since quit smoking,Health behaviour,Smoking,Continuous,Years,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","DerivedVar::[SMK_09A_B, SMKG09C]", -WTS_M,survey_design,Weight,Weights,N/A,N/A,Continuous,N/A,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2011_2012_p, cchs2013_2014_p","cchs2001_p::WTSAM, cchs2003_p::WTSC_M, cchs2005_p::WTSE_M, [WTS_M]", -potato_add,"intermediate, z_score",,,Health behaviour,Diet,Continuous,N/A,WorkingData::2,[FVCDPOT], -potato_minus,"intermediate, z_score",,,Health behaviour,Diet,Continuous,N/A,WorkingData::2,[FVCDPOT], -FVCDCAR_Z,intermediate,,,Health behaviour,Diet,Continuous,N/A,WorkingData::3,[FVCDCAR], -FVCDFRU_Z,intermediate,,,Health behaviour,Diet,Continuous,N/A,WorkingData::3,[FVCDFRU], -FVCDJUI_Z,intermediate,,,Health behaviour,Diet,Continuous,N/A,WorkingData::3,[FVCDJUI], -FVCDPOT_Z,intermediate,,,Health behaviour,Diet,Continuous,N/A,WorkingData::3,[FVCDPOT], -FVCDSAL_Z,intermediate,,,Health behaviour,Diet,Continuous,N/A,WorkingData::3,[FVCDSAL], -FVCDVEG_Z,intermediate,,,Health behaviour,Diet,Continuous,N/A,WorkingData::3,[FVCDVEG], -potato_add_Z,intermediate,,,Health behaviour,Diet,Continuous,N/A,WorkingData::3,[potato_add], -potato_minus_Z,intermediate,,,Health behaviour,Diet,Continuous,N/A,WorkingData::3,[potato_minus], -diet_score_simp,"predictor, table1_long",Simplified Diet Score,Simplified Diet Score,Health behaviour,Diet,Continuous,N/A,WorkingData::4,"[FVCDCAR_Z, FVCDFRU_Z, FVCDJUI_Z, FVCDPOT_Z, FVCDSAL_Z, potato_add_Z, potato_minus_Z] - -FVCDVEG_z, potato_add_z, potato_minus_z]", \ No newline at end of file diff --git a/Worksheets/phiatyll_variables_details.csv b/Worksheets/phiatyll_variables_details.csv deleted file mode 100644 index 30975ea..0000000 --- a/Worksheets/phiatyll_variables_details.csv +++ /dev/null @@ -1,21 +0,0 @@ -variable,dummyVariable,typeEnd,databaseStart,variableStart,typeStart,recEnd,numValidCat,catLabel,catLabelLong,units,recStart,catStartLabel,variableStartShortLabel,variableStartLabel,notes -SMKDSTY,SMKDSTY_cat6_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,1,6,Daily,Daily smoker,N/A,1,Daily,Smoke status,Type of smoker - (D), -SMKDSTY,SMKDSTY_cat6_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,2,6,Occassional (former daily),Former daily current occasional smoker,N/A,2,Occassional,Smoke status,Type of smoker - (D), -SMKDSTY,SMKDSTY_cat6_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,3,6,Always occassional,Never daily current occasional smoker,N/A,3,Always occassional,Smoke status,Type of smoker - (D), -SMKDSTY,SMKDSTY_cat6_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,4,6,Former daily,Former daily current nonsmoker,N/A,4,Former daily,Smoke status,Type of smoker - (D), -SMKDSTY,SMKDSTY_cat6_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,5,6,Former occasional,Never daily current nonsmoker (former occasional),N/A,5,Former occasional,Smoke status,Type of smoker - (D), -SMKDSTY,SMKDSTY_cat6_6,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,6,6,Never smoked,Never smoked,N/A,6,Never smoked,Smoke status,Type of smoker - (D), -SMKDSTY,SMKDSTY_cat6_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,NA::a,6,not applicable,not applicable,N/A,96,not applicable,Smoke status,Type of smoker - (D), -SMKDSTY,SMKDSTY_cat6_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, [SMKDSTY]",cat,NA::b,6,missing,missing,N/A,"[97,99]",don't know (97); refusal (98); not stated (99),Smoke status,Type of smoker - (D), -SurveyCycle,N/A,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[data_name],N/A,cchs2001_p,10,2001,2001 cycle,N/A,N/A,N/A,Dataset name,Dataset name, -SurveyCycle,N/A,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[data_name],N/A,cchs2003_p,10,2003,2003 cycle,N/A,N/A,N/A,Dataset name,Dataset name, -SurveyCycle,N/A,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[data_name],N/A,cchs2005_p,10,2005,2005 cycle,N/A,N/A,N/A,Dataset name,Dataset name, -SurveyCycle,N/A,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[data_name],N/A,cchs2007_2008_p,10,2007 to 2008,2007 to 2008 cycle,N/A,N/A,N/A,Dataset name,Dataset name, -SurveyCycle,N/A,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[data_name],N/A,cchs2009_2010_p,10,2009 to 2010,2009 to 2010 cycle,N/A,N/A,N/A,Dataset name,Dataset name, -SurveyCycle,N/A,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[data_name],N/A,cchs2011_2012_p,10,2011 to 2012,2011 to 2012 cycle,N/A,N/A,N/A,Dataset name,Dataset name, -SurveyCycle,N/A,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[data_name],N/A,cchs2013_2014_p,10,2013 to 2014,2013 to 2014 cycle,N/A,N/A,N/A,Dataset name,Dataset name, -SurveyCycle,N/A,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[data_name],N/A,cchs2015_2016_p,10,2015 to 2016,2015 to 2016 cycle,N/A,N/A,N/A,Dataset name,Dataset name, -SurveyCycle,N/A,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[data_name],N/A,cchs2017_2018_p,10,2017 to 2018,2017 to 2018 cycle,N/A,N/A,N/A,Dataset name,Dataset name, -SurveyCycle,N/A,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[data_name],N/A,Func::SurveyCycle.fun,10,N/A,N/A,N/A,N/A,N/A,N/A,N/A, -SurveyCycle,N/A,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[data_name],N/A,NA::a,10,not applicable,not applicable,N/A,N/A,N/A,Dataset name,Dataset name, -SurveyCycle,N/A,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p",DerivedVar::[data_name],N/A,NA::b,10,missing,missing,N/A,N/A,N/A,Dataset name,Dataset name, \ No newline at end of file diff --git a/_pkgdown.yml b/_pkgdown.yml new file mode 100644 index 0000000..c849f1f --- /dev/null +++ b/_pkgdown.yml @@ -0,0 +1,100 @@ +url: https://big-life-lab.github.io/MockData/ +template: + bootstrap: 5 + includes: + in_header: | + + +footer: + structure: + left: developed_by + right: built_with + components: + developed_by:

Developed by Juan Li and recodeflow contributors.

+ +reference: +- title: Main generation functions + desc: > + Generate categorical, continuous, date, and survival variables. Use `create_mock_data()` + for batch generation or individual functions for fine-grained control. + contents: + - create_cat_var + - create_con_var + - create_date_var + - create_survival_dates + - create_wide_survival_data + - create_mock_data + +- title: Configuration + desc: > + Read and validate v0.2 configuration files. Import existing recodeflow metadata + or create new configurations for mock data generation workflows. + contents: + - read_mock_data_config + - read_mock_data_config_details + - validate_mock_data_config + - validate_mock_data_config_details + - validate_mockdata_metadata + - import_from_recodeflow + +- title: Helper functions + desc: > + Utilities for metadata processing, proportions, type coercion, and data quality. + Support main generation functions or use directly for custom workflows. + contents: + - get_variable_details + - extract_proportions + - extract_distribution_params + - sample_with_proportions + - apply_missing_codes + - apply_rtype_defaults + - add_garbage + - apply_garbage + - has_garbage + - make_garbage + - generate_garbage_values + - print.mockdata_validation_result + - get_variables_by_role + - get_enabled_variables + - identify_derived_vars + - get_raw_var_dependencies + - get_cycle_variables + - get_raw_variables + +- title: Parsers + desc: > + Parse recodeflow notation for variable specifications and range syntax. + Extract structured information from metadata for mock data generation. + contents: + - parse_range_notation + - parse_variable_start + +articles: +- title: Tutorials + desc: Learning-oriented step-by-step guides + navbar: Tutorials + contents: + - getting-started + - tutorial-categorical-continuous + - tutorial-dates + - tutorial-survival-data + - tutorial-missing-data + - tutorial-garbage-data + +- title: How-to guides + desc: Task-oriented practical examples + navbar: How-to guides + contents: + - for-recodeflow-users + +- title: Explanation + desc: Understanding concepts and design decisions + navbar: Explanation + contents: + - advanced-topics + +- title: Reference + desc: Technical specifications and schema documentation + navbar: Reference + contents: + - reference-config diff --git a/inst/extdata/chms/variable_details_chmsflow_sample.csv b/inst/extdata/chms/variable_details_chmsflow_sample.csv new file mode 100644 index 0000000..16408e3 --- /dev/null +++ b/inst/extdata/chms/variable_details_chmsflow_sample.csv @@ -0,0 +1,74 @@ +variable,dummyVariable,typeEnd,databaseStart,variableStart,typeStart,recEnd,numValidCat,catLabel,catLabelLong,units,recStart,catStartLabel,variableStartShortLabel,variableStartLabel,notes +alc_11,alc_11_cat2_1,cat,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6:: ALC_11, [alc_11]",cat,1,2,Yes,Yes,N/A,1,Yes,Drank in past year,Drank alcohol - past 12 months, +alc_11,alc_11_cat2_2,cat,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6:: ALC_11, [alc_11]",cat,2,2,No,No,N/A,2,No,Drank in past year,Drank alcohol - past 12 months, +alc_11,alc_11_cat2_NA::a,cat,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6:: ALC_11, [alc_11]",cat,NA::a,2,not applicable,not applicable,N/A,6,Valid skip,Drank in past year,Drank alcohol - past 12 months, +alc_11,alc_11_cat2_NA::b,cat,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6:: ALC_11, [alc_11]",cat,NA::b,2,missing,missing,N/A,"[7, 9]",Don't know (7); Refusal (8); Not stated (9),Drank in past year,Drank alcohol - past 12 months, +alc_11,alc_11_cat2_NA::b,cat,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6:: ALC_11, [alc_11]",cat,NA::b,2,missing,missing,N/A,else,else,Drank in past year,Drank alcohol - past 12 months, +alc_17,alc_17_cat2_1,cat,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::ALC_17, [alc_17]",cat,1,2,Yes,Yes,N/A,1,Yes,Ever drank alcohol,Ever had a drink, +alc_17,alc_17_cat2_2,cat,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::ALC_17, [alc_17]",cat,2,2,No,No,N/A,2,No,Ever drank alcohol,Ever had a drink, +alc_17,alc_17_cat2_NA::a,cat,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::ALC_17, [alc_17]",cat,NA::a,2,not applicable,not applicable,N/A,6,Valid skip,Ever drank alcohol,Ever had a drink, +alc_17,alc_17_cat2_NA::b,cat,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::ALC_17, [alc_17]",cat,NA::b,2,missing,missing,N/A,"[7, 9]",Don't know (7); Refusal (8); Not stated (9),Ever drank alcohol,Ever had a drink, +alc_17,alc_17_cat2_NA::b,cat,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::ALC_17, [alc_17]",cat,NA::b,2,missing,missing,N/A,else,else,Ever drank alcohol,Ever had a drink, +alc_18,alc_18_cat2_1,cat,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::ALC_18, [alc_18]",cat,1,2,Yes,Yes,N/A,1,Yes,Drank alcohol regularly,Regularly drank more than 12 drinks a week, +alc_18,alc_18_cat2_2,cat,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::ALC_18, [alc_18]",cat,2,2,No,No,N/A,2,No,Drank alcohol regularly,Regularly drank more than 12 drinks a week, +alc_18,alc_18_cat2_NA::a,cat,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::ALC_18, [alc_18]",cat,NA::a,2,not applicable,not applicable,N/A,6,Valid skip,Drank alcohol regularly,Regularly drank more than 12 drinks a week, +alc_18,alc_18_cat2_NA::b,cat,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::ALC_18, [alc_18]",cat,NA::b,2,missing,missing,N/A,"[7, 9]",Don't know (7); Refusal (8); Not stated (9),Drank alcohol regularly,Regularly drank more than 12 drinks a week, +alc_18,alc_18_cat2_NA::b,cat,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::ALC_18, [alc_18]",cat,NA::b,2,missing,missing,N/A,else,else,Drank alcohol regularly,Regularly drank more than 12 drinks a week, +alcdwky,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::ALCDWKY, [alcdwky]",cont,copy,N/A,Drinks in week,Drinks in week,drinks/week,"[0, 84]",Number of drinks,Drinks in week," Weekly consumption - (D)", +alcdwky,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::ALCDWKY, [alcdwky]",cont,NA::a,N/A,not applicable,not applicable,drinks/week,996,Valid skip,Drinks in week," Weekly consumption - (D)", +alcdwky,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::ALCDWKY, [alcdwky]",cont,NA::b,N/A,missing,missing,drinks/week,"[997, 999]",Don't know (997); Refusal (998); Not stated (999),Drinks in week," Weekly consumption - (D)", +alcdwky,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::ALCDWKY, [alcdwky]",cont,NA::b,N/A,missing,missing,drinks/week,else,else,Drinks in week," Weekly consumption - (D)", +ammdmva1,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva1, cycle6::AMMDMVA1, [ammdmva1]",cont,copy,N/A,minutes/day,minutes/day,minutes/day,"[0, 404]",Minutes per day,Minutes of exercise per day (accelerometer Day 1),Total moderate-to-vigorous physical activity - Day 1 (min/day), +ammdmva1,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva1, cycle6::AMMDMVA1, [ammdmva1]",cont,NA::a,N/A,not applicable,not applicable,minutes/day,9996,Valid skip ,Minutes of exercise per day (accelerometer Day 1),Total moderate-to-vigorous physical activity - Day 1 (min/day), +ammdmva1,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva1, cycle6::AMMDMVA1, [ammdmva1]",cont,NA::b,N/A,missing,missing,minutes/day,"[9997, 9999]",Don't know (9997); Refusal (9998); Not stated (9999),Minutes of exercise per day (accelerometer Day 1),Total moderate-to-vigorous physical activity - Day 1 (min/day), +ammdmva1,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva1, cycle6::AMMDMVA1, [ammdmva1]",cont,NA::b,N/A,missing,missing,minutes/day,else,else,Minutes of exercise per day (accelerometer Day 1),Total moderate-to-vigorous physical activity - Day 1 (min/day), +ammdmva2,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva2, cycle6::AMMDMVA2, [ammdmva2]",cont,copy,N/A,minutes/day,minutes/day,minutes/day,"[0, 404]",Minutes per day,Minutes of exercise per day (accelerometer Day 2),Total moderate-to-vigorous physical activity - Day 2 (min/day), +ammdmva2,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva2, cycle6::AMMDMVA2, [ammdmva2]",cont,NA::a,N/A,not applicable,not applicable,minutes/day,9996,Valid skip ,Minutes of exercise per day (accelerometer Day 2),Total moderate-to-vigorous physical activity - Day 2 (min/day), +ammdmva2,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva2, cycle6::AMMDMVA2, [ammdmva2]",cont,NA::b,N/A,missing,missing,minutes/day,"[9997, 9999]",Don't know (9997); Refusal (9998); Not stated (9999),Minutes of exercise per day (accelerometer Day 2),Total moderate-to-vigorous physical activity - Day 2 (min/day), +ammdmva2,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva2, cycle6::AMMDMVA2, [ammdmva2]",cont,NA::b,N/A,missing,missing,minutes/day,else,else,Minutes of exercise per day (accelerometer Day 2),Total moderate-to-vigorous physical activity - Day 2 (min/day), +ammdmva3,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva3, cycle6::AMMDMVA3, [ammdmva3]",cont,copy,N/A,minutes/day,minutes/day,minutes/day,"[0, 404]",Minutes per day,Minutes of exercise per day (accelerometer Day 3),Total moderate-to-vigorous physical activity - Day 3 (min/day), +ammdmva3,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva3, cycle6::AMMDMVA3, [ammdmva3]",cont,NA::a,N/A,not applicable,not applicable,minutes/day,9996,Valid skip ,Minutes of exercise per day (accelerometer Day 3),Total moderate-to-vigorous physical activity - Day 3 (min/day), +ammdmva3,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva3, cycle6::AMMDMVA3, [ammdmva3]",cont,NA::b,N/A,missing,missing,minutes/day,"[9997, 9999]",Don't know (9997); Refusal (9998); Not stated (9999),Minutes of exercise per day (accelerometer Day 3),Total moderate-to-vigorous physical activity - Day 3 (min/day), +ammdmva3,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva3, cycle6::AMMDMVA3, [ammdmva3]",cont,NA::b,N/A,missing,missing,minutes/day,else,else,Minutes of exercise per day (accelerometer Day 3),Total moderate-to-vigorous physical activity - Day 3 (min/day), +ammdmva4,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva4, cycle6::AMMDMVA4, [ammdmva4]",cont,copy,N/A,minutes/day,minutes/day,minutes/day,"[0, 404]",Minutes per day,Minutes of exercise per day (accelerometer Day 4),Total moderate-to-vigorous physical activity - Day 4 (min/day), +ammdmva4,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva4, cycle6::AMMDMVA4, [ammdmva4]",cont,NA::a,N/A,not applicable,not applicable,minutes/day,9996,Valid skip ,Minutes of exercise per day (accelerometer Day 4),Total moderate-to-vigorous physical activity - Day 4 (min/day), +ammdmva4,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva4, cycle6::AMMDMVA4, [ammdmva4]",cont,NA::b,N/A,missing,missing,minutes/day,"[9997, 9999]",Don't know (9997); Refusal (9998); Not stated (9999),Minutes of exercise per day (accelerometer Day 4),Total moderate-to-vigorous physical activity - Day 4 (min/day), +ammdmva4,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva4, cycle6::AMMDMVA4, [ammdmva4]",cont,NA::b,N/A,missing,missing,minutes/day,else,else,Minutes of exercise per day (accelerometer Day 4),Total moderate-to-vigorous physical activity - Day 4 (min/day), +ammdmva5,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva5, cycle6::AMMDMVA5, [ammdmva5]",cont,copy,N/A,minutes/day,minutes/day,minutes/day,"[0, 404]",Minutes per day,Minutes of exercise per day (accelerometer Day 5),Total moderate-to-vigorous physical activity - Day 5 (min/day), +ammdmva5,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva5, cycle6::AMMDMVA5, [ammdmva5]",cont,NA::a,N/A,not applicable,not applicable,minutes/day,9996,Valid skip ,Minutes of exercise per day (accelerometer Day 5),Total moderate-to-vigorous physical activity - Day 5 (min/day), +ammdmva5,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva5, cycle6::AMMDMVA5, [ammdmva5]",cont,NA::b,N/A,missing,missing,minutes/day,"[9997, 9999]",Don't know (9997); Refusal (9998); Not stated (9999),Minutes of exercise per day (accelerometer Day 5),Total moderate-to-vigorous physical activity - Day 5 (min/day), +ammdmva5,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva5, cycle6::AMMDMVA5, [ammdmva5]",cont,NA::b,N/A,missing,missing,minutes/day,else,else,Minutes of exercise per day (accelerometer Day 5),Total moderate-to-vigorous physical activity - Day 5 (min/day), +ammdmva6,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva6, cycle6::AMMDMVA6, [ammdmva6]",cont,copy,N/A,minutes/day,minutes/day,minutes/day,"[0, 404]",Minutes per day,Minutes of exercise per day (accelerometer Day 6),Total moderate-to-vigorous physical activity - Day 6 (min/day), +ammdmva6,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva6, cycle6::AMMDMVA6, [ammdmva6]",cont,NA::a,N/A,not applicable,not applicable,minutes/day,9996,Valid skip ,Minutes of exercise per day (accelerometer Day 6),Total moderate-to-vigorous physical activity - Day 6 (min/day), +ammdmva6,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva6, cycle6::AMMDMVA6, [ammdmva6]",cont,NA::b,N/A,missing,missing,minutes/day,"[9997, 9999]",Don't know (9997); Refusal (9998); Not stated (9999),Minutes of exercise per day (accelerometer Day 6),Total moderate-to-vigorous physical activity - Day 6 (min/day), +ammdmva6,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva6, cycle6::AMMDMVA6, [ammdmva6]",cont,NA::b,N/A,missing,missing,minutes/day,else,else,Minutes of exercise per day (accelerometer Day 6),Total moderate-to-vigorous physical activity - Day 6 (min/day), +ammdmva7,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva7, cycle6::AMMDMVA7, [ammdmva7]",cont,copy,N/A,minutes/day,minutes/day,minutes/day,"[0, 404]",Minutes per day,Minutes of exercise per day (accelerometer Day 7),Total moderate-to-vigorous physical activity - Day 7 (min/day), +ammdmva7,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva7, cycle6::AMMDMVA7, [ammdmva7]",cont,NA::a,N/A,not applicable,not applicable,minutes/day,9996,Valid skip ,Minutes of exercise per day (accelerometer Day 7),Total moderate-to-vigorous physical activity - Day 7 (min/day), +ammdmva7,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva7, cycle6::AMMDMVA7, [ammdmva7]",cont,NA::b,N/A,missing,missing,minutes/day,"[9997, 9999]",Don't know (9997); Refusal (9998); Not stated (9999),Minutes of exercise per day (accelerometer Day 7),Total moderate-to-vigorous physical activity - Day 7 (min/day), +ammdmva7,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva7, cycle6::AMMDMVA7, [ammdmva7]",cont,NA::b,N/A,missing,missing,minutes/day,else,else,Minutes of exercise per day (accelerometer Day 7),Total moderate-to-vigorous physical activity - Day 7 (min/day), +atc_101a,N/A,cat,"cycle1_meds, cycle2_meds","cycle1_meds::ATC_101A, [atc_101a]",cat,copy,N/A,ATC,ATC,N/A,else,ATC,First prescription medication - ATC,First prescription medication - ATC, +atc_101a,N/A,cat,"cycle1_meds, cycle2_meds","cycle1_meds::ATC_101A, [atc_101a]",cat,NA::a,N/A,not applicable,not applicable,N/A,9999996,Valid skip,First prescription medication - ATC,First prescription medication - ATC, +atc_101a,N/A,cat,"cycle1_meds, cycle2_meds","cycle1_meds::ATC_101A, [atc_101a]",cat,NA::b,N/A,missing,missing,N/A,"[9999997, 9999999]",Don't know (9999997); Refusal (9999998); Not stated (9999999),First prescription medication - ATC,First prescription medication - ATC, +atc_102a,N/A,cat,"cycle1_meds, cycle2_meds","cycle1_meds::ATC_102A, [atc_102a]",cat,copy,N/A,ATC,ATC,N/A,else,ATC,Second prescription medication - ATC,Second prescription medication - ATC, +atc_102a,N/A,cat,"cycle1_meds, cycle2_meds","cycle1_meds::ATC_102A, [atc_102a]",cat,NA::a,N/A,not applicable,not applicable,N/A,9999996,Valid skip,Second prescription medication - ATC,Second prescription medication - ATC, +atc_102a,N/A,cat,"cycle1_meds, cycle2_meds","cycle1_meds::ATC_102A, [atc_102a]",cat,NA::b,N/A,missing,missing,N/A,"[9999997, 9999999]",Don't know (9999997); Refusal (9999998); Not stated (9999999),Second prescription medication - ATC,Second prescription medication - ATC, +atc_103a,N/A,cat,"cycle1_meds, cycle2_meds","cycle1_meds::ATC_103A, [atc_103a]",cat,copy,N/A,ATC,ATC,N/A,else,ATC,Third prescription medication - ATC,Third prescription medication - ATC, +atc_103a,N/A,cat,"cycle1_meds, cycle2_meds","cycle1_meds::ATC_103A, [atc_103a]",cat,NA::a,N/A,not applicable,not applicable,N/A,9999996,Valid skip,Third prescription medication - ATC,Third prescription medication - ATC, +atc_103a,N/A,cat,"cycle1_meds, cycle2_meds","cycle1_meds::ATC_103A, [atc_103a]",cat,NA::b,N/A,missing,missing,N/A,"[9999997, 9999999]",Don't know (9999997); Refusal (9999998); Not stated (9999999),Third prescription medication - ATC,Third prescription medication - ATC, +bpmdpbpd,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::BPMDPBPD, [bpmdpbpd]",cont,copy,N/A,Diastolic blood pressure,Diastolic blood pressure,mmHg,"[42, 154]",Diastolic blood pressure,Diastolic blood pressure,Final average diastolic blood pressure (mmHg) - prevalence - (D), +bpmdpbpd,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::BPMDPBPD, [bpmdpbpd]",cont,NA::a,N/A,not applicable,not applicable,mmHg,996,Valid skip,Diastolic blood pressure,Final average diastolic blood pressure (mmHg) - prevalence - (D), +bpmdpbpd,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::BPMDPBPD, [bpmdpbpd]",cont,NA::b,N/A,missing,missing,mmHg,"[997, 999]",Don't know (997); Refusal (998); Not stated (999),Diastolic blood pressure,Final average diastolic blood pressure (mmHg) - prevalence - (D), +bpmdpbpd,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::BPMDPBPD, [bpmdpbpd]",cont,NA::b,N/A,missing,missing,mmHg,else,else,Diastolic blood pressure,Final average diastolic blood pressure (mmHg) - prevalence - (D), +bpmdpbps,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::BPMDPBPS, [bpmdpbps]",cont,copy,N/A,Systolic blood pressure,Systolic blood pressure,mmHg,"[73, 216]",Systolic blood pressure,Systolic blood pressure,Final average systolic blood pressure (mmHg) - prevalence - (D), +bpmdpbps,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::BPMDPBPS, [bpmdpbps]",cont,NA::a,N/A,not applicable,not applicable,mmHg,996,Valid skip,Systolic blood pressure,Final average systolic blood pressure (mmHg) - prevalence - (D), +bpmdpbps,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::BPMDPBPS, [bpmdpbps]",cont,NA::b,N/A,missing,missing,mmHg,"[997, 999]",Don't know (997); Refusal (998); Not stated (999),Systolic blood pressure,Final average systolic blood pressure (mmHg) - prevalence - (D), +bpmdpbps,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::BPMDPBPS, [bpmdpbps]",cont,NA::b,N/A,missing,missing,mmHg,else,else,Systolic blood pressure,Final average systolic blood pressure (mmHg) - prevalence - (D), +clc_age,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::CLC_AGE, [clc_age]",cont,copy,N/A,Years,Years,years,"[3, 80]",Years,Age,Age at clinic visit, +clc_age,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::CLC_AGE, [clc_age]",cont,NA::a,N/A,not applicable,not applicable,years,996,Valid skip,Age,Age at clinic visit, +clc_age,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::CLC_AGE, [clc_age]",cont,NA::b,N/A,missing,missing,years,"[997, 999]",Don't know (997); Refusal (998); Not stated (999),Age,Age at clinic visit, +clc_age,N/A,cont,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::CLC_AGE, [clc_age]",cont,NA::b,N/A,missing,missing,years,else,else,Age,Age at clinic visit, +clc_sex,clc_sex_cat2_1,cat,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::CLC_SEX, [clc_sex]",cat,1,2,Male,Male,N/A,1,Male,Sex,Sex, +clc_sex,clc_sex_cat2_2,cat,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::CLC_SEX, [clc_sex]",cat,2,2,Female,Female,N/A,2,Female,Sex,Sex, +clc_sex,clc_sex_cat2_NA::a,cat,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::CLC_SEX, [clc_sex]",cat,NA::a,2,not applicable,not applicable,N/A,6,Valid skip,Sex,Sex, +clc_sex,clc_sex_cat2_NA::b,cat,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::CLC_SEX, [clc_sex]",cat,NA::b,2,missing,missing,N/A,"[7, 9]",Don't know (7); Refusal (8); Not stated (9),Sex,Sex, +clc_sex,clc_sex_cat2_NA::b,cat,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::CLC_SEX, [clc_sex]",cat,NA::b,2,missing,missing,N/A,else,else,Sex,Sex, diff --git a/inst/extdata/chms/variables_chmsflow_sample.csv b/inst/extdata/chms/variables_chmsflow_sample.csv new file mode 100644 index 0000000..39190dd --- /dev/null +++ b/inst/extdata/chms/variables_chmsflow_sample.csv @@ -0,0 +1,19 @@ +variable,label,labelLong,section,subject,variableType,units,databaseStart,variableStart,description +alc_11,Drank in past year,Drank alcohol - past 12 months,Health behaviour,Alcohol,Categorical,N/A,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6:: ALC_11, [alc_11]", +alc_17,Ever drank alcohol,Ever had a drink,Health behaviour,Alcohol,Categorical,N/A,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::ALC_17, [alc_17]", +alc_18,Drank alcohol regularly,Regularly drank more than 12 drinks a week,Health behaviour,Alcohol,Categorical,N/A,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::ALC_18, [alc_18]", +alcdwky,Drinks in week," Weekly consumption - (D)",Health behaviour,Alcohol,Continuous,drinks/week,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::ALCDWKY, [alcdwky]", +ammdmva1,Minutes of exercise per day (accelerometer Day 1),Total moderate-to-vigorous physical activity - Day 1 (min/day),Health behaviour,Exercise,Continuous,minutes/day,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva1, cycle6::AMMDMVA1, [ammdmva1]", +ammdmva2,Minutes of exercise per day (accelerometer Day 2),Total moderate-to-vigorous physical activity - Day 2 (min/day),Health behaviour,Exercise,Continuous,minutes/day,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva2, cycle6::AMMDMVA2, [ammdmva2]", +ammdmva3,Minutes of exercise per day (accelerometer Day 3),Total moderate-to-vigorous physical activity - Day 3 (min/day),Health behaviour,Exercise,Continuous,minutes/day,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva3, cycle6::AMMDMVA3, [ammdmva3]", +ammdmva4,Minutes of exercise per day (accelerometer Day 4),Total moderate-to-vigorous physical activity - Day 4 (min/day),Health behaviour,Exercise,Continuous,minutes/day,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva4, cycle6::AMMDMVA4, [ammdmva4]", +ammdmva5,Minutes of exercise per day (accelerometer Day 5),Total moderate-to-vigorous physical activity - Day 5 (min/day),Health behaviour,Exercise,Continuous,minutes/day,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva5, cycle6::AMMDMVA5, [ammdmva5]", +ammdmva6,Minutes of exercise per day (accelerometer Day 6),Total moderate-to-vigorous physical activity - Day 6 (min/day),Health behaviour,Exercise,Continuous,minutes/day,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva6, cycle6::AMMDMVA6, [ammdmva6]", +ammdmva7,Minutes of exercise per day (accelerometer Day 7),Total moderate-to-vigorous physical activity - Day 7 (min/day),Health behaviour,Exercise,Continuous,minutes/day,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle1::amsdmva7, cycle6::AMMDMVA7, [ammdmva7]", +atc_101a,First prescription medication - ATC,First prescription medication - ATC,Health status,Medication,Categorical,N/A,"cycle1_meds, cycle2_meds","cycle1_meds::ATC_101A, [atc_101a]", +atc_102a,Second prescription medication - ATC,Second prescription medication - ATC,Health status,Medication,Categorical,N/A,"cycle1_meds, cycle2_meds","cycle1_meds::ATC_102A, [atc_102a]", +atc_103a,Third prescription medication - ATC,Third prescription medication - ATC,Health status,Medication,Categorical,N/A,"cycle1_meds, cycle2_meds","cycle1_meds::ATC_103A, [atc_103a]", +bpmdpbpd,Diastolic blood pressure,Final average diastolic blood pressure (mmHg) - prevalence - (D),Health status,Blood pressure,Continuous,mmHg,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::BPMDPBPD, [bpmdpbpd]", +bpmdpbps,Systolic blood pressure,Final average systolic blood pressure (mmHg) - prevalence - (D),Health status,Blood pressure,Continuous,mmHg,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::BPMDPBPS, [bpmdpbps]", +clc_age,Age,Age at clinic visit,Sociodemographics,Age,Continuous,years,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::CLC_AGE, [clc_age]", +clc_sex,Sex,Sex,Sociodemographics,Sex,Categorical,N/A,"cycle1, cycle2, cycle3, cycle4, cycle5, cycle6","cycle6::CLC_SEX, [clc_sex]", diff --git a/inst/extdata/demport/variable_details_DemPoRT.csv.bak b/inst/extdata/demport/variable_details_DemPoRT.csv.bak new file mode 100644 index 0000000..bbfa198 --- /dev/null +++ b/inst/extdata/demport/variable_details_DemPoRT.csv.bak @@ -0,0 +1,660 @@ +variable,dummyVariable,typeEnd,databaseStart,variableStart,ICES confirmation,typeStart,recEnd,numValidCat,catLabel,catLabelLong,units,recStart,catStartLabel,variableStartShortLabel,variableStartLabel,notes,, +ADL_01,ADL_01_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6A, cchs2003_p::RACC_6A, cchs2005_p::RACE_6A, cchs2007_2008_p::RAC_6A, cchs2015_2016_p::ADL_005, cchs2017_2018_p::ADL_005, cchs2001_i::RACA_6A, cchs2003_i::RACC_6A, cchs2005_i::RACE_6A, [ADL_01]",ICES confirmed,cat,1,2,Yes,Yes,N/A,1,Yes,Help preparing meals,Needs help - preparing meals,,, +ADL_01,ADL_01_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::RACA_6A, cchs2003_p::RACC_6A, cchs2005_p::RACE_6A, cchs2007_2008_p::RAC_6A, cchs2015_2016_p::ADL_005, cchs2017_2018_p::ADL_005, cchs2001_i::RACA_6A, cchs2003_i::RACC_6A, cchs2005_i::RACE_6A, [ADL_01]",ICES confirmed,cat,2,2,No,No,N/A,2,No,Help preparing meals,Needs help - preparing meals,,, +ADL_01,ADL_01_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::RACA_6A, cchs2003_p::RACC_6A, cchs2005_p::RACE_6A, cchs2007_2008_p::RAC_6A, cchs2015_2016_p::ADL_005, cchs2017_2018_p::ADL_005, cchs2001_i::RACA_6A, cchs2003_i::RACC_6A, cchs2005_i::RACE_6A, [ADL_01]",ICES confirmed,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Help preparing meals,Needs help - preparing meals,,, +ADL_01,ADL_01_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::RACA_6A, cchs2003_p::RACC_6A, cchs2005_p::RACE_6A, cchs2007_2008_p::RAC_6A, cchs2015_2016_p::ADL_005, cchs2017_2018_p::ADL_005, cchs2001_i::RACA_6A, cchs2003_i::RACC_6A, cchs2005_i::RACE_6A, [ADL_01]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Help preparing meals,Needs help - preparing meals,,, +ADL_01,ADL_01_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::RACA_6A, cchs2003_p::RACC_6A, cchs2005_p::RACE_6A, cchs2007_2008_p::RAC_6A, cchs2015_2016_p::ADL_005, cchs2017_2018_p::ADL_005, cchs2001_i::RACA_6A, cchs2003_i::RACC_6A, cchs2005_i::RACE_6A, [ADL_01]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,else,else,Help preparing meals,Needs help - preparing meals,,, +ADL_02,ADL_02_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6B, cchs2003_p::RACC_6B1, cchs2005_p::RACE_6B1, cchs2007_2008_p::RAC_6B1, cchs2001_i::RACA_6B, cchs2003_i::RACC_6B1, cchs2005_i::RACE_6B1, cchs2007_2008_i::RAC_6B1, [ADL_02]",ICES confirmed,cat,1,2,Yes,Yes,N/A,1,Yes,Help appointments/errands,Needs help - getting to appointments/errands,"In the 2001 CCHS, respondents were asked, ""Because of any condition or health problem, do you need the help of another person in shopping for groceries or other necessities?""",, +ADL_02,ADL_02_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6B, cchs2003_p::RACC_6B1, cchs2005_p::RACE_6B1, cchs2007_2008_p::RAC_6B1, cchs2001_i::RACA_6B, cchs2003_i::RACC_6B1, cchs2005_i::RACE_6B1, cchs2007_2008_i::RAC_6B1, [ADL_02]",ICES confirmed,cat,2,2,No,No,N/A,2,No,Help appointments/errands,Needs help - getting to appointments/errands,,, +ADL_02,ADL_02_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6B, cchs2003_p::RACC_6B1, cchs2005_p::RACE_6B1, cchs2007_2008_p::RAC_6B1, cchs2001_i::RACA_6B, cchs2003_i::RACC_6B1, cchs2005_i::RACE_6B1, cchs2007_2008_i::RAC_6B1, [ADL_02]",ICES confirmed,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Help appointments/errands,Needs help - getting to appointments/errands,,, +ADL_02,ADL_02_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6B, cchs2003_p::RACC_6B1, cchs2005_p::RACE_6B1, cchs2007_2008_p::RAC_6B1, cchs2001_i::RACA_6B, cchs2003_i::RACC_6B1, cchs2005_i::RACE_6B1, cchs2007_2008_i::RAC_6B1, [ADL_02]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Help appointments/errands,Needs help - getting to appointments/errands,,, +ADL_02,ADL_02_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6B, cchs2003_p::RACC_6B1, cchs2005_p::RACE_6B1, cchs2007_2008_p::RAC_6B1, cchs2001_i::RACA_6B, cchs2003_i::RACC_6B1, cchs2005_i::RACE_6B1, cchs2007_2008_i::RAC_6B1, [ADL_02]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,else,else,Help appointments/errands,Needs help - getting to appointments/errands,,, +ADL_03,ADL_03_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6C, cchs2003_p::RACC_6C, cchs2005_p::RACE_6C, cchs2007_2008_p::RAC_6C, cchs2001_i::RACA_6C, cchs2003_i::RACC_6C, cchs2005_i::RACE_6C, cchs2007_2008_i::RAC_6C,[ADL_03]",ICES confirmed,cat,1,2,Yes,Yes,N/A,1,Yes,Help housework,Needs help - doing housework,,, +ADL_03,ADL_03_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6C, cchs2003_p::RACC_6C, cchs2005_p::RACE_6C, cchs2007_2008_p::RAC_6C, cchs2001_i::RACA_6C, cchs2003_i::RACC_6C, cchs2005_i::RACE_6C, cchs2007_2008_i::RAC_6C,[ADL_03]",ICES confirmed,cat,2,2,No,No,N/A,2,No,Help housework,Needs help - doing housework,,, +ADL_03,ADL_03_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6C, cchs2003_p::RACC_6C, cchs2005_p::RACE_6C, cchs2007_2008_p::RAC_6C, cchs2001_i::RACA_6C, cchs2003_i::RACC_6C, cchs2005_i::RACE_6C, cchs2007_2008_i::RAC_6C,[ADL_03]",ICES confirmed,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Help housework,Needs help - doing housework,,, +ADL_03,ADL_03_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6C, cchs2003_p::RACC_6C, cchs2005_p::RACE_6C, cchs2007_2008_p::RAC_6C, cchs2001_i::RACA_6C, cchs2003_i::RACC_6C, cchs2005_i::RACE_6C, cchs2007_2008_i::RAC_6C,[ADL_03]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Help housework,Needs help - doing housework,,, +ADL_03,ADL_03_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6C, cchs2003_p::RACC_6C, cchs2005_p::RACE_6C, cchs2007_2008_p::RAC_6C, cchs2001_i::RACA_6C, cchs2003_i::RACC_6C, cchs2005_i::RACE_6C, cchs2007_2008_i::RAC_6C,[ADL_03]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,else,else,Help housework,Needs help - doing housework,,, +ADL_04,ADL_04_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6E, cchs2003_p::RACC_6E, cchs2005_p::RACE_6E, cchs2007_2008_p::RAC_6E, cchs2001_i::RACA_6E, cchs2003_i::RACC_6E, cchs2005_i::RACE_6E, cchs2007_2008_i::RAC_6E,[ADL_04]",ICES confirmed,cat,1,2,Yes,Yes,N/A,1,Yes,Help personal care,Needs help - personal care,,, +ADL_04,ADL_04_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6E, cchs2003_p::RACC_6E, cchs2005_p::RACE_6E, cchs2007_2008_p::RAC_6E, cchs2001_i::RACA_6E, cchs2003_i::RACC_6E, cchs2005_i::RACE_6E, cchs2007_2008_i::RAC_6E,[ADL_04]",ICES confirmed,cat,2,2,No,No,N/A,2,No,Help personal care,Needs help - personal care,,, +ADL_04,ADL_04_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6E, cchs2003_p::RACC_6E, cchs2005_p::RACE_6E, cchs2007_2008_p::RAC_6E, cchs2001_i::RACA_6E, cchs2003_i::RACC_6E, cchs2005_i::RACE_6E, cchs2007_2008_i::RAC_6E,[ADL_04]",ICES confirmed,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Help personal care,Needs help - personal care,,, +ADL_04,ADL_04_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6E, cchs2003_p::RACC_6E, cchs2005_p::RACE_6E, cchs2007_2008_p::RAC_6E, cchs2001_i::RACA_6E, cchs2003_i::RACC_6E, cchs2005_i::RACE_6E, cchs2007_2008_i::RAC_6E,[ADL_04]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Help personal care,Needs help - personal care,,, +ADL_04,ADL_04_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6E, cchs2003_p::RACC_6E, cchs2005_p::RACE_6E, cchs2007_2008_p::RAC_6E, cchs2001_i::RACA_6E, cchs2003_i::RACC_6E, cchs2005_i::RACE_6E, cchs2007_2008_i::RAC_6E,[ADL_04]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,else,else,Help personal care,Needs help - personal care,,, +ADL_05,ADL_05_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6F, cchs2003_p::RACC_6F, cchs2005_p::RACE_6F, cchs2007_2008_p::RAC_6F, cchs2001_i::RACA_6F, cchs2003_i::RACC_6F, cchs2005_i::RACE_6F, cchs2007_2008_i::RAC_6F,[ADL_05]",ICES confirmed,cat,1,2,Yes,Yes,N/A,1,Yes,Help move inside house,Needs help - moving about inside house,,, +ADL_05,ADL_05_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6F, cchs2003_p::RACC_6F, cchs2005_p::RACE_6F, cchs2007_2008_p::RAC_6F, cchs2001_i::RACA_6F, cchs2003_i::RACC_6F, cchs2005_i::RACE_6F, cchs2007_2008_i::RAC_6F,[ADL_05]",ICES confirmed,cat,2,2,No,No,N/A,2,No,Help move inside house,Needs help - moving about inside house,,, +ADL_05,ADL_05_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6F, cchs2003_p::RACC_6F, cchs2005_p::RACE_6F, cchs2007_2008_p::RAC_6F, cchs2001_i::RACA_6F, cchs2003_i::RACC_6F, cchs2005_i::RACE_6F, cchs2007_2008_i::RAC_6F,[ADL_05]",ICES confirmed,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Help move inside house,Needs help - moving about inside house,,, +ADL_05,ADL_05_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6F, cchs2003_p::RACC_6F, cchs2005_p::RACE_6F, cchs2007_2008_p::RAC_6F, cchs2001_i::RACA_6F, cchs2003_i::RACC_6F, cchs2005_i::RACE_6F, cchs2007_2008_i::RAC_6F,[ADL_05]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Help move inside house,Needs help - moving about inside house,,, +ADL_05,ADL_05_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6F, cchs2003_p::RACC_6F, cchs2005_p::RACE_6F, cchs2007_2008_p::RAC_6F, cchs2001_i::RACA_6F, cchs2003_i::RACC_6F, cchs2005_i::RACE_6F, cchs2007_2008_i::RAC_6F,[ADL_05]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,else,else,Help move inside house,Needs help - moving about inside house,,, +ADL_06,ADL_06_cat2_1,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_p::RACC_6G, cchs2005_p::RACE_6G, cchs2007_2008_p::RAC_6G, cchs2003_i::RACC_6G, cchs2005_i::RACE_6G, cchs2007_2008_i::RAC_6G, [ADL_06]",ICES confirmed,cat,1,2,Yes,Yes,N/A,1,Yes,Help personal finances,Needs help - looking after finances,Only available for 2003 onwards,, +ADL_06,ADL_06_cat2_2,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_p::RACC_6G, cchs2005_p::RACE_6G, cchs2007_2008_p::RAC_6G, cchs2003_i::RACC_6G, cchs2005_i::RACE_6G, cchs2007_2008_i::RAC_6G, [ADL_06]",ICES confirmed,cat,2,2,No,No,N/A,2,No,Help personal finances,Needs help - looking after finances,Only available for 2003 onwards,, +ADL_06,ADL_06_cat2_NA::a,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_p::RACC_6G, cchs2005_p::RACE_6G, cchs2007_2008_p::RAC_6G, cchs2003_i::RACC_6G, cchs2005_i::RACE_6G, cchs2007_2008_i::RAC_6G, [ADL_06]",ICES confirmed,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Help personal finances,Needs help - looking after finances,Only available for 2003 onwards,, +ADL_06,ADL_06_cat2_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_p::RACC_6G, cchs2005_p::RACE_6G, cchs2007_2008_p::RAC_6G, cchs2003_i::RACC_6G, cchs2005_i::RACE_6G, cchs2007_2008_i::RAC_6G, [ADL_06]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Help personal finances,Needs help - looking after finances,Only available for 2003 onwards,, +ADL_06,ADL_06_cat2_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_p::RACC_6G, cchs2005_p::RACE_6G, cchs2007_2008_p::RAC_6G, cchs2003_i::RACC_6G, cchs2005_i::RACE_6G, cchs2007_2008_i::RAC_6G, [ADL_06]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,else,else,Help personal finances,Needs help - looking after finances,Only available for 2003 onwards,, +ADL_07,ADL_07_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_p::RACA_6D, cchs2003_p::RACC_6D, cchs2005_p::RACE_6D, cchs2001_i::RACA_6D, cchs2003_i::RACC_6D, cchs2005_i::RACE_6D",ICES confirmed,cat,1,2,Yes,Yes,N/A,1,Yes,Help heavy household chores,Needs help - heavy household chores,,, +ADL_07,ADL_07_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_p::RACA_6D, cchs2003_p::RACC_6D, cchs2005_p::RACE_6D, cchs2001_i::RACA_6D, cchs2003_i::RACC_6D, cchs2005_i::RACE_6D",ICES confirmed,cat,2,2,No,No,N/A,2,No,Help heavy household chores,Needs help - heavy household chores,,, +ADL_07,ADL_07_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_p::RACA_6D, cchs2003_p::RACC_6D, cchs2005_p::RACE_6D, cchs2001_i::RACA_6D, cchs2003_i::RACC_6D, cchs2005_i::RACE_6D",ICES confirmed,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Help heavy household chores,Needs help - heavy household chores,,, +ADL_07,ADL_07_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_p::RACA_6D, cchs2003_p::RACC_6D, cchs2005_p::RACE_6D, cchs2001_i::RACA_6D, cchs2003_i::RACC_6D, cchs2005_i::RACE_6D",ICES confirmed,cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Help heavy household chores,Needs help - heavy household chores,,, +ADL_07,ADL_07_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_p::RACA_6D, cchs2003_p::RACC_6D, cchs2005_p::RACE_6D, cchs2001_i::RACA_6D, cchs2003_i::RACC_6D, cchs2005_i::RACE_6D",ICES confirmed,cat,NA::b,2,missing,missing,N/A,else,else,Help heavy household chores,Needs help - heavy household chores,,, +ADL_score_6,ADL_score_6_catN/A_Func::adl_score_6_fun,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05, ADL_06]",ICES specifc,N/A,Func::adl_score_6_fun,N/A,N/A,N/A,N/A,N/A,N/A,ADL score ,"Derived using the ADL variables used in DemPoRT from 2001 to 2014 (ADL_01, ADL_02, ADL_03, ADL_04, ADL_05, ADL_06) to represent the number of tasks that an individual needs help with.",,, +ADL_score_6,ADL_score_6_cat7_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05, ADL_06]",ICES specifc,N/A,0,7,Needs help with 0 tasks,Needs help with 0 tasks,N/A,N/A,Needs help with 0 tasks,ADL score ,"Derived using the ADL variables used in DemPoRT from 2001 to 2014 (ADL_01, ADL_02, ADL_03, ADL_04, ADL_05, ADL_06) to represent the number of tasks that an individual needs help with.",,, +ADL_score_6,ADL_score_6_cat7_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05, ADL_06]",ICES specifc,N/A,1,7,Needs help with at least 1 task,Needs help with at least 1 task,N/A,N/A,Needs help with at least 1 task,ADL score ,"Derived using the ADL variables used in DemPoRT from 2001 to 2014 (ADL_01, ADL_02, ADL_03, ADL_04, ADL_05, ADL_06) to represent the number of tasks that an individual needs help with.",,, +ADL_score_6,ADL_score_6_cat7_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05, ADL_06]",ICES specifc,N/A,2,7,Needs help with at least 2 tasks,Needs help with at least 2 tasks,N/A,N/A,Needs help with at least 2 tasks,ADL score ,"Derived using the ADL variables used in DemPoRT from 2001 to 2014 (ADL_01, ADL_02, ADL_03, ADL_04, ADL_05, ADL_06) to represent the number of tasks that an individual needs help with.",,, +ADL_score_6,ADL_score_6_cat7_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05, ADL_06]",ICES specifc,N/A,3,7,Needs help with at least 3 tasks,Needs help with at least 3 tasks,N/A,N/A,Needs help with at least 3 tasks,ADL score ,"Derived using the ADL variables used in DemPoRT from 2001 to 2014 (ADL_01, ADL_02, ADL_03, ADL_04, ADL_05, ADL_06) to represent the number of tasks that an individual needs help with.",,, +ADL_score_6,ADL_score_6_cat7_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05, ADL_06]",ICES specifc,N/A,4,7,Needs help with at least 4 tasks,Needs help with at least 4 tasks,N/A,N/A,Needs help with at least 4 tasks,ADL score ,"Derived using the ADL variables used in DemPoRT from 2001 to 2014 (ADL_01, ADL_02, ADL_03, ADL_04, ADL_05, ADL_06) to represent the number of tasks that an individual needs help with.",,, +ADL_score_6,ADL_score_6_cat7_6,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05, ADL_06]",ICES specifc,N/A,5,7,Needs help with at least 5 tasks,Needs help with at least 5 tasks,N/A,N/A,Needs help with at least 5 tasks,ADL score ,"Derived using the ADL variables used in DemPoRT from 2001 to 2014 (ADL_01, ADL_02, ADL_03, ADL_04, ADL_05, ADL_06) to represent the number of tasks that an individual needs help with.",,, +ADL_score_6,ADL_score_6_cat7_7,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05, ADL_06]",ICES specifc,N/A,6,7,Needs help with at least 6 tasks,Needs help with at least 6 tasks,N/A,N/A,Needs help with at least 6 tasks,ADL score ,"Derived using the ADL variables used in DemPoRT from 2001 to 2014 (ADL_01, ADL_02, ADL_03, ADL_04, ADL_05, ADL_06) to represent the number of tasks that an individual needs help with.",,, +ADL_score_6,ADL_score_6_cat7_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05, ADL_06]",ICES specifc,N/A,NA::a,7,not applicable,not applicable,N/A,N/A,not applicable,ADL score ,"Derived using the ADL variables used in DemPoRT from 2001 to 2014 (ADL_01, ADL_02, ADL_03, ADL_04, ADL_05, ADL_06) to represent the number of tasks that an individual needs help with.",,, +ADL_score_6,ADL_score_6_cat7_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05, ADL_06]",ICES specifc,N/A,NA::b,7,missing,missing,N/A,N/A,missing,ADL score ,"Derived using the ADL variables used in DemPoRT from 2001 to 2014 (ADL_01, ADL_02, ADL_03, ADL_04, ADL_05, ADL_06) to represent the number of tasks that an individual needs help with.",,, +ALCDTTM,ALCDTTM_cat3_1,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2015_2016_p::ALCDVTTM, cchs2017_2018_p::ALCDVTTM, cchs2015_2016_i::ALCDVTTM, cchs2017_2018_i::ALCDVTTM, [ALCDTTM]",ICES altered,cat,1,3,Regular,Regular Drinker,N/A,1,Regular Drinker,Drinker type (last 12 months),Type of drinker (12 months),,, +ALCDTTM,ALCDTTM_cat3_2,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2015_2016_p::ALCDVTTM, cchs2017_2018_p::ALCDVTTM, cchs2015_2016_i::ALCDVTTM, cchs2017_2018_i::ALCDVTTM, [ALCDTTM]",ICES altered,cat,2,3,Occasional,Occasional Drinker,N/A,2,Occasional drinker,Drinker type (last 12 months),Type of drinker (12 months),,, +ALCDTTM,ALCDTTM_cat3_3,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2015_2016_p::ALCDVTTM, cchs2017_2018_p::ALCDVTTM, cchs2015_2016_i::ALCDVTTM, cchs2017_2018_i::ALCDVTTM, [ALCDTTM]",ICES altered,cat,3,3,No drink in last 12 months,No drink in last 12 months,N/A,3,No drink in the last 12 months,Drinker type (last 12 months),Type of drinker (12 months),,, +ALCDTTM,ALCDTTM_cat3_NA::a,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2015_2016_p::ALCDVTTM, cchs2017_2018_p::ALCDVTTM, cchs2015_2016_i::ALCDVTTM, cchs2017_2018_i::ALCDVTTM, [ALCDTTM]",ICES altered,cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Drinker type (last 12 months),Type of drinker (12 months),,, +ALCDTTM,ALCDTTM_cat3_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2015_2016_p::ALCDVTTM, cchs2017_2018_p::ALCDVTTM, cchs2015_2016_i::ALCDVTTM, cchs2017_2018_i::ALCDVTTM, [ALCDTTM]",ICES altered,cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Drinker type (last 12 months),Type of drinker (12 months),,, +ALCDTTM,ALCDTTM_cat3_NA::b,cat,"cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2015_2016_p::ALCDVTTM, cchs2017_2018_p::ALCDVTTM, cchs2015_2016_i::ALCDVTTM, cchs2017_2018_i::ALCDVTTM, [ALCDTTM]",ICES altered,cat,NA::b,3,missing,missing,N/A,else,else,Drinker type (last 12 months),Type of drinker (12 months),,, +ALCDTTM,ALCDTTM_cat3_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP, cchs2001_i::ALCADTYP, cchs2003_i::ALCCDTYP, cchs2005_i::ALCEDTYP",ICES altered,cat,1,3,Regular,Regular Drinker,N/A,1,Regular drinker,Drinker type (last 12 months),Type of drinker (12 months),"In CCHS cycles 2001, 2003, and 2005, ALCDTTM was derived from ALCDTYP in which former and never drinkers were combined into ""No drink in the last 12 months""",, +ALCDTTM,ALCDTTM_cat3_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP, cchs2001_i::ALCADTYP, cchs2003_i::ALCCDTYP, cchs2005_i::ALCEDTYP",ICES altered,cat,2,3,Occasional,Occasional Drinker,N/A,2,Occasional drinker,Drinker type (last 12 months),Type of drinker (12 months),,, +ALCDTTM,ALCDTTM_cat3_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP, cchs2001_i::ALCADTYP, cchs2003_i::ALCCDTYP, cchs2005_i::ALCEDTYP",ICES altered,cat,3,3,No drink in last 12 months,No drink in last 12 months,N/A,3,Former drinker,Drinker type (last 12 months),Type of drinker (12 months),,, +ALCDTTM,ALCDTTM_cat3_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP, cchs2001_i::ALCADTYP, cchs2003_i::ALCCDTYP, cchs2005_i::ALCEDTYP",ICES altered,cat,3,3,No drink in last 12 months,No drink in last 12 months,N/A,4,Never drank,Drinker type (last 12 months),Type of drinker (12 months),,, +ALCDTTM,ALCDTTM_cat3_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP, cchs2001_i::ALCADTYP, cchs2003_i::ALCCDTYP, cchs2005_i::ALCEDTYP",ICES altered,cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Drinker type (last 12 months),Type of drinker (12 months),,, +ALCDTTM,ALCDTTM_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP, cchs2001_i::ALCADTYP, cchs2003_i::ALCCDTYP, cchs2005_i::ALCEDTYP",ICES altered,cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Drinker type (last 12 months),Type of drinker (12 months),,, +ALCDTTM,ALCDTTM_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP, cchs2001_i::ALCADTYP, cchs2003_i::ALCCDTYP, cchs2005_i::ALCEDTYP",ICES altered,cat,NA::b,3,missing,missing,N/A,else,else,Drinker type (last 12 months),Type of drinker (12 months),,, +ALCDTYP_A,ALCDTYP_cat5_1,cat,"cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_i::ALCADTYP, cchs2003_i::ALCCDTYP, cchs2005_i::ALCEDTYP",ICES specifc,cat,1,2,Former ,Former drinker,N/A,3,Former drinker,Drinker type,Type of drinker - (D),,, +ALCDTYP_A,ALCDTYP_cat5_2,cat,"cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_i::ALCADTYP, cchs2003_i::ALCCDTYP, cchs2005_i::ALCEDTYP",ICES specifc,cat,2,2,Other,Other drinker,N/A,"[1,2]",Other drinker,Drinker type,Type of drinker - (D),"""Other"" drinker type derived from combining ""Regular"", ""Occasional"" and ""Never"" drink categories ",, +ALCDTYP_A,ALCDTYP_cat5_2,cat,"cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_i::ALCADTYP, cchs2003_i::ALCCDTYP, cchs2005_i::ALCEDTYP",ICES specifc,cat,2,2,Other,Other drinker,N/A,[4],Other drinker,Drinker type,Type of drinker - (D),"""Other"" drinker type derived from combining ""Regular"", ""Occasional"" and ""Never"" drink categories ",, +ALCDTYP_A,ALCDTYP_cat5_NA::a,cat,"cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_i::ALCADTYP, cchs2003_i::ALCCDTYP, cchs2005_i::ALCEDTYP",ICES specifc,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Drinker type,Type of drinker - (D),,, +ALCDTYP_A,ALCDTYP_cat5_NA::b,cat,"cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_i::ALCADTYP, cchs2003_i::ALCCDTYP, cchs2005_i::ALCEDTYP",ICES specifc,cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Drinker type,Type of drinker - (D),,, +ALCDTYP_A,ALCDTYP_cat5_NA::b,cat,"cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_i::ALCADTYP, cchs2003_i::ALCCDTYP, cchs2005_i::ALCEDTYP",ICES specifc,cat,NA::b,2,missing,missing,N/A,else,else,Drinker type,Type of drinker - (D),,, +ALCDTYP_A,ALCDTYP_cat5_NA::b,cat,"cchs2007_2008_i, cchs2009_2010_i, 2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2015_2016_i::ALCDVTTM, cchs2017_2018_i::ALCDVTTM, [ALCDTTM]",ICES specifc,cat,1,2,Former,Former drinker,N/A,3,Former drinker,Drinker type,Type of drinker - (D),,, +ALCDTYP_A,ALCDTYP_cat5_NA::b,cat,"cchs2007_2008_i, cchs2009_2010_i, 2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2015_2016_i::ALCDVTTM, cchs2017_2018_i::ALCDVTTM, [ALCDTTM]",ICES specifc,cat,2,2,Other,Other drinker,N/A,"[1,2]",Other drinker,Drinker type,Type of drinker - (D),"""Other"" drinker type derived from combining ""Regular"" and ""Occasional"" drinker categories ",, +ALCDTYP_A,ALCDTYP_cat5_NA::b,cat,"cchs2007_2008_i, cchs2009_2010_i, 2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2015_2016_i::ALCDVTTM, cchs2017_2018_i::ALCDVTTM, [ALCDTTM]",ICES specifc,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Drinker type,Type of drinker - (D),,, +ALCDTYP_A,ALCDTYP_cat5_NA::b,cat,"cchs2007_2008_i, cchs2009_2010_i, 2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2015_2016_i::ALCDVTTM, cchs2017_2018_i::ALCDVTTM, [ALCDTTM]",ICES specifc,cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Drinker type,Type of drinker - (D),,, +ALCDTYP_A,ALCDTYP_cat5_NA::b,cat,"cchs2007_2008_i, cchs2009_2010_i, 2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2015_2016_i::ALCDVTTM, cchs2017_2018_i::ALCDVTTM, [ALCDTTM]",ICES specifc,cat,NA::b,2,missing,missing,N/A,else,else,Drinker type,Type of drinker - (D),,, +ALWDWKY,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::ALCADWKY, cchs2003_p::ALCCDWKY, cchs2005_p::ALCEDWKY, cchs2015_2016_p::ALWDVWKY, cchs2017_2018_p::ALWDVWKY, cchs2001_i::ALCADWKY, cchs2003_i::ALCCDWKY, cchs2005_i:: ALCEDWKY, cchs2015_2016_i::ALWDVWKY, cchs2017_2018_i::ALWDVWKY, [ALWDWKY]",ICES confirmed,cont,copy,N/A,drinks/week,drinks/week,drinks/week,"[0,449]",drinks per week,Drinks last week,Weekly consumption of alcohol,shown as categorical variable in CCHS 2014 cycle,, +ALWDWKY,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::ALCADWKY, cchs2003_p::ALCCDWKY, cchs2005_p::ALCEDWKY, cchs2015_2016_p::ALWDVWKY, cchs2017_2018_p::ALWDVWKY, cchs2001_i::ALCADWKY, cchs2003_i::ALCCDWKY, cchs2005_i:: ALCEDWKY, cchs2015_2016_i::ALWDVWKY, cchs2017_2018_i::ALWDVWKY, [ALWDWKY]",ICES confirmed,cont,NA::a,N/A,not applicable,not applicable,drinks/week,996,not applicable (996),Drinks last week,Weekly consumption of alcohol,,, +ALWDWKY,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::ALCADWKY, cchs2003_p::ALCCDWKY, cchs2005_p::ALCEDWKY, cchs2015_2016_p::ALWDVWKY, cchs2017_2018_p::ALWDVWKY, cchs2001_i::ALCADWKY, cchs2003_i::ALCCDWKY, cchs2005_i:: ALCEDWKY, cchs2015_2016_i::ALWDVWKY, cchs2017_2018_i::ALWDVWKY, [ALWDWKY]",ICES confirmed,cont,NA::b,N/A,missing,missing,drinks/week,"[997,999]",don't know (997); refusal (998); not stated (999),Drinks last week,Weekly consumption of alcohol,,, +ALWDWKY,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::ALCADWKY, cchs2003_p::ALCCDWKY, cchs2005_p::ALCEDWKY, cchs2015_2016_p::ALWDVWKY, cchs2017_2018_p::ALWDVWKY, cchs2001_i::ALCADWKY, cchs2003_i::ALCCDWKY, cchs2005_i:: ALCEDWKY, cchs2015_2016_i::ALWDVWKY, cchs2017_2018_i::ALWDVWKY, [ALWDWKY]",ICES confirmed,cont,NA::b,N/A,missing,missing,drinks/week,else,else,Drinks last week,Weekly consumption of alcohol,,, +CCC_071,CCC_071_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i ","cchs2001_p::CCCA_071, cchs2003_p::CCCC_071, cchs2005_p::CCCE_071, cchs2015_2016_p::CCC_065, cchs2017_2018_p::CCC_065, cchs2001_i::CCCA_071, cchs2003_i::CCCC_071, cchs2005_i::CCCE_071, cchs2015_2016_i::CCC_065, cchs2017_2018_i::CCC_065,[CCC_071]",ICES confirmed,cat,1,2,Hypertension,Hypertension,N/A,1,Yes (Do you have high blood pressure?),Hypertension,Do you have high blood pressure?,,, +CCC_071,CCC_071_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i ","cchs2001_p::CCCA_071, cchs2003_p::CCCC_071, cchs2005_p::CCCE_071, cchs2015_2016_p::CCC_065, cchs2017_2018_p::CCC_065, cchs2001_i::CCCA_071, cchs2003_i::CCCC_071, cchs2005_i::CCCE_071, cchs2015_2016_i::CCC_065, cchs2017_2018_i::CCC_065,[CCC_071]",ICES confirmed,cat,2,2,No Hypertension,No Hypertension,N/A,2,No (Do you have high blood pressure?),Hypertension,Do you have high blood pressure?,,, +CCC_071,CCC_071_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i ","cchs2001_p::CCCA_071, cchs2003_p::CCCC_071, cchs2005_p::CCCE_071, cchs2015_2016_p::CCC_065, cchs2017_2018_p::CCC_065, cchs2001_i::CCCA_071, cchs2003_i::CCCC_071, cchs2005_i::CCCE_071, cchs2015_2016_i::CCC_065, cchs2017_2018_i::CCC_065,[CCC_071]",ICES confirmed,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Hypertension,Do you have high blood pressure?,,, +CCC_071,CCC_071_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i ","cchs2001_p::CCCA_071, cchs2003_p::CCCC_071, cchs2005_p::CCCE_071, cchs2015_2016_p::CCC_065, cchs2017_2018_p::CCC_065, cchs2001_i::CCCA_071, cchs2003_i::CCCC_071, cchs2005_i::CCCE_071, cchs2015_2016_i::CCC_065, cchs2017_2018_i::CCC_065,[CCC_071]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Hypertension,Do you have high blood pressure?,,, +CCC_071,CCC_071_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i ","cchs2001_p::CCCA_071, cchs2003_p::CCCC_071, cchs2005_p::CCCE_071, cchs2015_2016_p::CCC_065, cchs2017_2018_p::CCC_065, cchs2001_i::CCCA_071, cchs2003_i::CCCC_071, cchs2005_i::CCCE_071, cchs2015_2016_i::CCC_065, cchs2017_2018_i::CCC_065,[CCC_071]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,else,else,Hypertension,Do you have high blood pressure?,,, +CCC_091,CCC_091_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::CCCA_91B, cchs2003_p::CCCC_91B, cchs2015_2016_p::CCC_030, cchs2017_2018_p::CCC_030, cchs2001_i::CCCA_91B, cchs2003_i::CCCC_91B, cchs2005_i::CCCE_91F, cchs2007_2008_i::CCC_91F, cchs2015_2016_i::CCC_030, cchs2017_2018_i::CCC_030, [CCC_091]",ICES confirmed,cat,1,2,COPD/emphysema/bronchitis,COPD/emphysema/bronchitis,N/A,1,"Yes (Do you have COPD(eg bronchitis,emphysema)?)",COPD/Emphysema/Bronchitis,"Do you have COPD (eg bronchitis, emphysema)?",,, +CCC_091,CCC_091_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::CCCA_91B, cchs2003_p::CCCC_91B, cchs2015_2016_p::CCC_030, cchs2017_2018_p::CCC_030, cchs2001_i::CCCA_91B, cchs2003_i::CCCC_91B, cchs2005_i::CCCE_91F, cchs2007_2008_i::CCC_91F, cchs2015_2016_i::CCC_030, cchs2017_2018_i::CCC_030, [CCC_091]",ICES confirmed,cat,2,2,No COPD/emphysema/bronchitis,No COPD/emphysema/bronchitis,N/A,2,"No (Do you have COPD(eg bronchitis,emphysema)?)",COPD/Emphysema/Bronchitis,"Do you have COPD (eg bronchitis, emphysema)?",,, +CCC_091,CCC_091_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::CCCA_91B, cchs2003_p::CCCC_91B, cchs2015_2016_p::CCC_030, cchs2017_2018_p::CCC_030, cchs2001_i::CCCA_91B, cchs2003_i::CCCC_91B, cchs2005_i::CCCE_91F, cchs2007_2008_i::CCC_91F, cchs2015_2016_i::CCC_030, cchs2017_2018_i::CCC_030, [CCC_091]",ICES confirmed,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,COPD/Emphysema/Bronchitis,"Do you have COPD (eg bronchitis, emphysema)?",,, +CCC_091,CCC_091_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::CCCA_91B, cchs2003_p::CCCC_91B, cchs2015_2016_p::CCC_030, cchs2017_2018_p::CCC_030, cchs2001_i::CCCA_91B, cchs2003_i::CCCC_91B, cchs2005_i::CCCE_91F, cchs2007_2008_i::CCC_91F, cchs2015_2016_i::CCC_030, cchs2017_2018_i::CCC_030, [CCC_091]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),COPD/Emphysema/Bronchitis,"Do you have COPD (eg bronchitis, emphysema)?",,, +CCC_091,CCC_091_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::CCCA_91B, cchs2003_p::CCCC_91B, cchs2015_2016_p::CCC_030, cchs2017_2018_p::CCC_030, cchs2001_i::CCCA_91B, cchs2003_i::CCCC_91B, cchs2005_i::CCCE_91F, cchs2007_2008_i::CCC_91F, cchs2015_2016_i::CCC_030, cchs2017_2018_i::CCC_030, [CCC_091]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,else,else,COPD/Emphysema/Bronchitis,"Do you have COPD (eg bronchitis, emphysema)?",,, +CCC_101,CCC_101_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::CCCA_101, cchs2003_p::CCCC_101, cchs2005_p::CCCE_101, cchs2015_2016_p::CCC_095, cchs2017_2018_p::CCC_095, cchs2001_i::CCCA_101, cchs2003_i::CCCC_101, cchs2005_i::CCCE_101, cchs2015_2016_i::CCC_095, cchs2017_2018_i::CCC_095,[CCC_101]",ICES confirmed,cat,1,2,Diabetes,Diabetes,N/A,1,Yes (Do you have diabetes?),Diabetes,Do you have diabetes?,,, +CCC_101,CCC_101_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s","cchs2001_p::CCCA_101, cchs2003_p::CCCC_101, cchs2005_p::CCCE_101, cchs2015_2016_p::CCC_095, cchs2017_2018_p::CCC_095, cchs2001_i::CCCA_101, cchs2003_i::CCCC_101, cchs2005_i::CCCE_101, cchs2015_2016_i::CCC_095, cchs2017_2018_i::CCC_095,[CCC_101]",ICES confirmed,cat,2,2,No Diabetes,No Diabetes,N/A,2,No (Do you have diabetes?),Diabetes,Do you have diabetes?,,, +CCC_101,CCC_101_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s","cchs2001_p::CCCA_101, cchs2003_p::CCCC_101, cchs2005_p::CCCE_101, cchs2015_2016_p::CCC_095, cchs2017_2018_p::CCC_095, cchs2001_i::CCCA_101, cchs2003_i::CCCC_101, cchs2005_i::CCCE_101, cchs2015_2016_i::CCC_095, cchs2017_2018_i::CCC_095,[CCC_101]",ICES confirmed,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Diabetes,Do you have diabetes?,,, +CCC_101,CCC_101_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s","cchs2001_p::CCCA_101, cchs2003_p::CCCC_101, cchs2005_p::CCCE_101, cchs2015_2016_p::CCC_095, cchs2017_2018_p::CCC_095, cchs2001_i::CCCA_101, cchs2003_i::CCCC_101, cchs2005_i::CCCE_101, cchs2015_2016_i::CCC_095, cchs2017_2018_i::CCC_095,[CCC_101]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Diabetes,Do you have diabetes?,,, +CCC_101,CCC_101_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s","cchs2001_p::CCCA_101, cchs2003_p::CCCC_101, cchs2005_p::CCCE_101, cchs2015_2016_p::CCC_095, cchs2017_2018_p::CCC_095, cchs2001_i::CCCA_101, cchs2003_i::CCCC_101, cchs2005_i::CCCE_101, cchs2015_2016_i::CCC_095, cchs2017_2018_i::CCC_095,[CCC_101]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,else,else,Diabetes,Do you have diabetes?,,, +CCC_111,CCC_111_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_p::CCCA_111, cchs2003_p::CCCC_111, cchs2005_p::CCCE_111, cchs2001_i::CCCA_111, cchs2003_i::CCCC_111, cchs2005_i::CCCE_111",ICES confirmed,cat,1,2,Epilepsy,Epilepsy,N/A,1,Yes (Do you have epilepsy?),Epilepsy,Do you have epilepsy?,,, +CCC_111,CCC_111_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_p::CCCA_111, cchs2003_p::CCCC_111, cchs2005_p::CCCE_111, cchs2001_i::CCCA_111, cchs2003_i::CCCC_111, cchs2005_i::CCCE_111",ICES confirmed,cat,2,2,No Epilepsy,No Epilepsy,N/A,2,No (Do you have epilepsy?),Epilepsy,Do you have epilepsy?,,, +CCC_111,CCC_111_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_p::CCCA_111, cchs2003_p::CCCC_111, cchs2005_p::CCCE_111, cchs2001_i::CCCA_111, cchs2003_i::CCCC_111, cchs2005_i::CCCE_111",ICES confirmed,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Epilepsy,Do you have epilepsy?,,, +CCC_111,CCC_111_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_p::CCCA_111, cchs2003_p::CCCC_111, cchs2005_p::CCCE_111, cchs2001_i::CCCA_111, cchs2003_i::CCCC_111, cchs2005_i::CCCE_111",ICES confirmed,cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Epilepsy,Do you have epilepsy?,,, +CCC_111,CCC_111_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_p::CCCA_111, cchs2003_p::CCCC_111, cchs2005_p::CCCE_111, cchs2001_i::CCCA_111, cchs2003_i::CCCC_111, cchs2005_i::CCCE_111",ICES confirmed,cat,NA::b,2,missing,missing,N/A,else,else,Epilepsy,Do you have epilepsy?,,, +CCC_121,CCC_121_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::CCCA_121, cchs2003_p::CCCC_121, cchs2005_p::CCCE_121, cchs2015_2016_p::CCC_085, cchs2017_2018_p::CCC_085, cchs2001_i::CCCA_121, cchs2003_i::CCCC_121, cchs2005_i::CCCE_121, cchs2015_2016_i::CCC_085, cchs2017_2018_i::CCC_085,[CCC_121]",ICES confirmed,cat,1,2,Heart Disease,Heart Disease,N/A,1,Yes (Do you have heart disease?),Heart Disease,Do you have heart disease?,,, +CCC_121,CCC_121_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s","cchs2001_p::CCCA_121, cchs2003_p::CCCC_121, cchs2005_p::CCCE_121, cchs2015_2016_p::CCC_085, cchs2017_2018_p::CCC_085, cchs2001_i::CCCA_121, cchs2003_i::CCCC_121, cchs2005_i::CCCE_121, cchs2015_2016_i::CCC_085, cchs2017_2018_i::CCC_085,[CCC_121]",ICES confirmed,cat,2,2,No Heart Disease,No Heart Disease,N/A,2,No (Do you have heart disease?),Heart Disease,Do you have heart disease?,,, +CCC_121,CCC_121_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s","cchs2001_p::CCCA_121, cchs2003_p::CCCC_121, cchs2005_p::CCCE_121, cchs2015_2016_p::CCC_085, cchs2017_2018_p::CCC_085, cchs2001_i::CCCA_121, cchs2003_i::CCCC_121, cchs2005_i::CCCE_121, cchs2015_2016_i::CCC_085, cchs2017_2018_i::CCC_085,[CCC_121]",ICES confirmed,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Heart Disease,Do you have heart disease?,,, +CCC_121,CCC_121_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s","cchs2001_p::CCCA_121, cchs2003_p::CCCC_121, cchs2005_p::CCCE_121, cchs2015_2016_p::CCC_085, cchs2017_2018_p::CCC_085, cchs2001_i::CCCA_121, cchs2003_i::CCCC_121, cchs2005_i::CCCE_121, cchs2015_2016_i::CCC_085, cchs2017_2018_i::CCC_085,[CCC_121]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Heart Disease,Do you have heart disease?,,, +CCC_121,CCC_121_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s","cchs2001_p::CCCA_121, cchs2003_p::CCCC_121, cchs2005_p::CCCE_121, cchs2015_2016_p::CCC_085, cchs2017_2018_p::CCC_085, cchs2001_i::CCCA_121, cchs2003_i::CCCC_121, cchs2005_i::CCCE_121, cchs2015_2016_i::CCC_085, cchs2017_2018_i::CCC_085,[CCC_121]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,else,else,Heart Disease,Do you have heart disease?,,, +CCC_151,CCC_151_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, ccsh2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::CCCA_151, cchs2003_p::CCCC_151, cchs2005_p::CCCE_151, cchs2015_2016_p::CCC_090, cchs2017_2018_p::CCC_090, cchs2001_i::CCCA_151, cchs2003_i::CCCC_151, cchs2005_i::CCCE_151, cchs2015_2016_i::CCC_090, cchs2017_2018_i::CCC_090,[CCC_151]",ICES confirmed,cat,1,2,Stroke,Stroke,N/A,1,Yes (Do you suffer from the effects of stroke?),Stroke,Do you suffer from effects of stroke?,,, +CCC_151,CCC_151_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, ccsh2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::CCCA_151, cchs2003_p::CCCC_151, cchs2005_p::CCCE_151, cchs2015_2016_p::CCC_090, cchs2017_2018_p::CCC_090, cchs2001_i::CCCA_151, cchs2003_i::CCCC_151, cchs2005_i::CCCE_151, cchs2015_2016_i::CCC_090, cchs2017_2018_i::CCC_090,[CCC_151]",ICES confirmed,cat,2,2,No Stroke,No Stroke,N/A,2,No (Do you suffer from the effects of stroke?),Stroke,Do you suffer from effects of stroke?,,, +CCC_151,CCC_151_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, ccsh2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::CCCA_151, cchs2003_p::CCCC_151, cchs2005_p::CCCE_151, cchs2015_2016_p::CCC_090, cchs2017_2018_p::CCC_090, cchs2001_i::CCCA_151, cchs2003_i::CCCC_151, cchs2005_i::CCCE_151, cchs2015_2016_i::CCC_090, cchs2017_2018_i::CCC_090,[CCC_151]",ICES confirmed,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Stroke,Do you suffer from effects of stroke?,,, +CCC_151,CCC_151_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, ccsh2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::CCCA_151, cchs2003_p::CCCC_151, cchs2005_p::CCCE_151, cchs2015_2016_p::CCC_090, cchs2017_2018_p::CCC_090, cchs2001_i::CCCA_151, cchs2003_i::CCCC_151, cchs2005_i::CCCE_151, cchs2015_2016_i::CCC_090, cchs2017_2018_i::CCC_090,[CCC_151]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Stroke,Do you suffer from effects of stroke?,,, +CCC_151,CCC_151_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, ccsh2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::CCCA_151, cchs2003_p::CCCC_151, cchs2005_p::CCCE_151, cchs2015_2016_p::CCC_090, cchs2017_2018_p::CCC_090, cchs2001_i::CCCA_151, cchs2003_i::CCCC_151, cchs2005_i::CCCE_151, cchs2015_2016_i::CCC_090, cchs2017_2018_i::CCC_090,[CCC_151]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,else,else,Stroke,Do you suffer from effects of stroke?,,, +CCC_280,CCC_280_cat2_1,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_p::CCCC_280, cchs2005_p::CCCE_280, cchs2015_2016_p::CCC_195, cchs2017_2018_p::CCC_195, cchs2003_i::CCCC_280, cchs2005_i::CCCE_280, cchs2015_2016_i::CCC_195, cchs2017_2018_i::CCC_195, [CCC_280]",ICES confirmed,cat,1,2,Has a mood disorder,Has a mood disorder,N/A,1,Yes (Do you have a mood disorder?),Mood disorder,Do you have a mood disorder?,,, +CCC_280,CCC_280_cat2_2,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_p::CCCC_280, cchs2005_p::CCCE_280, cchs2015_2016_p::CCC_195, cchs2017_2018_p::CCC_195, cchs2003_i::CCCC_280, cchs2005_i::CCCE_280, cchs2015_2016_i::CCC_195, cchs2017_2018_i::CCC_195, [CCC_280]",ICES confirmed,cat,2,2,Does not have a mood disorder,Does not have a mood disorder,N/A,2,No (Do you have a mood disorder?),Mood disorder,Do you have a mood disorder?,,, +CCC_280,CCC_280_cat2_NA::a,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_p::CCCC_280, cchs2005_p::CCCE_280, cchs2015_2016_p::CCC_195, cchs2017_2018_p::CCC_195, cchs2003_i::CCCC_280, cchs2005_i::CCCE_280, cchs2015_2016_i::CCC_195, cchs2017_2018_i::CCC_195, [CCC_280]",ICES confirmed,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Mood disorder,Do you have a mood disorder?,,, +CCC_280,CCC_280_cat2_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_p::CCCC_280, cchs2005_p::CCCE_280, cchs2015_2016_p::CCC_195, cchs2017_2018_p::CCC_195, cchs2003_i::CCCC_280, cchs2005_i::CCCE_280, cchs2015_2016_i::CCC_195, cchs2017_2018_i::CCC_195, [CCC_280]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Mood disorder,Do you have a mood disorder?,,, +CCC_280,CCC_280_cat2_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_p::CCCC_280, cchs2005_p::CCCE_280, cchs2015_2016_p::CCC_195, cchs2017_2018_p::CCC_195, cchs2003_i::CCCC_280, cchs2005_i::CCCE_280, cchs2015_2016_i::CCC_195, cchs2017_2018_i::CCC_195, [CCC_280]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,else,else,Mood disorder,Do you have a mood disorder?,,, +DHH_SEX,DHH_SEX_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::DHHA_SEX, cchs2003_p::DHHC_SEX, cchs2005_p::DHHE_SEX, cchs2001_i::DHHA_SEX, cchs2003_i::DHHC_SEX, cchs2005_i::DHHE, [DHH_SEX]",ICES confirmed,cat,1,2,Male,Male,N/A,1,Male,Sex,Sex,,, +DHH_SEX,DHH_SEX_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::DHHA_SEX, cchs2003_p::DHHC_SEX, cchs2005_p::DHHE_SEX, cchs2001_i::DHHA_SEX, cchs2003_i::DHHC_SEX, cchs2005_i::DHHE, [DHH_SEX]",ICES confirmed,cat,2,2,Female,Female,N/A,2,Female,Sex,Sex,,, +DHH_SEX,DHH_SEX_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::DHHA_SEX, cchs2003_p::DHHC_SEX, cchs2005_p::DHHE_SEX, cchs2001_i::DHHA_SEX, cchs2003_i::DHHC_SEX, cchs2005_i::DHHE, [DHH_SEX]",ICES confirmed,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Sex,Sex,,, +DHH_SEX,DHH_SEX_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::DHHA_SEX, cchs2003_p::DHHC_SEX, cchs2005_p::DHHE_SEX, cchs2001_i::DHHA_SEX, cchs2003_i::DHHC_SEX, cchs2005_i::DHHE, [DHH_SEX]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Sex,Sex,,, +DHH_SEX,DHH_SEX_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::DHHA_SEX, cchs2003_p::DHHC_SEX, cchs2005_p::DHHE_SEX, cchs2001_i::DHHA_SEX, cchs2003_i::DHHC_SEX, cchs2005_i::DHHE, [DHH_SEX]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,else,else,Sex,Sex,,, +DHH_AGE,N/A,cont,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::DHHA_AGE, cchs2003_i::DHHC_AGE, cchs2005_i::DHHE_AGE, [DHH_AGE]",ICES altered,cont,copy,N/A,Age,continuous age,years,"[12,102]",Age,Age,Continuous age,Share files have continuous age.,, +DHH_AGE,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::DHHA_AGE, cchs2003_i::DHHC_AGE, cchs2005_i::DHHE_AGE, [DHH_AGE]",ICES altered,cont,NA::a,N/A,not applicable,not applicable,years,96,not applicable,Age,Continuous age,,, +DHH_AGE,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::DHHA_AGE, cchs2003_i::DHHC_AGE, cchs2005_i::DHHE_AGE, [DHH_AGE]",ICES altered,cont,NA::b,N/A,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),Age,Continuous age,,, +DHH_AGE,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::DHHA_AGE, cchs2003_i::DHHC_AGE, cchs2005_i::DHHE_AGE, [DHH_AGE]",ICES altered,cont,NA::b,N/A,missing,missing,years,else,else,Age,Continuous age,,, +DHH_MS,DHH_MS_cat4_1,cat,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::DHHA_MS, cchs2003_i::DHHC_MS, cchs2005_i::DHHE_MS, [DHH_MS]",ICES specific,cat,1,4,Married,Married,N/A,1,Married,Marital status,2001:Marital status - (G); [Marital status],,, +DHH_MS,DHH_MS_cat4_2,cat,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::DHHA_MS, cchs2003_i::DHHC_MS, cchs2005_i::DHHE_MS, [DHH_MS]",ICES specific,cat,2,4,Common-law,Common-law,N/A,2,Common-law,Marital status,2001:Marital status - (G); [Marital status],,, +DHH_MS,DHH_MS_cat4_3,cat,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::DHHA_MS, cchs2003_i::DHHC_MS, cchs2005_i::DHHE_MS, [DHH_MS]",ICES specific,cat,3,4,Widow/Sep/Div,Widow/Sep/Div,N/A,"[3,5]",Widow/Sep/Div,Marital status,2001:Marital status - (G); [Marital status],,, +DHH_MS,DHH_MS_cat4_4,cat,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::DHHA_MS, cchs2003_i::DHHC_MS, cchs2005_i::DHHE_MS, [DHH_MS]",ICES specific,cat,4,4,Single/Never mar.,Single/Never mar.,N/A,6,Single/Never mar.,Marital status,2001:Marital status - (G); [Marital status],,, +DHH_MS,DHH_MS_cat4_NA::a,cat,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::DHHA_MS, cchs2003_i::DHHC_MS, cchs2005_i::DHHE_MS, [DHH_MS]",ICES specific,cat,NA::a,4,not applicable,not applicable,N/A,96,not applicable,Marital status,2001:Marital status - (G); [Marital status],,, +DHH_MS,DHH_MS_cat4_NA::b,cat,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::DHHA_MS, cchs2003_i::DHHC_MS, cchs2005_i::DHHE_MS, [DHH_MS]",ICES specific,cat,NA::b,4,missing,missing,N/A,"[97,99]",don't know (97); refusal (98); not stated (99),Marital status,2001:Marital status - (G); [Marital status],,, +DHH_MS,DHH_MS_cat4_NA::b,cat,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::DHHA_MS, cchs2003_i::DHHC_MS, cchs2005_i::DHHE_MS, [DHH_MS]",ICES specific,cat,NA::b,4,missing,missing,N/A,else,else,Marital status,2001:Marital status - (G); [Marital status],,, +DHH_MS_A,DHH_MS_DemPoRT_cat3_1,cat,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::DHHA_MS, cchs2003_i::DHHC_MS, cchs2005_i::DHHE_MS, [DHH_MS]",ICES specific,cat,1,4,Married/Common-law,Married/Common-law,N/A,"[1,2]",Married/Common-law,Marital status,2001:Marital status - (G); [Marital status],DemPoRt marriage categories,, +DHH_MS_A,DHH_MS_DemPoRT_cat3_2,cat,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::DHHA_MS, cchs2003_i::DHHC_MS, cchs2005_i::DHHE_MS, [DHH_MS]",ICES specific,cat,2,4,Sep/Div,Sep/Div,N/A,"[4,5]",Sep/Div,Marital status,2001:Marital status - (G); [Marital status],DemPoRt marriage categories,, +DHH_MS_A,DHH_MS_DemPoRT_cat3_3,cat,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::DHHA_MS, cchs2003_i::DHHC_MS, cchs2005_i::DHHE_MS, [DHH_MS]",ICES specific,cat,3,4,Widow,Widow,N/A,3,Widow,Marital status,2001:Marital status - (G); [Marital status],DemPoRt marriage categories,, +DHH_MS_A,DHH_MS_DemPoRT_cat3_3,cat,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::DHHA_MS, cchs2003_i::DHHC_MS, cchs2005_i::DHHE_MS, [DHH_MS]",ICES specific,cat,4,4,Single ,Single ,N/A,6,Single ,Marital status,2001:Marital status - (G); [Marital status],DemPoRt marriage categories,, +DHH_MS_A,DHH_MS_DemPoRT_cat3_NA::a,cat,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::DHHA_MS, cchs2003_i::DHHC_MS, cchs2005_i::DHHE_MS, [DHH_MS]",ICES specific,cat,NA::a,4,not applicable,not applicable,N/A,96,not applicable,Marital status,2001:Marital status - (G); [Marital status],DemPoRt marriage categories,, +DHH_MS_A,DHH_MS_DemPoRT_cat3_NA::b,cat,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::DHHA_MS, cchs2003_i::DHHC_MS, cchs2005_i::DHHE_MS, [DHH_MS]",ICES specific,cat,NA::b,4,missing,missing,N/A,"[97,99]",don't know (97); refusal (98); not stated (99),Marital status,2001:Marital status - (G); [Marital status],DemPoRt marriage categories,, +DHH_MS_A,DHH_MS_DemPoRT_cat3_NA::b,cat,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::DHHA_MS, cchs2003_i::DHHC_MS, cchs2005_i::DHHE_MS, [DHH_MS]",ICES specific,cat,NA::b,4,missing,missing,N/A,else,else,Marital status,2001:Marital status - (G); [Marital status],DemPoRt marriage categories,, +EDUDR04,EDUDR04_cat4_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::EDUADR04, cchs2003_p::EDUCDR04, cchs2005_p::EDUEDR04, cchs2001_i::EDUADR04, cchs2003_i::EDUCDR04, cchs2005_i::EDUEDR04, cchs2015_2016_i::EHG2DVR3, cchs2017_2018_i::EHG2DVR3, [EDUDR04]",ICES confirmed,cat,1,4,Less than high school,Less than High School,N/A,1,< Than Secondary,Highest education,Highest level/education - 4 categories,Slight change in wording of categories from CCHS 2011 onwards,, +EDUDR04,EDUDR04_cat4_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::EDUADR04, cchs2003_p::EDUCDR04, cchs2005_p::EDUEDR04, cchs2001_i::EDUADR04, cchs2003_i::EDUCDR04, cchs2005_i::EDUEDR04, cchs2015_2016_i::EHG2DVR3, cchs2017_2018_i::EHG2DVR3, [EDUDR04]",ICES confirmed,cat,2,4,High school graduate,High School Graduate,N/A,2,Secondary grad,Highest education,Highest level/education - 4 categories,,, +EDUDR04,EDUDR04_cat4_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::EDUADR04, cchs2003_p::EDUCDR04, cchs2005_p::EDUEDR04, cchs2001_i::EDUADR04, cchs2003_i::EDUCDR04, cchs2005_i::EDUEDR04, cchs2015_2016_i::EHG2DVR3, cchs2017_2018_i::EHG2DVR3, [EDUDR04]",ICES confirmed,cat,3,4,Some post-secondary education,Some post-secondary education,N/A,3,Other post-sec.,Highest education,Highest level/education - 4 categories,,, +EDUDR04,EDUDR04_cat4_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::EDUADR04, cchs2003_p::EDUCDR04, cchs2005_p::EDUEDR04, cchs2001_i::EDUADR04, cchs2003_i::EDUCDR04, cchs2005_i::EDUEDR04, cchs2015_2016_i::EHG2DVR3, cchs2017_2018_i::EHG2DVR3, [EDUDR04]",ICES confirmed,cat,4,4,Post-secondary graduate,Post-secondary graduate,N/A,4,Post-sec. grad,Highest education,Highest level/education - 4 categories,,, +EDUDR04,EDUDR04_cat4_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::EDUADR04, cchs2003_p::EDUCDR04, cchs2005_p::EDUEDR04, cchs2001_i::EDUADR04, cchs2003_i::EDUCDR04, cchs2005_i::EDUEDR04, cchs2015_2016_i::EHG2DVR3, cchs2017_2018_i::EHG2DVR3, [EDUDR04]",ICES confirmed,cat,NA::a,4,not applicable,not applicable,N/A,6,not applicable,Highest education,Highest level/education - 4 categories,,, +EDUDR04,EDUDR04_cat4_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::EDUADR04, cchs2003_p::EDUCDR04, cchs2005_p::EDUEDR04, cchs2001_i::EDUADR04, cchs2003_i::EDUCDR04, cchs2005_i::EDUEDR04, cchs2015_2016_i::EHG2DVR3, cchs2017_2018_i::EHG2DVR3, [EDUDR04]",ICES confirmed,cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Highest education,Highest level/education - 4 categories,CCHS 2001 does not have don't know (7) or refusal (8); CCHS 2001 ICES has don't know (7) and refusal (8),, +EDUDR04,EDUDR04_cat4_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::EDUADR04, cchs2003_p::EDUCDR04, cchs2005_p::EDUEDR04, cchs2001_i::EDUADR04, cchs2003_i::EDUCDR04, cchs2005_i::EDUEDR04, cchs2015_2016_i::EHG2DVR3, cchs2017_2018_i::EHG2DVR3, [EDUDR04]",ICES confirmed,cat,NA::b,4,missing,missing,N/A,else,else,Highest education,Highest level/education - 4 categories,,, +FVCDJUI,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs20013_2014_i, cchs2015_2016_i","cchs2001_p::FVCADJUI, cchs2003_p::FVCCDJUI, cchs2005_p::FVCEDJUI, cchs2015_2016_p::FVCDVJUI, cchs2017_2018_p::FVCDVJUI, cchs2001_i::FVCADJUI, cchs2003_i::FVCCDJUI, cchs2005_i::FVCEDJUI, cchs2015_2016_i::FVCDVJUI, [FVCDJUI]",ICES confirmed,cont,copy,N/A,Daily juice,Daily juice,N/A,"[0,47]",Daily consumption - fruit juice - (D),Juice consumption,Daily consumption - fruit juice (D),,, +FVCDJUI,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs20013_2014_i, cchs2015_2016_i","cchs2001_p::FVCADJUI, cchs2003_p::FVCCDJUI, cchs2005_p::FVCEDJUI, cchs2015_2016_p::FVCDVJUI, cchs2017_2018_p::FVCDVJUI, cchs2001_i::FVCADJUI, cchs2003_i::FVCCDJUI, cchs2005_i::FVCEDJUI, cchs2015_2016_i::FVCDVJUI, [FVCDJUI]",ICES confirmed,cont,NA::a,N/A,not applicable,not applicable,N/A,999.6,Not applicable,Juice consumption,Daily consumption - fruit juice (D),,, +FVCDJUI,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs20013_2014_i, cchs2015_2016_i","cchs2001_p::FVCADJUI, cchs2003_p::FVCCDJUI, cchs2005_p::FVCEDJUI, cchs2015_2016_p::FVCDVJUI, cchs2017_2018_p::FVCDVJUI, cchs2001_i::FVCADJUI, cchs2003_i::FVCCDJUI, cchs2005_i::FVCEDJUI, cchs2015_2016_i::FVCDVJUI, [FVCDJUI]",ICES confirmed,cont,NA::b,N/A,missing,missing,N/A,"[999.7,999.9]",don't know (999.7); refusal (999.8); not stated (999.9),Juice consumption,Daily consumption - fruit juice (D),Don't know (999.7) and refusal (999.8) not included in 2001 CCHS,, +FVCDJUI,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs20013_2014_i, cchs2015_2016_i","cchs2001_p::FVCADJUI, cchs2003_p::FVCCDJUI, cchs2005_p::FVCEDJUI, cchs2015_2016_p::FVCDVJUI, cchs2017_2018_p::FVCDVJUI, cchs2001_i::FVCADJUI, cchs2003_i::FVCCDJUI, cchs2005_i::FVCEDJUI, cchs2015_2016_i::FVCDVJUI, [FVCDJUI]",ICES confirmed,cont,NA::b,N/A,missing,missing,N/A,else,else,Juice consumption,Daily consumption - fruit juice (D),,, +FVCDPOT,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2001_p::FVCADPOT, cchs2003_p::FVCCDPOT, cchs2005_p::FVCEDPOT, cchs2015_2016_p::FVCDVPOT, cchs2017_2018_p::FVCDVPOT,cchs2001_i::FVCADPOT, cchs2003_i::FVCCDPOT, cchs2005_i::FVCEDPOT, cchs2015_2016_i::FVCDVPOT, [FVCDPOT]",ICES confirmed,cont,copy,N/A,Daily potatoes,Daily potatoes,N/A,"[0,30]",Daily consumption - potatoes - (D),Potato consumption,Daily consumption - potatoes (D),,, +FVCDPOT,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2001_p::FVCADPOT, cchs2003_p::FVCCDPOT, cchs2005_p::FVCEDPOT, cchs2015_2016_p::FVCDVPOT, cchs2017_2018_p::FVCDVPOT,cchs2001_i::FVCADPOT, cchs2003_i::FVCCDPOT, cchs2005_i::FVCEDPOT, cchs2015_2016_i::FVCDVPOT, [FVCDPOT]",ICES confirmed,cont,NA::a,N/A,not applicable,not applicable,N/A,999.6,Not applicable,Potato consumption,Daily consumption - potatoes (D),,, +FVCDPOT,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2001_p::FVCADPOT, cchs2003_p::FVCCDPOT, cchs2005_p::FVCEDPOT, cchs2015_2016_p::FVCDVPOT, cchs2017_2018_p::FVCDVPOT,cchs2001_i::FVCADPOT, cchs2003_i::FVCCDPOT, cchs2005_i::FVCEDPOT, cchs2015_2016_i::FVCDVPOT, [FVCDPOT]",ICES confirmed,cont,NA::b,N/A,missing,missing,N/A,"[999.7,999.9]",don't know (999.7); refusal (999.8); not stated (999.9),Potato consumption,Daily consumption - potatoes (D),Don't know (999.7) and refusal (999.8) not included in 2001 CCHS,, +FVCDPOT,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2001_p::FVCADPOT, cchs2003_p::FVCCDPOT, cchs2005_p::FVCEDPOT, cchs2015_2016_p::FVCDVPOT, cchs2017_2018_p::FVCDVPOT,cchs2001_i::FVCADPOT, cchs2003_i::FVCCDPOT, cchs2005_i::FVCEDPOT, cchs2015_2016_i::FVCDVPOT, [FVCDPOT]",ICES confirmed,cont,NA::b,N/A,missing,missing,N/A,else,else,Potato consumption,Daily consumption - potatoes (D),,, +FVCDTOT,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2001_p::FVCADTOT, cchs2003_p::FVCCDTOT, cchs2005_p::FVCEDTOT, cchs2015_2016_p::FVCDVTOT, cchs2017_2018_p::FVCDVTOT, cchs2001_i::FVCADTOT, cchs2003_i::FVCCDTOT, cchs2005_i::FVCEDTOT, cchs2015_2016_i::FVCDVTOT,[FVCDTOT]",ICES confirmed,cont,copy,N/A,Daily total fruits and vegetables,Daily total fruits and vegetables,N/A,"[0,70]",Daily consumption - total fruits and veg. - (D),Total fruit/veg consumption,Daily consumptoin - total fruits and veg. - (D),,, +FVCDTOT,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2001_p::FVCADTOT, cchs2003_p::FVCCDTOT, cchs2005_p::FVCEDTOT, cchs2015_2016_p::FVCDVTOT, cchs2017_2018_p::FVCDVTOT, cchs2001_i::FVCADTOT, cchs2003_i::FVCCDTOT, cchs2005_i::FVCEDTOT, cchs2015_2016_i::FVCDVTOT,[FVCDTOT]",ICES confirmed,cont,NA::a,N/A,not applicable,not applicable,N/A,999.6,Not applicable,Total fruit/veg consumption,Daily consumptoin - total fruits and veg. - (D),,, +FVCDTOT,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2001_p::FVCADTOT, cchs2003_p::FVCCDTOT, cchs2005_p::FVCEDTOT, cchs2015_2016_p::FVCDVTOT, cchs2017_2018_p::FVCDVTOT, cchs2001_i::FVCADTOT, cchs2003_i::FVCCDTOT, cchs2005_i::FVCEDTOT, cchs2015_2016_i::FVCDVTOT,[FVCDTOT]",ICES confirmed,cont,NA::b,N/A,missing,missing,N/A,"[999.7,999.9]",don't know (999.7); refusal (999.8); not stated (999.9),Total fruit/veg consumption,Daily consumptoin - total fruits and veg. - (D),Don't know (999.7) and refusal (999.8) not included in 2001 CCHS,, +FVCDTOT,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2001_p::FVCADTOT, cchs2003_p::FVCCDTOT, cchs2005_p::FVCEDTOT, cchs2015_2016_p::FVCDVTOT, cchs2017_2018_p::FVCDVTOT, cchs2001_i::FVCADTOT, cchs2003_i::FVCCDTOT, cchs2005_i::FVCEDTOT, cchs2015_2016_i::FVCDVTOT,[FVCDTOT]",ICES confirmed,cont,NA::b,N/A,missing,missing,N/A,else,else,Total fruit/veg consumption,Daily consumptoin - total fruits and veg. - (D),,, +FVCDTOT,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2001_p::FVCADTOT, cchs2003_p::FVCCDTOT, cchs2005_p::FVCEDTOT, cchs2015_2016_p::FVCDVTOT, cchs2017_2018_p::FVCDVTOT, cchs2001_i::FVCADTOT, cchs2003_i::FVCCDTOT, cchs2005_i::FVCEDTOT, cchs2015_2016_i::FVCDVTOT,[FVCDTOT]",ICES confirmed,cont,NA::a,N/A,not applicable,not applicable,N/A,9999.6,Not applicable,Total fruit/veg consumption,Daily consumptoin - total fruits and veg. - (D),Not applicable (9999.6) not included in 2015-2016 CCHS,, +FVCDTOT,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2001_p::FVCADTOT, cchs2003_p::FVCCDTOT, cchs2005_p::FVCEDTOT, cchs2015_2016_p::FVCDVTOT, cchs2017_2018_p::FVCDVTOT, cchs2001_i::FVCADTOT, cchs2003_i::FVCCDTOT, cchs2005_i::FVCEDTOT, cchs2015_2016_i::FVCDVTOT,[FVCDTOT]",ICES confirmed,cont,NA::b,N/A,missing,missing,N/A,9999.9,don't know (999.7); refusal (999.8); not stated (999.9),Total fruit/veg consumption,Daily consumptoin - total fruits and veg. - (D),,, +GEN_01,GEN_01_cat5_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_01, cchs2003_p::GENC_01, cchs2005_p::GENE_01, cchs2015_2016_p::GEN_005, cchs2017_2018_p::GEN_005, cchs2001_i::GENA_i, cchs2003_i::GENC_01, cchs2005_i::GENE_01, cchs2015_2016_i::GEN_005, cchs2017_2018_i::GEN_005, [GEN_01]",ICES confirmed,cat,1,5,Excellent,Excellent,N/A,1,Excellent,Self-perceived health,Self-perceived health,,, +GEN_01,GEN_01_cat5_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_01, cchs2003_p::GENC_01, cchs2005_p::GENE_01, cchs2015_2016_p::GEN_005, cchs2017_2018_p::GEN_005, cchs2001_i::GENA_i, cchs2003_i::GENC_01, cchs2005_i::GENE_01, cchs2015_2016_i::GEN_005, cchs2017_2018_i::GEN_005, [GEN_01]",ICES confirmed,cat,2,5,Very good,Very good,N/A,2,Very good,Self-perceived health,Self-perceived health,,, +GEN_01,GEN_01_cat5_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_01, cchs2003_p::GENC_01, cchs2005_p::GENE_01, cchs2015_2016_p::GEN_005, cchs2017_2018_p::GEN_005, cchs2001_i::GENA_i, cchs2003_i::GENC_01, cchs2005_i::GENE_01, cchs2015_2016_i::GEN_005, cchs2017_2018_i::GEN_005, [GEN_01]",ICES confirmed,cat,3,5,Good,Good,N/A,3,Good,Self-perceived health,Self-perceived health,,, +GEN_01,GEN_01_cat5_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_01, cchs2003_p::GENC_01, cchs2005_p::GENE_01, cchs2015_2016_p::GEN_005, cchs2017_2018_p::GEN_005, cchs2001_i::GENA_i, cchs2003_i::GENC_01, cchs2005_i::GENE_01, cchs2015_2016_i::GEN_005, cchs2017_2018_i::GEN_005, [GEN_01]",ICES confirmed,cat,4,5,Fair,Fair,N/A,4,Fair,Self-perceived health,Self-perceived health,,, +GEN_01,GEN_01_cat5_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_01, cchs2003_p::GENC_01, cchs2005_p::GENE_01, cchs2015_2016_p::GEN_005, cchs2017_2018_p::GEN_005, cchs2001_i::GENA_i, cchs2003_i::GENC_01, cchs2005_i::GENE_01, cchs2015_2016_i::GEN_005, cchs2017_2018_i::GEN_005, [GEN_01]",ICES confirmed,cat,5,5,Poor,Poor,N/A,5,Poor,Self-perceived health,Self-perceived health,,, +GEN_01,GEN_01_cat5_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_01, cchs2003_p::GENC_01, cchs2005_p::GENE_01, cchs2015_2016_p::GEN_005, cchs2017_2018_p::GEN_005, cchs2001_i::GENA_i, cchs2003_i::GENC_01, cchs2005_i::GENE_01, cchs2015_2016_i::GEN_005, cchs2017_2018_i::GEN_005, [GEN_01]",ICES confirmed,cat,NA::a,5,not applicable,not applicable,N/A,6,not applicable,Self-perceived health,Self-perceived health,,, +GEN_01,GEN_01_cat5_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_01, cchs2003_p::GENC_01, cchs2005_p::GENE_01, cchs2015_2016_p::GEN_005, cchs2017_2018_p::GEN_005, cchs2001_i::GENA_i, cchs2003_i::GENC_01, cchs2005_i::GENE_01, cchs2015_2016_i::GEN_005, cchs2017_2018_i::GEN_005, [GEN_01]",ICES confirmed,cat,NA::b,5,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Self-perceived health,Self-perceived health,,, +GEN_01,GEN_01_cat5_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_01, cchs2003_p::GENC_01, cchs2005_p::GENE_01, cchs2015_2016_p::GEN_005, cchs2017_2018_p::GEN_005, cchs2001_i::GENA_i, cchs2003_i::GENC_01, cchs2005_i::GENE_01, cchs2015_2016_i::GEN_005, cchs2017_2018_i::GEN_005, [GEN_01]",ICES confirmed,cat,NA::b,5,missing,missing,N/A,else,else,Self-perceived health,Self-perceived health,,, +GEN_07,GEN_07_cat5_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_07, cchs2003_p::GENC_07, cchs2005_p::GENE_07, cchs2015_2016_p::GEN_020, cchs2017_2018_p:: GEN_020, cchs2001_i::GENA_07, cchs2003_i::GENC_07, cchs2005_i::GENE_07, cchs2015_2016_i::GEN_020, cchs2017_2018_i:: GEN_020, [GEN_07]",ICES confirmed,cat,1,5,Not at all,Not at all,N/A,1,Not at all,Self-perceived life stress,Self-perceived life stress,,, +GEN_07,GEN_07_cat5_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_07, cchs2003_p::GENC_07, cchs2005_p::GENE_07, cchs2015_2016_p::GEN_020, cchs2017_2018_p:: GEN_020,cchs2001_i::GENA_07, cchs2003_i::GENC_07, cchs2005_i::GENE_07, cchs2015_2016_i::GEN_020, cchs2017_2018_i:: GEN_020, [GEN_07]",ICES confirmed,cat,2,5,Not very,Not very,N/A,2,Not very,Self-perceived life stress,Self-perceived life stress,,, +GEN_07,GEN_07_cat5_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_07, cchs2003_p::GENC_07, cchs2005_p::GENE_07, cchs2015_2016_p::GEN_020, cchs2017_2018_p:: GEN_020,cchs2001_i::GENA_07, cchs2003_i::GENC_07, cchs2005_i::GENE_07, cchs2015_2016_i::GEN_020, cchs2017_2018_i:: GEN_020, [GEN_07]",ICES confirmed,cat,3,5,A bit,A bit,N/A,3,A bit,Self-perceived life stress,Self-perceived life stress,,, +GEN_07,GEN_07_cat5_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_07, cchs2003_p::GENC_07, cchs2005_p::GENE_07, cchs2015_2016_p::GEN_020, cchs2017_2018_p:: GEN_020,cchs2001_i::GENA_07, cchs2003_i::GENC_07, cchs2005_i::GENE_07, cchs2015_2016_i::GEN_020, cchs2017_2018_i:: GEN_020, [GEN_07]",ICES confirmed,cat,4,5,Quite a bit,Quite a bit,N/A,4,Quite a bit,Self-perceived life stress,Self-perceived life stress,,, +GEN_07,GEN_07_cat5_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_07, cchs2003_p::GENC_07, cchs2005_p::GENE_07, cchs2015_2016_p::GEN_020, cchs2017_2018_p:: GEN_020,cchs2001_i::GENA_07, cchs2003_i::GENC_07, cchs2005_i::GENE_07, cchs2015_2016_i::GEN_020, cchs2017_2018_i:: GEN_020, [GEN_07]",ICES confirmed,cat,5,5,Extremely,Extremely,N/A,5,Extremely,Self-perceived life stress,Self-perceived life stress,,, +GEN_07,GEN_07_cat5_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_07, cchs2003_p::GENC_07, cchs2005_p::GENE_07, cchs2015_2016_p::GEN_020, cchs2017_2018_p:: GEN_020,cchs2001_i::GENA_07, cchs2003_i::GENC_07, cchs2005_i::GENE_07, cchs2015_2016_i::GEN_020, cchs2017_2018_i:: GEN_020, [GEN_07]",ICES confirmed,cat,NA::a,5,not applicable,not applicable,N/A,6,not applicable,Self-perceived life stress,Self-perceived life stress,CCHS 2015-2018 does not have not applicable (6),, +GEN_07,GEN_07_cat5_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_07, cchs2003_p::GENC_07, cchs2005_p::GENE_07, cchs2015_2016_p::GEN_020, cchs2017_2018_p:: GEN_020,cchs2001_i::GENA_07, cchs2003_i::GENC_07, cchs2005_i::GENE_07, cchs2015_2016_i::GEN_020, cchs2017_2018_i:: GEN_020, [GEN_07]",ICES confirmed,cat,NA::b,5,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Self-perceived life stress,Self-perceived life stress,,, +GEN_07,GEN_07_cat5_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_07, cchs2003_p::GENC_07, cchs2005_p::GENE_07, cchs2015_2016_p::GEN_020, cchs2017_2018_p:: GEN_020,cchs2001_i::GENA_07, cchs2003_i::GENC_07, cchs2005_i::GENE_07, cchs2015_2016_i::GEN_020, cchs2017_2018_i:: GEN_020, [GEN_07]",ICES confirmed,cat,NA::b,5,missing,missing,N/A,else,else,Self-perceived life stress,Self-perceived life stress,,, +GEN_10,GEN_10_cat4_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_10, cchs2003_p::GENC_10, cchs2005_p::GENE_10, cchs2015_2016_p::GEN_030, cchs2017_2018_p::GEN_030, cchs2001_i::GENA_01, cchs2003_i::GENC_01, cchs2005_i::GENE_01, cchs2015_2016_i::GEN_030, cchs2017_2018_i::GEN_030, [GEN_10]",ICES confirmed,cat,1,4,Very strong,Very strong,N/A,1,Very strong,Sense of belonging,Sense of belonging in the community,,, +GEN_10,GEN_10_cat4_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_10, cchs2003_p::GENC_10, cchs2005_p::GENE_10, cchs2015_2016_p::GEN_030, cchs2017_2018_p::GEN_030, cchs2001_i::GENA_01, cchs2003_i::GENC_01, cchs2005_i::GENE_01, cchs2015_2016_i::GEN_030, cchs2017_2018_i::GEN_030, [GEN_10]",ICES confirmed,cat,2,4,Somewhat strong,Somewhat strong,N/A,2,Somewhat strong,Sense of belonging,Sense of belonging in the community,,, +GEN_10,GEN_10_cat4_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_10, cchs2003_p::GENC_10, cchs2005_p::GENE_10, cchs2015_2016_p::GEN_030, cchs2017_2018_p::GEN_030, cchs2001_i::GENA_01, cchs2003_i::GENC_01, cchs2005_i::GENE_01, cchs2015_2016_i::GEN_030, cchs2017_2018_i::GEN_030, [GEN_10]",ICES confirmed,cat,3,4,Somewhat weak,Somewhat weak,N/A,3,Somewhat weak,Sense of belonging,Sense of belonging in the community,,, +GEN_10,GEN_10_cat4_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_10, cchs2003_p::GENC_10, cchs2005_p::GENE_10, cchs2015_2016_p::GEN_030, cchs2017_2018_p::GEN_030, cchs2001_i::GENA_01, cchs2003_i::GENC_01, cchs2005_i::GENE_01, cchs2015_2016_i::GEN_030, cchs2017_2018_i::GEN_030, [GEN_10]",ICES confirmed,cat,4,4,Very weak,Very weak,N/A,4,Very weak,Sense of belonging,Sense of belonging in the community,,, +GEN_10,GEN_10_cat4_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_10, cchs2003_p::GENC_10, cchs2005_p::GENE_10, cchs2015_2016_p::GEN_030, cchs2017_2018_p::GEN_030, cchs2001_i::GENA_01, cchs2003_i::GENC_01, cchs2005_i::GENE_01, cchs2015_2016_i::GEN_030, cchs2017_2018_i::GEN_030, [GEN_10]",ICES confirmed,cat,NA::a,4,not applicable,not applicable,N/A,6,not applicable,Sense of belonging,Sense of belonging in the community,,, +GEN_10,GEN_10_cat4_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_10, cchs2003_p::GENC_10, cchs2005_p::GENE_10, cchs2015_2016_p::GEN_030, cchs2017_2018_p::GEN_030, cchs2001_i::GENA_01, cchs2003_i::GENC_01, cchs2005_i::GENE_01, cchs2015_2016_i::GEN_030, cchs2017_2018_i::GEN_030, [GEN_10]",ICES confirmed,cat,NA::b,4,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Sense of belonging,Sense of belonging in the community,,, +GEN_10,GEN_10_cat4_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_10, cchs2003_p::GENC_10, cchs2005_p::GENE_10, cchs2015_2016_p::GEN_030, cchs2017_2018_p::GEN_030, cchs2001_i::GENA_01, cchs2003_i::GENC_01, cchs2005_i::GENE_01, cchs2015_2016_i::GEN_030, cchs2017_2018_i::GEN_030, [GEN_10]",ICES confirmed,cat,NA::b,4,missing,missing,N/A,else,else,Sense of belonging,Sense of belonging in the community,,, +HUIGHER,HUIGHER_cat3_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2001_i","cchs2001_p::HUIAGHER, cchs2003_p::HUICGHER, cchs2005_p::HUIEGHER, cchs2015_2016_p::HUIDGHER, cchs2001_i::HUIAGHER, [HUIGHER]",,cat,1,3,No hearing prob,No hearing problem,N/A,1,No hearing prob,HUI Hearing,"Hearing problems - function code (D, G)",,, +HUIGHER,HUIGHER_cat3_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2001_i","cchs2001_p::HUIAGHER, cchs2003_p::HUICGHER, cchs2005_p::HUIEGHER, cchs2015_2016_p::HUIDGHER, cchs2001_i::HUIAGHER, [HUIGHER]",,cat,2,3,Hear corrected,Hearing corrected,N/A,2,Hear corrected,HUI Hearing,"Hearing problems - function code (D, G)",,, +HUIGHER,HUIGHER_cat3_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2001_i","cchs2001_p::HUIAGHER, cchs2003_p::HUICGHER, cchs2005_p::HUIEGHER, cchs2015_2016_p::HUIDGHER, cchs2001_i::HUIAGHER, [HUIGHER]",,cat,3,3,Hear n-corrected,Hearing not-corrected,N/A,3,Hear n-corrected,HUI Hearing,"Hearing problems - function code (D, G)",,, +HUIGHER,HUIGHER_cat3_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2001_i","cchs2001_p::HUIAGHER, cchs2003_p::HUICGHER, cchs2005_p::HUIEGHER, cchs2015_2016_p::HUIDGHER, cchs2001_i::HUIAGHER, [HUIGHER]",,cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,HUI Hearing,"Hearing problems - function code (D, G)",,, +HUIGHER,HUIGHER_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2001_i","cchs2001_p::HUIAGHER, cchs2003_p::HUICGHER, cchs2005_p::HUIEGHER, cchs2015_2016_p::HUIDGHER, cchs2001_i::HUIAGHER, [HUIGHER]",,cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),HUI Hearing,"Hearing problems - function code (D, G)",CCHS 2001 does not include don't know (7) or refusal (8),, +HUIGHER,HUIGHER_cat3_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2001_i","cchs2001_p::HUIAGHER, cchs2003_p::HUICGHER, cchs2005_p::HUIEGHER, cchs2015_2016_p::HUIDGHER, cchs2001_i::HUIAGHER, [HUIGHER]",,cat,NA::b,3,missing,missing,N/A,else,else,HUI Hearing,"Hearing problems - function code (D, G)",,, +HUIGHER,HUIGHER_cat3_1,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2009_2010_i, cchs2013_2014_i",[HUIDHER],,cat,1,3,No hearing prob,No hearing problem,N/A,1,No hearing prob,HUI Hearing,"Hearing problems - function code (D, G)",Shared files use hearing health status with more detailed categories. See derived variable documentation.,, +HUIGHER,HUIGHER_cat3_2,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2009_2010_i, cchs2013_2014_i",[HUIDHER],,cat,2,3,Hear corrected,Hearing corrected,N/A,"[2,3]",Hear corrected,HUI Hearing,"Hearing problems - function code (D, G)",,, +HUIGHER,HUIGHER_cat3_3,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2009_2010_i, cchs2013_2014_i",[HUIDHER],,cat,3,3,Hear n-corrected,Hearing not-corrected,N/A,"[4,6]",Hear n-corrected,HUI Hearing,"Hearing problems - function code (D, G)",,, +HUIGHER,HUIGHER_cat3_NA::a,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2009_2010_i, cchs2013_2014_i",[HUIDHER],,cat,NA::a,3,not applicable,not applicable,N/A,96,not applicable,HUI Hearing,"Hearing problems - function code (D, G)",,, +HUIGHER,HUIGHER_cat3_NA::b,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2009_2010_i, cchs2013_2014_i",[HUIDHER],,cat,NA::b,3,missing,missing,N/A,"[97,99]",don't know (97); refusal (98); not stated (99),HUI Hearing,"Hearing problems - function code (D, G)",,, +HUIGHER,HUIGHER_cat3_NA::b,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2009_2010_i, cchs2013_2014_i",[HUIDHER],,cat,NA::b,3,missing,missing,N/A,else,else,HUI Hearing,"Hearing problems - function code (D, G)",,, +HUI06,HUI06_cat2_1,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_06, cchs2003_i::HUAC_06, [HUI_06]",ICES specific,cat,1,2,Able to hear in a group w/o hearing aid,Able to hear in a group without a hearing aid,N/A,1,Able to hear in a group with a hearing aid,HUI Hearing,Hearing ability - in a group without a hearing aid,,, +HUI06,HUI06_cat2_2,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_06, cchs2003_i::HUAC_06, [HUI_06]",ICES specific,cat,2,2,Unable to hear in a group w/o hearing aid,Unable to hear in a group without a hearing aid,N/A,2,Unable to hear in a group with a hearing aid,HUI Hearing,Hearing ability - in a group without a hearing aid,,, +HUI06,HUI06_cat2_NA::a,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_06, cchs2003_i::HUAC_06, [HUI_06]",ICES specific,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,HUI Hearing,Hearing ability - in a group without a hearing aid,,, +HUI06,HUI06_cat2_NA::a,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_06, cchs2003_i::HUAC_06, [HUI_06]",ICES specific,cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),HUI Hearing,Hearing ability - in a group without a hearing aid,,, +HUI06,HUI06_cat2_NA::b,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_06, cchs2003_i::HUAC_06, [HUI_06]",ICES specific,cat,NA::b,2,missing,missing,N/A,else,else,HUI Hearing,Hearing ability - in a group without a hearing aid,,, +HUI07,HUI07_cat2_1,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_07, cchs2003_i::HUIC_07, [HUI_07]",ICES specific,cat,1,2,Able to hear in a group w/ hearing aid,Able to hear in a group with hearing aid,N/A,1,Able to hear in a group with a hearing aid,HUI Hearing,Hearing ability - in a group with a hearing aid,,, +HUI07,HUI07_cat2_2,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_07, cchs2003_i::HUIC_07, [HUI_07]",ICES specific,cat,2,2,Unable to hear in a group w/ hearing aid,Unable to hear in a group with hearing aid,N/A,2,Unable to hear in a group with a hearing aid,HUI Hearing,Hearing ability - in a group with a hearing aid,,, +HUI07,HUI07_cat2_NA::a,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_07, cchs2003_i::HUIC_07, [HUI_07]",ICES specific,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,HUI Hearing,Hearing ability - in a group with a hearing aid,,, +HUI07,HUI07_cat2_NA::a,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_07, cchs2003_i::HUIC_07, [HUI_07]",ICES specific,cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),HUI Hearing,Hearing ability - in a group with a hearing aid,,, +HUI07,HUI07_cat2_NA::b,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_07, cchs2003_i::HUIC_07, [HUI_07]",ICES specific,cat,NA::b,2,missing,missing,N/A,else,else,HUI Hearing,Hearing ability - in a group with a hearing aid,,, +HUI07A,HUI07_cat2_1,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i, cchs_2017_2018_i","cchs2001_i::HUIA_07A, cchs2003_i::HUIC_07A, cchs2017_2018_i::WDM_101, [HUI_07A]",ICES specific,cat,1,2,Yes,Yes,N/A,1,Able to hear,HUI Hearing,Hearing ability - Able to hear,,, +HUI07A,HUI07_cat2_2,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i, cchs_2017_2018_i","cchs2001_i::HUIA_07A, cchs2003_i::HUIC_07A, cchs2017_2018_i::WDM_101, [HUI_07A]",ICES specific,cat,2,2,No,No,N/A,2,Unable to hear,HUI Hearing,Hearing ability - Able to hear,,, +HUI07A,HUI07_cat2_NA::a,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i, cchs_2017_2018_i","cchs2001_i::HUIA_07A, cchs2003_i::HUIC_07A, cchs2017_2018_i::WDM_101, [HUI_07A]",ICES specific,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,HUI Hearing,Hearing ability - Able to hear,,, +HUI07A,HUI07_cat2_NA::a,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i, cchs_2017_2018_i","cchs2001_i::HUIA_07A, cchs2003_i::HUIC_07A, cchs2017_2018_i::WDM_101, [HUI_07A]",ICES specific,cat,NA::a,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),HUI Hearing,Hearing ability - Able to hear,,, +HUI07A,HUI07_cat2_NA::b,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i, cchs_2017_2018_i","cchs2001_i::HUIA_07A, cchs2003_i::HUIC_07A, cchs2017_2018_i::WDM_101, [HUI_07A]",ICES specific,cat,NA::b,2,missing,missing,N/A,else,else,HUI Hearing,Hearing ability - Able to hear,,, +HUI08,HUI08_cat2_1,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_08, cchs2003_i::HUIC_08, [HUI_08]",ICES specific,cat,1,2,Yes,Yes,N/A,1,Able to hear in quiet room without a hearing aid,HUI Hearing ,Hearing ability - Able to hear in quiet room without hearing aid ,,, +HUI08,HUI08_cat2_2,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_08, cchs2003_i::HUIC_08, [HUI_08]",ICES specific,cat,2,2,No ,No,N/A,2,Unable to hear in quiet room without a hearing aid,HUI Hearing ,Hearing ability - Able to hear in quiet room without hearing aid ,,, +HUI08,HUI08_cat2_NA::a,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_08, cchs2003_i::HUIC_08, [HUI_08]",ICES specific,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,HUI Hearing ,Hearing ability - Able to hear in quiet room without hearing aid ,,, +HUI08,HUI08_cat2_NA::a,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_08, cchs2003_i::HUIC_08, [HUI_08]",ICES specific,cat,NA::a,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),HUI Hearing ,Hearing ability - Able to hear in quiet room without hearing aid ,,, +HUI08,HUI08_cat2_NA::b,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_08, cchs2003_i::HUIC_08, [HUI_08]",ICES specific,cat,NA::b,2,missing,missing,N/A,else,else,HUI Hearing ,Hearing ability - Able to hear in quiet room without hearing aid ,,, +HUI09,HUI09_cat2_1,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_09, cchs2003_i::HUIC_09, [HUI_09]",ICES specific,cat,1,2,Yes,Yes,N/A,1,Able to hear in quiet room with a hearing aid,HUI Hearing ,Hearing ability - Able to hear in quiet room with hearing aid,,, +HUI09,HUI09_cat2_2,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_08, cchs2003_i::HUIC_08, [HUI_08]",ICES specific,cat,2,2,No ,No ,N/A,2,Unable to hear in quiet room with a hearing aid ,HUI Hearing ,Hearing ability - Able to hear in quiet room with hearing aid,,, +HUI09,HUI09_cat2_NA::a,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_08, cchs2003_i::HUIC_08, [HUI_08]",ICES specific,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,HUI Hearing ,Hearing ability - Able to hear in quiet room with hearing aid,,, +HUI09,HUI09_cat2_NA::a,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_08, cchs2003_i::HUIC_08, [HUI_08]",ICES specific,cat,NA::a,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),HUI Hearing ,Hearing ability - Able to hear in quiet room with hearing aid,,, +HUI09,HUI09_cat2_NA::b,cat,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_08, cchs2003_i::HUIC_08, [HUI_08]",ICES specific,cat,NA::b,2,missing,missing,N/A,else,else,HUI Hearing ,Hearing ability - Able to hear in quiet room with hearing aid,,, +HWTGBMI,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::HWTAGBMI, cchs2003_p::HWTCGBMI, cchs2005_p::HWTEGBMI, cchs2015_2016_p::HWTDGBMI, cchs2017_2018_p::HWTDGBMI, cchs2009_s::HWTDBMI, cchs2010_s::HWTDBMI, cchs2012_s::HWTDBMI, cchs2001_i::HWTAGBMI, [HWTGBMI]",ICES confirmed,cont,copy,N/A,BMI,Body Mass Index,kg/m2,"[8.07,137.46]","BMI / self-report - (D,G)",BMI,"BMI / self-report - (D,G)","CCHS 2001 restricts BMI to ages 20-64. CCHS 2015-2016 uses adjusted BMI. Consider using using HWTGBMI_der for the most concistent BMI variable across all CCHS cycles. See documentation for BMI_fun() in derived variables for more details, or type ?BMI_fun in the console.",, +HWTGBMI,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::HWTAGBMI, cchs2003_p::HWTCGBMI, cchs2005_p::HWTEGBMI, cchs2015_2016_p::HWTDGBMI, cchs2017_2018_p::HWTDGBMI, cchs2009_s::HWTDBMI, cchs2010_s::HWTDBMI, cchs2012_s::HWTDBMI, cchs2001_i::HWTAGBMI, cchs2015_2016_i::HWTGVBMI, [HWTGBMI]",ICES confirmed,cont,NA::a,N/A,not applicable,not applicable,kg/m2,999.6,Not applicable,BMI,"BMI / self-report - (D,G)","CCHS 2001 and 2003 codes not applicable and missing variables as 999.6 and 999.7-999.9 respectively, while CCHS 2005 onwards codes not applicable and missing variables as 999.96 and 999.7-999.99 respectively",, +HWTGBMI,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::HWTAGBMI, cchs2003_p::HWTCGBMI, cchs2005_p::HWTEGBMI, cchs2015_2016_p::HWTDGBMI, cchs2017_2018_p::HWTDGBMI, cchs2009_s::HWTDBMI, cchs2010_s::HWTDBMI, cchs2012_s::HWTDBMI, cchs2001_i::HWTAGBMI, cchs2015_2016_i::HWTGVBMI, [HWTGBMI]",ICES confirmed,cont,NA::b,N/A,missing,missing,kg/m2,"[999.7,999.9]",don't know (999.7); refusal (999.8); not stated (999.9),BMI,"BMI / self-report - (D,G)",Don't know (999.7) and refusal (999.8) not included in 2001 CCHS,, +HWTGBMI,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::HWTAGBMI, cchs2003_p::HWTCGBMI, cchs2005_p::HWTEGBMI, cchs2015_2016_p::HWTDGBMI, cchs2017_2018_p::HWTDGBMI, cchs2009_s::HWTDBMI, cchs2010_s::HWTDBMI, cchs2012_s::HWTDBMI, cchs2001_i::HWTAGBMI, cchs2015_2016_i::HWTGVBMI, [HWTGBMI]",ICES confirmed,cont,NA::a,N/A,not applicable,not applicable,kg/m2,999.96,Not applicable,BMI,"BMI / self-report - (D,G)",,, +HWTGBMI,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::HWTAGBMI, cchs2003_p::HWTCGBMI, cchs2005_p::HWTEGBMI, cchs2015_2016_p::HWTDGBMI, cchs2017_2018_p::HWTDGBMI, cchs2009_s::HWTDBMI, cchs2010_s::HWTDBMI, cchs2012_s::HWTDBMI, cchs2001_i::HWTAGBMI, cchs2015_2016_i::HWTGVBMI, [HWTGBMI]",ICES confirmed,cont,NA::b,N/A,missing,missing,kg/m2,"[999.97,999.99]",don't know (999.97); refusal (999.98); not stated (999.99),BMI,"BMI / self-report - (D,G)",,, +HWTGBMI,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::HWTAGBMI, cchs2003_p::HWTCGBMI, cchs2005_p::HWTEGBMI, cchs2015_2016_p::HWTDGBMI, cchs2017_2018_p::HWTDGBMI, cchs2009_s::HWTDBMI, cchs2010_s::HWTDBMI, cchs2012_s::HWTDBMI, cchs2001_i::HWTAGBMI, cchs2015_2016_i::HWTGVBMI, [HWTGBMI]",ICES confirmed,cont,NA::b,N/A,missing,missing,kg/m2,else,else,BMI,"BMI / self-report - (D,G)",,, +HWTDBMI,N/A,cont,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::HWTADBMI, cchs2003_i::HWTCDBMI, cchs2005_i::HWTEDBMI, cchs2015_2016_i::HWTDVBMI, cchs2017_2018_i::HWTDVBMI, [HWTDBMI]",ICES specific,cont,copy,N/A,BMI,Body Mass Index,kg/m3,"[8.07, 137.46]",BMI / self-report - (D),BMI,BMI / self-report - (D),,, +HWTDBMI,N/A,cont,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::HWTCDBMI, cchs2005_i::HWTEDBMI, cchs2017_2018_i::HWTDVBMI, [HWTDBMI]",ICES specific,cont,NA::a,N/A,not applicable,not applicable,kg/m4,999.6,Not applicable,BMI,BMI / self-report - (D),,, +HWTDBMI,N/A,cont,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::HWTCDBMI, cchs2005_i::HWTEDBMI, cchs2017_2018_i::HWTDVBMI, [HWTDBMI]",ICES specific,cont,NA::b,N/A,missing,missing,kg/m5,"[999.7,999.9]",don't know (999.7); refusal (999.8); not stated (999.9),BMI,BMI / self-report - (D),,, +HWTDBMI,N/A,cont,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::HWTCDBMI, cchs2005_i::HWTEDBMI, cchs2017_2018_i::HWTDVBMI, [HWTDBMI]",ICES specific,cont,NA::a,N/A,not applicable,not applicable,kg/m6,999.96,Not applicable,BMI,BMI / self-report - (D),,, +HWTDBMI,N/A,cont,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::HWTCDBMI, cchs2005_i::HWTEDBMI, cchs2017_2018_i::HWTDVBMI, [HWTDBMI]",ICES specific,cont,NA::b,N/A,missing,missing,kg/m7,"[999.97,999.99]",don't know (999.97); refusal (999.98); not stated (999.99),BMI,BMI / self-report - (D),,, +HWTDBMI,N/A,cont,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::HWTCDBMI, cchs2005_i::HWTEDBMI, cchs2017_2018_i::HWTDVBMI, [HWTDBMI]",ICES specific,cont,NA::b,N/A,missing,missing,kg/m8,else,else,BMI,BMI / self-report - (D),,, +HWTGBMI_der,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s","DerivedVar::[HWTGHTM, HWTGWTK]",,N/A,Func::bmi_fun,N/A,N/A,N/A,kg/m2,N/A,N/A,Derived BMI,Derived Body Mass Index,"BMI variable derived from the harmonized height and weight variables. See documentation for BMI_fun() in derived variables for more details, or type ?BMI_fun in the console.",, +HWTGBMI_der,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s","DerivedVar::[HWTGHTM, HWTGWTK]",,N/A,NA::b,N/A,missing,missing,kg/m2,N/A,N/A,Derived BMI,Derived Body Mass Index,,, +HWTDBMI_der,N/A,cont,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","DerivedVar::[HWTDHTM, HWTDWTK]",,N/A,Func::bmi_fun_D,N/A,missing,missing,kg/m2,N/A,N/A,Derived BMI,Derived Body Mass Index,,, +HWTDBMI_der,N/A,cont,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","DerivedVar::[HWTDHTM, HWTDWTK]",,N/A,NA::b,N/A,missing,missing,kg/m2,N/A,N/A,Derived BMI,Derived Body Mass Index,,, +HWTGBMI_der_cat4,HWTGBMI_der_cat4N/A_Func::bmi_fun_cat,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s",DerivedVar::[HWTGBMI_der],,N/A,Func::bmi_fun_cat,N/A,N/A,N/A,kg/m2,N/A,N/A,Categorical BMI,Categorical body mass index,,, +HWTGBMI_der_cat4,HWTGBMI_der_cat4_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s",DerivedVar::[HWTGBMI_der],,N/A,1,4,Underweight,Underweight with BMI less than 18.5,kg/m2,1,Underweight,Categorical BMI,Categorical body mass index,,, +HWTGBMI_der_cat4,HWTGBMI_der_cat4_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s",DerivedVar::[HWTGBMI_der],,N/A,2,4,Normal weight,Normal weight with BMI between 18.5 and 25,kg/m2,2,Normal weight,Categorical BMI,Categorical body mass index,,, +HWTGBMI_der_cat4,HWTGBMI_der_cat4_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s",DerivedVar::[HWTGBMI_der],,N/A,3,4,Overweight,Overweight with BMI between 25 and 30,kg/m2,3,Overweight,Categorical BMI,Categorical body mass index,,, +HWTGBMI_der_cat4,HWTGBMI_der_cat4_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s",DerivedVar::[HWTGBMI_der],,N/A,4,4,Obese,Obese with BMI greater than 30,kg/m2,4,Obese,Categorical BMI,Categorical body mass index,,, +HWTGBMI_der_cat4,HWTGBMI_der_cat4_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s",DerivedVar::[HWTGBMI_der],,N/A,NA::a,4,not applicable,not applicable,kg/m2,NA::a,not applicable,Categorical BMI,Categorical body mass index,,, +HWTGBMI_der_cat4,HWTGBMI_der_cat4_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s",DerivedVar::[HWTGBMI_der],,N/A,NA::b,4,missing,missing,kg/m2,NA::b,missing,Categorical BMI,Categorical body mass index,,, +HWTDBMI_der_cat4,HWTDBMI_der_cat4N/A_Func::bmi_fun_cat_D,cat,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i",DerivedVar::HWTDBMI_der_cat4,,N/A,Func::bmi_fun_cat_D,N/A,N/A,N/A,kg/m2,N/A,N/A,Categorical BMI,Categorical body mass index,,, +HWTDBMI_der_cat4,HWTDBMI_der_cat4N/A_Func::bmi_fun_cat_D,cat,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i",DerivedVar::HWTDBMI_der_cat4,,N/A,1,4,Underweight,Underweight with BMI less than 18.5,kg/m2,1,Underweight,Categorical BMI,Categorical body mass index,,, +HWTDBMI_der_cat4,HWTDBMI_der_cat4N/A_Func::bmi_fun_cat_D,cat,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i",DerivedVar::HWTDBMI_der_cat4,,N/A,2,4,Normal weight,Normal weight with BMI between 18.5 and 25,kg/m2,2,Normal weight,Categorical BMI,Categorical body mass index,,, +HWTDBMI_der_cat4,HWTDBMI_der_cat4N/A_Func::bmi_fun_cat_D,cat,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i",DerivedVar::HWTDBMI_der_cat4,,N/A,3,4,Overweight,Overweight with BMI between 25 and 30,kg/m2,3,Overweight,Categorical BMI,Categorical body mass index,,, +HWTDBMI_der_cat4,HWTDBMI_der_cat4N/A_Func::bmi_fun_cat_D,cat,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i",DerivedVar::HWTDBMI_der_cat4,,N/A,4,4,Obese,Obese with BMI greater than 30,kg/m2,4,Obese,Categorical BMI,Categorical body mass index,,, +HWTDBMI_der_cat4,HWTDBMI_der_cat4N/A_Func::bmi_fun_cat_D,cat,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i",DerivedVar::HWTDBMI_der_cat4,,N/A,NA::a,4,not applicable,not applicable,kg/m2,NA::a,not applicable,Categorical BMI,Categorical body mass index,,, +HWTDBMI_der_cat4,HWTDBMI_der_cat4N/A_Func::bmi_fun_cat_D,cat,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i",DerivedVar::HWTDBMI_der_cat4,,N/A,NA::b,4,missing,missing,kg/m2,NA::b,missing,Categorical BMI,Categorical body mass index,,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.118,N/A,Height,converted height (3'8 IN - 44 inches),meters,1,3'8 IN - 44 inches,Height,"Height (metres)/self-reported - (D,G)","2001 and 2003 CCHS use inches, values converted to meters to 3 decimal points",, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.143,N/A,Height,converted height (3'9 IN - 45 inches),meters,2,3'9 IN - 45 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.168,N/A,Height,converted height (3'10 IN - 46 inches),meters,3,3'10 IN - 46 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.194,N/A,Height,converted height (3'11 IN - 47 inches),meters,4,3'11 IN - 47 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.219,N/A,Height,converted height (4'0 IN - 48 inches),meters,5,4'0 IN - 48 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.245,N/A,Height,converted height (4'1 IN - 49 inches),meters,6,4'1 IN - 49 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.27,N/A,Height,converted height (4'2 IN - 50 inches),meters,7,4'2 IN - 50 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.295,N/A,Height,converted height (4'3 IN - 51 inches),meters,8,4'3 IN - 51 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.321,N/A,Height,converted height (4'4 IN - 52 inches),meters,9,4'4 IN - 52 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.346,N/A,Height,converted height (4'5 IN - 53 inches),meters,10,4'5 IN - 53 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.372,N/A,Height,converted height (4'6 IN - 54 inches),meters,11,4'6 IN - 54 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.397,N/A,Height,converted height (4'7 IN - 55 inches),meters,12,4'7 IN - 55 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.422,N/A,Height,converted height (4'8 IN - 56 inches),meters,13,4'8 IN - 56 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.448,N/A,Height,converted height (4'9 IN - 57 inches),meters,14,4'9 IN - 57 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.473,N/A,Height,converted height (4'10 IN - 58 inches),meters,15,4'10 IN - 58 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.499,N/A,Height,converted height (4'11 in - 59 inches),meters,16,4'11 in - 59 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.524,N/A,Height,converted height (5'0 IN - 60 inches),meters,17,5'0 IN - 60 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.549,N/A,Height,converted height (5'1 IN - 61 inches),meters,18,5'1 IN - 61 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.575,N/A,Height,converted height (5'2 IN - 62 inches),meters,19,5'2 IN - 62 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.6,N/A,Height,converted height (5'3 IN - 63 inches),meters,20,5'3 IN - 63 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.626,N/A,Height,converted height (5'4 IN - 64 inches),meters,21,5'4 IN - 64 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.651,N/A,Height,converted height (5'5 IN - 65 inches),meters,22,5'5 IN - 65 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.676,N/A,Height,converted height (5'6 IN - 66 inches),meters,23,5'6 IN - 66 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.702,N/A,Height,converted height (5'7 IN - 67 inches),meters,24,5'7 IN - 67 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.727,N/A,Height,converted height (5'8 IN - 68 inches),meters,25,5'8 IN - 68 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.753,N/A,Height,converted height (5'9 IN - 69 inches),meters,26,5'9 IN - 69 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.778,N/A,Height,converted height (5'10 IN - 70 inches),meters,27,5'10 IN - 70 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.803,N/A,Height,converted height (5'11 IN - 71 inches),meters,28,5'11 IN - 71 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.829,N/A,Height,converted height (6'0 IN - 72 inches),meters,29,6'0 IN - 72 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.854,N/A,Height,converted height (6'1 IN - 73 inches),meters,30,6'1 IN - 73 inches,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,1.93,N/A,Height,converted height (6'2 IN+ - 74+ inches),meters,31,6'2 IN+ - 74+ inches,Height,"Height (metres)/self-reported - (D,G)",74+ inches converted to 76 inches,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,NA::a,N/A,not applicable,not applicable,meters,96,not applicable,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,NA::b,N/A,missing,missing,meters,99,not stated (99),Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::HWTAGHT, cchs2003_p::HWTCGHT",,cat,NA::b,N/A,missing,missing,meters,else,else,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s","cchs2005_p::HWTEGHTM, cchs2015_2016_p::HWTDGHTM, cchs2017_2018_p::HWTDGHTM, cchs2009_s::HWTDHTM, cchs2010_s::HWTDHTM, cchs2012_s::HWTDHTM, [HWTGHTM]",,cont,copy,N/A,Height,Height,meters,"[0.914,2.134]",Height,Height,"Height (metres)/self-reported - (D,G)",Height is a reported in meters from 2005 CCHS onwards,, +HWTGHTM,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s","cchs2005_p::HWTEGHTM, cchs2015_2016_p::HWTDGHTM, cchs2017_2018_p::HWTDGHTM, cchs2009_s::HWTDHTM, cchs2010_s::HWTDHTM, cchs2012_s::HWTDHTM, [HWTGHTM]",,cont,NA::a,N/A,not applicable,not applicable,meters,9.996,not applicable,Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s","cchs2005_p::HWTEGHTM, cchs2015_2016_p::HWTDGHTM, cchs2017_2018_p::HWTDGHTM, cchs2009_s::HWTDHTM, cchs2010_s::HWTDHTM, cchs2012_s::HWTDHTM, [HWTGHTM]",,cont,NA::b,N/A,missing,missing,meters,"[9.997,9.999]","don't know (9.997), refusal (9.998), not stated (9.999)",Height,"Height (metres)/self-reported - (D,G)",,, +HWTGHTM,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s","cchs2005_p::HWTEGHTM, cchs2015_2016_p::HWTDGHTM, cchs2017_2018_p::HWTDGHTM, cchs2009_s::HWTDHTM, cchs2010_s::HWTDHTM, cchs2012_s::HWTDHTM, [HWTGHTM]",,cont,NA::b,N/A,missing,missing,meters,else,else,Height,"Height (metres)/self-reported - (D,G)",,, +HWTDHTM,N/A,cont,cchs_2001_i,[HWTADHTM],ICES specific,cont,copy,N/A,Height,Height,meters,"[0.914, 2.134]",Height,Height,Height (metres)/self-reported - (D),,, +HWTDHTM,N/A,cont,cchs_2001_i,[HWTADHTM],ICES specific,cont,NA::a,N/A,Height,Height,meters,9.996,not applicable,Height,Height (metres)/self-reported - (D),,, +HWTDHTM,N/A,cont,cchs_2001_i,[HWTADHTM],ICES specific,cont,NA::b,N/A,Height,Height,meters,"[9.997,9.999]",don't know (9.997); refusal (9.998); not stated (9.999),Height,Height (metres)/self-reported - (D),,, +HWTDHTM,N/A,cont,cchs_2001_i,[HWTADHTM],ICES specific,cont,NA::b,N/A,Height,Height,meters,else,else,Height,Height (metres)/self-reported - (D),,, +HWTDHTM,N/A,cont,"cchs_2003_i, cchs_2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs_2003_i::HWTCDHTM, cchs_2005_i::HWTEDHTM, 2015_2016_i::HWTDVHTM, cchs2017_2018_i::HTWDVHTM, [HWTDHTM]",ICES specific,cont,copy,N/A,Height,Height,meters,"[0.914, 2.134]",Height,Height,Height (metres)/self-reported - (D),,, +HWTDHTM,N/A,cont,"cchs_2003_i, cchs_2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs_2003_i::HWTCDHTM, cchs_2005_i::HWTEDHTM, 2015_2016_i::HWTDVHTM, cchs2017_2018_i::HTWDVHTM, [HWTDHTM]",ICES specific,cont,NA::a,N/A,not applicable,not applicable,meters,9.996,not applicable,Height,Height (metres)/self-reported - (D),,, +HWTDHTM,N/A,cont,"cchs_2003_i, cchs_2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs_2003_i::HWTCDHTM, cchs_2005_i::HWTEDHTM, 2015_2016_i::HWTDVHTM, cchs2017_2018_i::HTWDVHTM, [HWTDHTM]",ICES specific,cont,NA::b,N/A,missing,missing,meters,"[9.997, 9.999]",don't know (9.997); refusal (9.998); not stated (9.999),Height,Height (metres)/self-reported - (D),,, +HWTDHTM,N/A,cont,"cchs_2003_i, cchs_2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs_2003_i::HWTCDHTM, cchs_2005_i::HWTEDHTM, 2015_2016_i::HWTDVHTM, cchs2017_2018_i::HTWDVHTM, [HWTDHTM]",ICES specific,cont,NA::b,N/A,missing,missing,meters,else,else,Height,Height (metres)/self-reported - (D),,, +HWTDWTK,N/A,cont,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, ccsh2015_2016_i, cchs2017_2018_i","cchs2001_i::HWTADWTK, cchs2003_i::HWTCDWTK, cchs2005_i::HWTEDWTK, cchs2015_2016_i::HWTDVWTK, cchs2017_2018_i::HWTDVWTK, [HWTDWTK]",ICES confirmed,cont,copy,N/A,Weight,Weight - kilograms,kg,***,"Weight - kilograms (D, G)",Weight,"Weight - kilograms (D, G)",,, +HWTDWTK,N/A,cont,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, ccsh2015_2016_i, cchs2017_2018_i","cchs2001_i::HWTADWTK, cchs2003_i::HWTCDWTK, cchs2005_i::HWTEDWTK, cchs2015_2016_i::HWTDVWTK, cchs2017_2018_i::HWTDVWTK, [HWTDWTK]",ICES confirmed,cont,NA::a,N/A,not applicable,not applicable,kg,999.96,not applicable,Weight,"Weight - kilograms (D, G)",,, +HWTDWTK,N/A,cont,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, ccsh2015_2016_i, cchs2017_2018_i","cchs2001_i::HWTADWTK, cchs2003_i::HWTCDWTK, cchs2005_i::HWTEDWTK, cchs2015_2016_i::HWTDVWTK, cchs2017_2018_i::HWTDVWTK, [HWTDWTK]",ICES confirmed,cont,NA::b,N/A,missing,missing,kg,"[999.97, 999.99]",don't know (999.97); refusal (999.98); not stated (999.99),Weight,"Weight - kilograms (D, G)",,, +HWTDWTK,N/A,cont,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, ccsh2015_2016_i, cchs2017_2018_i","cchs2001_i::HWTADWTK, cchs2003_i::HWTCDWTK, cchs2005_i::HWTEDWTK, cchs2015_2016_i::HWTDVWTK, cchs2017_2018_i::HWTDVWTK, [HWTDWTK]",ICES confirmed,cont,NA::b,N/A,missing,missing,kg,else,else,Weight,"Weight - kilograms (D, G)",,, +pack_years_cat,pack_years_catN/A_Func::pack_years_fun_cat,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s",DerivedVar::[pack_years_der],,N/A,Func::pack_years_fun_cat,N/A,N/A,N/A,pack-years,N/A,N/A,Categorical PackYears,Categorical smoking pack-years,,, +pack_years_cat,pack_years_cat_cat8_1,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s",DerivedVar::[pack_years_der],,N/A,1,8,0,0 pack-years,pack-years,N/A,0 pack-years,Categorical PackYears,Categorical smoking pack-years,,, +pack_years_cat,pack_years_cat_cat8_2,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s",DerivedVar::[pack_years_der],,N/A,2,8,0 to 0.01,0 to 0.01 pack-years,pack-years,N/A,0 to 0.01 pack-years,Categorical PackYears,Categorical smoking pack-years,,, +pack_years_cat,pack_years_cat_cat8_3,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s",DerivedVar::[pack_years_der],,N/A,3,8,0.01 to 3.0,0.01 to 3.0 pack-years,pack-years,N/A,0.01 to 3.0 pack-years,Categorical PackYears,Categorical smoking pack-years,,, +pack_years_cat,pack_years_cat_cat8_4,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s",DerivedVar::[pack_years_der],,N/A,4,8,3.0 to 9.0,3.0 to 9.0 pack-years,pack-years,N/A,3.0 to 9.0 pack-years,Categorical PackYears,Categorical smoking pack-years,,, +pack_years_cat,pack_years_cat_cat8_5,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s",DerivedVar::[pack_years_der],,N/A,5,8,9.0 to 16.2,9.0 to 16.2 pack-years,pack-years,N/A,9.0 to 16.2 pack-years,Categorical PackYears,Categorical smoking pack-years,,, +pack_years_cat,pack_years_cat_cat8_6,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s",DerivedVar::[pack_years_der],,N/A,6,8,16.2 to 25.7,16.2 to 25.7 pack-years,pack-years,N/A,16.2 to 25.7 pack-years,Categorical PackYears,Categorical smoking pack-years,,, +pack_years_cat,pack_years_cat_cat8_7,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s",DerivedVar::[pack_years_der],,N/A,7,8,25.7 to 40.0,25.7 to 40.0 pack-years,pack-years,N/A,25.7 to 40.0 pack-years,Categorical PackYears,Categorical smoking pack-years,,, +pack_years_cat,pack_years_cat_cat8_8,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s",DerivedVar::[pack_years_der],,N/A,8,8,40.0+,40.0+ pack-years,pack-years,N/A,40.0+ pack-years,Categorical PackYears,Categorical smoking pack-years,,, +pack_years_cat,pack_years_cat_cat8_NA::a,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s",DerivedVar::[pack_years_der],,N/A,NA::a,8,not applicable,not applicable,pack-years,N/A,not applicable,Categorical PackYears,Categorical smoking pack-years,,, +pack_years_cat,pack_years_cat_cat8_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s",DerivedVar::[pack_years_der],,N/A,NA::b,8,missing,missing,pack-years,N/A,missing,Categorical PackYears,Categorical smoking pack-years,,, +pack_years_der,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","DerivedVar::[SMKDSTY_A, DHHGAGE_cont, time_quit_smoking, SMKG203_cont, SMKG207_cont, SMK_204, SMK_05B, SMK_208, SMK_05C, SMKG01C_cont, SMK_01A]",,N/A,Func::pack_years_fun,N/A,N/A,N/A,pack-years,N/A,N/A,PackYears,Smoking pack-years,PackYears variable derived from various harmonized smoking variables,, +pack_years_der,N/A,cont,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","DerivedVar::[SMKDSTY_A, DHHGAGE_cont, time_quit_smoking, SMKG203_cont, SMKG207_cont, SMK_204, SMK_05B, SMK_208, SMK_05C, SMKG01C_cont, SMK_01A]",,N/A,NA::b,N/A,missing,missing,pack-years,N/A,N/A,PackYears,Smoking pack-years,,, +PACFLEI,PACFLEI_cat_cat6_1,cat,"cchs2001_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_i::PACAFLEI, cchs2005_i::PACEFLEI, [PACFLEI]",ICES specific,cat,1,2,Yes,Yes,Leisure physical activity,1,Yes,Leisure phys. activity,Leisure physical activity,,, +PACFLEI,PACFLEI_cat_cat6_2,cat,"cchs2001_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_i::PACAFLEI, cchs2005_i::PACEFLEI, [PACFLEI]",ICES specific,cat,2,2,No,No,Leisure physical activity,2,No,Leisure phys. activity,Leisure physical activity,,, +PACFLEI,PACFLEI_cat_cat6_NA::a,cat,"cchs2001_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_i::PACAFLEI, cchs2005_i::PACEFLEI, [PACFLEI]",ICES specific,cat,NA::a,2,not applicable,not applicable,Leisure physical activity,6,not applicable,Leisure phys. activity,Leisure physical activity,,, +PACFLEI,PACFLEI_cat_cat6_NA::b,cat,"cchs2001_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_i::PACAFLEI, cchs2005_i::PACEFLEI, [PACFLEI]",ICES specific,cat,NA::b,2,missing,missing,Leisure physical activity,"[7,9]",don't know (7); refusal (8); not stated (9) ,Leisure phys. activity,Leisure physical activity,,, +PACFLEI,PACFLEI_cat_cat6_NA::b,cat,"cchs2001_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_i::PACAFLEI, cchs2005_i::PACEFLEI, [PACFLEI]",ICES specific,cat,NA::b,2,missing,missing,Leisure physical activity,else,else,Leisure phys. activity,Leisure physical activity,,, +RAC_6D,RAC_6D_cat_cat1,cat,"cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_i::RACA_6D, cchs2003_i::RACC_6D, cchs2005_i::RACE_6D",ICES specific,cat,1,2,Yes,Yes,N/A,1,Yes,Help heavy housework,Needs help - heavy housework,,, +RAC_6D,RAC_6D_cat_cat2,cat,"cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_i::RACA_6D, cchs2003_i::RACC_6D, cchs2005_i::RACE_6D",ICES specific,cat,2,2,No,No,N/A,2,No,Help heavy housework,Needs help - heavy housework,,, +RAC_6D,RAC_6D_cat_NA::a,cat,"cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_i::RACA_6D, cchs2003_i::RACC_6D, cchs2005_i::RACE_6D",ICES specific,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Help heavy housework,Needs help - heavy housework,,, +RAC_6D,RAC_6D_cat_NA::b,cat,"cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_i::RACA_6D, cchs2003_i::RACC_6D, cchs2005_i::RACE_6D",ICES specific,cat,NA::b,2,missing,missing,N/A,"[7,9]",don’t know (7); refusal (8); not stated (9),Help heavy housework,Needs help - heavy housework,,, +RAC_6D,RAC_6D_cat_NA::b,cat,"cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_i::RACA_6D, cchs2003_i::RACC_6D, cchs2005_i::RACE_6D",ICES specific,cat,NA::b,2,missing,missing,N/A,else,else,Help heavy housework,Needs help - heavy housework,,, +SDCFIMM,SDCFIMM_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SDCAFIMM, cchs2003_p::SDCCFIMM, cchs2005_p::SDCEFIMM, cchs2015_2016_p::SDCDVIMM, cchs2017_2018_p::SDCDVIMM, cchs2001_i::SDCAFIMM, cchs2003_i::SDCCFIMM, cchs2005_i::SDCEFIMM, cchs2015_2016::SDCDVIMM, cchs2017_2018_i::SDCDVIMM, [SDCFIMM]",ICES confirmed,cat,1,2,Yes,Yes,N/A,1,Yes,Immigrant status,Immigrant Status (D),,, +SDCFIMM,SDCFIMM_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016, cchs2017_2019","cchs2001_p::SDCAFIMM, cchs2003_p::SDCCFIMM, cchs2005_p::SDCEFIMM, cchs2015_2016_p::SDCDVIMM, cchs2017_2018_p::SDCDVIMM, cchs2001_i::SDCAFIMM, cchs2003_i::SDCCFIMM, cchs2005_i::SDCEFIMM, cchs2015_2016::SDCDVIMM, cchs2017_2018_i::SDCDVIMM, [SDCFIMM]",ICES confirmed,cat,2,2,No,No,N/A,2,No,Immigrant status,Immigrant Status (D),,, +SDCFIMM,SDCFIMM_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016, cchs2017_2020","cchs2001_p::SDCAFIMM, cchs2003_p::SDCCFIMM, cchs2005_p::SDCEFIMM, cchs2015_2016_p::SDCDVIMM, cchs2017_2018_p::SDCDVIMM, cchs2001_i::SDCAFIMM, cchs2003_i::SDCCFIMM, cchs2005_i::SDCEFIMM, cchs2015_2016::SDCDVIMM, cchs2017_2018_i::SDCDVIMM, [SDCFIMM]",ICES confirmed,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Immigrant status,Immigrant Status (D),,, +SDCFIMM,SDCFIMM_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016, cchs2017_2021","cchs2001_p::SDCAFIMM, cchs2003_p::SDCCFIMM, cchs2005_p::SDCEFIMM, cchs2015_2016_p::SDCDVIMM, cchs2017_2018_p::SDCDVIMM, cchs2001_i::SDCAFIMM, cchs2003_i::SDCCFIMM, cchs2005_i::SDCEFIMM, cchs2015_2016::SDCDVIMM, cchs2017_2018_i::SDCDVIMM, [SDCFIMM]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Immigrant status,Immigrant Status (D),,, +SDCFIMM,SDCFIMM_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016, cchs2017_2022","cchs2001_p::SDCAFIMM, cchs2003_p::SDCCFIMM, cchs2005_p::SDCEFIMM, cchs2015_2016_p::SDCDVIMM, cchs2017_2018_p::SDCDVIMM, cchs2001_i::SDCAFIMM, cchs2003_i::SDCCFIMM, cchs2005_i::SDCEFIMM, cchs2015_2016::SDCDVIMM, cchs2017_2018_i::SDCDVIMM, [SDCFIMM]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,else,else,Immigrant status,Immigrant Status (D),,, +SDCGCGT,SDCGCGT_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2001_i, cchs2005_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SDCAGRAC, cchs2003_p::SDCCGRAC, cchs2005_p::SDCEGCGT, cchs2015_2016_p::SDCDGCGT, cchs2017_2018_p::SDCDGCGT, cchs2001_i::SDCAGRAC, cchs2003_i::SDCCDRAC, cchs_2005_i:: SDCEGCGT, cchs2015_2016_i::SDCDVCGT, cchs2017_2018_i::SDCDVCGT, [SDCGCGT]",ICES altered,cat,1,2,White,White,N/A,1,White,Ethnicity,"Cultural or racial origin - (D, G)",,, +SDCGCGT,SDCGCGT_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2001_i, cchs2005_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::SDCAGRAC, cchs2003_p::SDCCGRAC, cchs2005_p::SDCEGCGT, cchs2015_2016_p::SDCDGCGT, cchs2017_2018_p::SDCDGCGT, cchs2001_i::SDCAGRAC, cchs2003_i::SDCCDRAC, cchs_2005_i:: SDCEGCGT, cchs2015_2016_i::SDCDVCGT, cchs2017_2018_i::SDCDVCGT, [SDCGCGT]",ICES altered,cat,2,2,Non-white,Non-white,N/A,2,Visible minority,Ethnicity,"Cultural or racial origin - (D, G)",,, +SDCGCGT,SDCGCGT_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2001_i, cchs2005_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::SDCAGRAC, cchs2003_p::SDCCGRAC, cchs2005_p::SDCEGCGT, cchs2015_2016_p::SDCDGCGT, cchs2017_2018_p::SDCDGCGT, cchs2001_i::SDCAGRAC, cchs2003_i::SDCCDRAC, cchs_2005_i:: SDCEGCGT, cchs2015_2016_i::SDCDVCGT, cchs2017_2018_i::SDCDVCGT, [SDCGCGT]",ICES altered,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,Ethnicity,"Cultural or racial origin - (D, G)",,, +SDCGCGT,SDCGCGT_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2001_i, cchs2005_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::SDCAGRAC, cchs2003_p::SDCCGRAC, cchs2005_p::SDCEGCGT, cchs2015_2016_p::SDCDGCGT, cchs2017_2018_p::SDCDGCGT, cchs2001_i::SDCAGRAC, cchs2003_i::SDCCDRAC, cchs_2005_i:: SDCEGCGT, cchs2015_2016_i::SDCDVCGT, cchs2017_2018_i::SDCDVCGT, [SDCGCGT]",ICES altered,cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Ethnicity,"Cultural or racial origin - (D, G)","CCHS 2001 missing don't know (7), refusal (8)",, +SDCGCGT,SDCGCGT_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2001_i, cchs2005_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::SDCAGRAC, cchs2003_p::SDCCGRAC, cchs2005_p::SDCEGCGT, cchs2015_2016_p::SDCDGCGT, cchs2017_2018_p::SDCDGCGT, cchs2001_i::SDCAGRAC, cchs2003_i::SDCCDRAC, cchs_2005_i:: SDCEGCGT, cchs2015_2016_i::SDCDVCGT, cchs2017_2018_i::SDCDVCGT, [SDCGCGT]",ICES altered,cat,NA::b,2,missing,missing,N/A,else,else,Ethnicity,"Cultural or racial origin - (D, G)",,, +SDCDCGT_A,SDCDCGT_A_cat13_1,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, [SDCDCGT] ",ICES specific,cat,1,14,White,White,N/A,1,White,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_2,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, [SDCDCGT] ",ICES specific,cat,2,14,Black,Black,N/A,2,Black,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_3,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, [SDCDCGT] ",ICES specific,cat,3,14,Korean,Korean,N/A,3,Korean,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_4,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, [SDCDCGT] ",ICES specific,cat,4,14,Filipino,Filipino,N/A,4,Filipino,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_5,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, [SDCDCGT] ",ICES specific,cat,5,14,Japanese,Japanese,N/A,5,Japanese,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_6,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, [SDCDCGT] ",ICES specific,cat,6,14,Chinese,Chinese,N/A,6,Chinese,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_7,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, [SDCDCGT] ",ICES specific,cat,7,14,Aboriginal/N ame,Aboriginal/N ame,N/A,7,Aboriginal/N ame,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_8,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, [SDCDCGT] ",ICES specific,cat,8,14,South Asian,South Asian,N/A,8,South Asian,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_9,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, [SDCDCGT] ",ICES specific,cat,9,14,South East Asian,South East Asian,N/A,9,South East Asian,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_10,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, [SDCDCGT] ",ICES specific,cat,10,14,Arab,Arab,N/A,10,Arab,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_11,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, [SDCDCGT] ",ICES specific,cat,11,14,West Asian,West Asian,N/A,11,West Asian,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_12,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, [SDCDCGT] ",ICES specific,cat,12,14,Latin American,Latin American,N/A,12,Latin American,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_13,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, [SDCDCGT] ",ICES specific,cat,13,14,Other,Other,N/A,13,Other,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_13,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, [SDCDCGT] ",ICES specific,cat,14,14,Multiple origins,Multiple origins,N/A,14,Multiple origins,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_NA::a,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, [SDCDCGT] ",ICES specific,cat,NA::a,14,not applicable,not applicable,N/A,96,not applicable,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_NA::b,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, [SDCDCGT] ",ICES specific,cat,NA::b,14,missing,missing,N/A,"[97, 99]",don't know (97); refusal (98); not stated (99),Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_NA::b,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, [SDCDCGT] ",ICES specific,cat,NA::b,14,missing,missing,N/A,else,else,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_1,cat,"cchs2015_2016_i, cchs2017_2018_i",[SDCDVCGT],ICES specific,cat,1,13,White only,White only,N/A,1,White only,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_2,cat,"cchs2015_2016_i, cchs2017_2018_i",[SDCDVCGT],ICES specific,cat,2,13,South Asian only,South Asian only,N/A,8,South Asian only,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_3,cat,"cchs2015_2016_i, cchs2017_2018_i",[SDCDVCGT],ICES specific,cat,3,13,Chinese only,Chinese only,N/A,6,Chinese only,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_4,cat,"cchs2015_2016_i, cchs2017_2018_i",[SDCDVCGT],ICES specific,cat,4,13,Black only,Black only,N/A,2,Black only,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_5,cat,"cchs2015_2016_i, cchs2017_2018_i",[SDCDVCGT],ICES specific,cat,5,13,Filipino only,Filipino only,N/A,4,Filipino only,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_6,cat,"cchs2015_2016_i, cchs2017_2018_i",[SDCDVCGT],ICES specific,cat,6,13,Latin American only,Latin American only,N/A,12,Latin American only,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_7,cat,"cchs2015_2016_i, cchs2017_2018_i",[SDCDVCGT],ICES specific,cat,7,13,Arab only,Arab only,N/A,10,Arab only,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_8,cat,"cchs2015_2016_i, cchs2017_2018_i",[SDCDVCGT],ICES specific,cat,8,13,Southeastern Asian only,Southeastern Asian only,N/A,9,Southeastern Asian only,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_9,cat,"cchs2015_2016_i, cchs2017_2018_i",[SDCDVCGT],ICES specific,cat,9,13,West Asian only,West Asian only,N/A,11,West Asian only,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_10,cat,"cchs2015_2016_i, cchs2017_2018_i",[SDCDVCGT],ICES specific,cat,10,13,Korean only,Korean only,N/A,3,Korean only,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_11,cat,"cchs2015_2016_i, cchs2017_2018_i",[SDCDVCGT],ICES specific,cat,11,13,Japenese only,Japenese only,N/A,5,Japenese only,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_12,cat,"cchs2015_2016_i, cchs2017_2018_i",[SDCDVCGT],ICES specific,cat,12,13,Other racial or cultural origin (only),Other racial or cultural origin (only),N/A,13,Other racial or cultural origin (only),Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_13,cat,"cchs2015_2016_i, cchs2017_2018_i",[SDCDVCGT],ICES specific,cat,13,13,Multiple racial or cultural origins,Multiple racial or cultural origins,N/A,14,Multiple racial or cultural origins,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_NA::a,cat,"cchs2015_2016_i, cchs2017_2018_i",[SDCDVCGT],ICES specific,cat,NA::a,13,not applicable,not applicable,N/A,96,not applicable,Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_NA::b,cat,"cchs2015_2016_i, cchs2017_2018_i",[SDCDVCGT],ICES specific,cat,NA::b,13,missing,missing,N/A,"[97, 99]",don't know (97); refusal (98); not stated (99),Ethnicity,Cultural or racial origin,,, +SDCDCGT_A,SDCDCGT_A_cat13_NA::b,cat,"cchs2015_2016_i, cchs2017_2018_i",[SDCDVCGT],ICES specific,cat,NA::b,13,missing,missing,N/A,else,else,Ethnicity,Cultural or racial origin,,, +SDCDCGT_B,SDCDCGT_B_cat7_1,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, cchs2015_2016_i::SDCDVCGT, cchs2017_2018_i::SDCDVCGT, [SDCDCGT] ",ICES specific,cat,1,7,White,White,N/A,1,White,Ethnicity,Cultural or racial origin,,, +SDCDCGT_B,SDCDCGT_B_cat7_2,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, cchs2015_2016_i::SDCDVCGT, cchs2017_2018_i::SDCDVCGT, [SDCDCGT] ",ICES specific,cat,2,7,Black,Black,N/A,2,Black,Ethnicity,Cultural or racial origin,,, +SDCDCGT_B,SDCDCGT_B_cat7_3,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, cchs2015_2016_i::SDCDVCGT, cchs2017_2018_i::SDCDVCGT, [SDCDCGT] ",ICES specific,cat,3,7,Chinese,Chinese,N/A,6,Chinese,Ethnicity,Cultural or racial origin,,, +SDCDCGT_B,SDCDCGT_B_cat7_4,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, cchs2015_2016_i::SDCDVCGT, cchs2017_2018_i::SDCDVCGT, [SDCDCGT] ",ICES specific,cat,4,7,Aboriginal,Aboriginal,N/A,7,Aboriginal,Ethnicity,Cultural or racial origin,,, +SDCDCGT_B,SDCDCGT_B_cat7_5,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, cchs2015_2016_i::SDCDVCGT, cchs2017_2018_i::SDCDVCGT, [SDCDCGT] ",ICES specific,cat,5,7,Japanese/Korean/South East Asian/Filipino,Japanese/Korean/South East Asian/Filipino,N/A,[3],Japanese/Korean/South East Asian/Filipino,Ethnicity,Cultural or racial origin,,, +SDCDCGT_B,SDCDCGT_B_cat7_5,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, cchs2015_2016_i::SDCDVCGT, cchs2017_2018_i::SDCDVCGT, [SDCDCGT] ",ICES specific,cat,5,7,Japanese/Korean/South East Asian/Filipino,Japanese/Korean/South East Asian/Filipino,N/A,[5],Japanese/Korean/South East Asian/Filipino,Ethnicity,Cultural or racial origin,,, +SDCDCGT_B,SDCDCGT_B_cat7_5,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, cchs2015_2016_i::SDCDVCGT, cchs2017_2018_i::SDCDVCGT, [SDCDCGT] ",ICES specific,cat,5,7,Japanese/Korean/South East Asian/Filipino,Japanese/Korean/South East Asian/Filipino,N/A,[9],Japanese/Korean/South East Asian/Filipino,Ethnicity,Cultural or racial origin,,, +SDCDCGT_B,SDCDCGT_B_cat7_6,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, cchs2015_2016_i::SDCDVCGT, cchs2017_2018_i::SDCDVCGT, [SDCDCGT] ",ICES specific,cat,6,7,other/multiple origin/unknown/Latin American,other/multiple origin/unknown/Latin American,N/A,[12],other/multiple origin/unknown/Latin American,Ethnicity,Cultural or racial origin,,, +SDCDCGT_B,SDCDCGT_B_cat7_6,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, cchs2015_2016_i::SDCDVCGT, cchs2017_2018_i::SDCDVCGT, [SDCDCGT] ",ICES specific,cat,6,7,other/multiple origin/unknown/Latin American,other/multiple origin/unknown/Latin American,N/A,[14],other/multiple origin/unknown/Latin American,Ethnicity,Cultural or racial origin,,, +SDCDCGT_B,SDCDCGT_B_cat7_7,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, cchs2015_2016_i::SDCDVCGT, cchs2017_2018_i::SDCDVCGT, [SDCDCGT] ",ICES specific,cat,7,7,South Asian/Arab/West Asian,South Asian/Arab/West Asian,N/A,[8],South Asian/Arab/West Asian,Ethnicity,Cultural or racial origin,,, +SDCDCGT_B,SDCDCGT_B_cat7_7,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, cchs2015_2016_i::SDCDVCGT, cchs2017_2018_i::SDCDVCGT, [SDCDCGT] ",ICES specific,cat,7,7,South Asian/Arab/West Asian,South Asian/Arab/West Asian,N/A,"[10,11]",South Asian/Arab/West Asian,Ethnicity,Cultural or racial origin,,, +SDCDCGT_B,SDCDCGT_B_cat7_NA::a,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, cchs2015_2016_i::SDCDVCGT, cchs2017_2018_i::SDCDVCGT, [SDCDCGT] ",ICES specific,cat,NA::a,7,not applicable,not applicable,N/A,96,not applicable,Ethnicity,Cultural or racial origin,,, +SDCDCGT_B,SDCDCGT_B_cat7_NA::b,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, cchs2015_2016_i::SDCDVCGT, cchs2017_2018_i::SDCDVCGT, [SDCDCGT] ",ICES specific,cat,NA::b,7,missing,missing,N/A,"[97,99]",missing,Ethnicity,Cultural or racial origin,,, +SDCDCGT_B,SDCDCGT_B_cat7_NA::b,cat,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, cchs2015_2016_i::SDCDVCGT, cchs2017_2018_i::SDCDVCGT, [SDCDCGT] ",ICES specific,cat,NA::b,7,missing,missing,N/A,else,else,Ethnicity,Cultural or racial origin,,, +SLP_02,SLP_02_cat5_1,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2012_s, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2015_2016_p::SLP_010, cchs2017_2018_p::SLP_010, cchs2015_2016_i::SLP_010, [SLP_02]",ICES altered,cat,1,5,None of the time,None of the time,N/A,1,None of the time,Trouble sleeping,Freq. - trouble sleeping,,, +SLP_02,SLP_02_cat5_2,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2012_s, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2015_2016_p::SLP_010, cchs2017_2018_p::SLP_010, cchs2015_2016_i::SLP_010, [SLP_02]",ICES altered,cat,2,5,Little of the time,Little of the time,N/A,2,Little of the time,Trouble sleeping,Freq. - trouble sleeping,,, +SLP_02,SLP_02_cat5_3,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2012_s, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2015_2016_p::SLP_010, cchs2017_2018_p::SLP_010, cchs2015_2016_i::SLP_010, [SLP_02]",ICES altered,cat,3,5,Some of the time,Some of the time,N/A,3,Some of the time,Trouble sleeping,Freq. - trouble sleeping,,, +SLP_02,SLP_02_cat5_4,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2012_s, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2015_2016_p::SLP_010, cchs2017_2018_p::SLP_010, cchs2015_2016_i::SLP_010, [SLP_02]",ICES altered,cat,4,5,Most of the time,Most of the time,N/A,4,Most of the time,Trouble sleeping,Freq. - trouble sleeping,,, +SLP_02,SLP_02_cat5_5,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2012_s, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2015_2016_p::SLP_010, cchs2017_2018_p::SLP_010, cchs2015_2016_i::SLP_010, [SLP_02]",ICES altered,cat,5,5,All the time,All the time,N/A,5,All the time,Trouble sleeping,Freq. - trouble sleeping,,, +SLP_02,SLP_02_cat5_NA::a,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2012_s, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2015_2016_p::SLP_010, cchs2017_2018_p::SLP_010, cchs2015_2016_i::SLP_010, [SLP_02]",ICES altered,cat,NA::a,5,not applicable,not applicable,N/A,6,not applicable,Trouble sleeping,Freq. - trouble sleeping,,, +SLP_02,SLP_02_cat5_NA::b,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2012_s, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2015_2016_p::SLP_010, cchs2017_2018_p::SLP_010, cchs2015_2016_i::SLP_010, [SLP_02]",ICES altered,cat,NA::b,5,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Trouble sleeping,Freq. - trouble sleeping,,, +SLP_02,SLP_02_cat5_NA::b,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2012_s, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2015_2016_p::SLP_010, cchs2017_2018_p::SLP_010, cchs2015_2016_i::SLP_010, [SLP_02]",ICES altered,cat,NA::b,5,missing,missing,N/A,else,else,Trouble sleeping,Freq. - trouble sleeping,,, +SLP_02_A,SLP_02_A_cat3_1,cat,"cchs2001_p, cchs2001_i",[GENA_04],ICES altered,cat,1,3,Most of the time,Most of the time,N/A,1,Most of the time,Trouble sleeping,Freq. - trouble sleeping,CCHS 2001 has different categories from other cycles,, +SLP_02_A,SLP_02_A_cat3_2,cat,"cchs2001_p, cchs2001_i",[GENA_04],ICES altered,cat,2,3,Sometimes,Sometimes,N/A,2,Sometimes,Trouble sleeping,Freq. - trouble sleeping,,, +SLP_02_A,SLP_02_A_cat3_3,cat,"cchs2001_p, cchs2001_i",[GENA_04],ICES altered,cat,3,3,Never,Never,N/A,3,Never,Trouble sleeping,Freq. - trouble sleeping,,, +SLP_02_A,SLP_02_A_cat3_NA::a,cat,"cchs2001_p, cchs2001_i",[GENA_04],ICES altered,cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Trouble sleeping,Freq. - trouble sleeping,,, +SLP_02_A,SLP_02_A_cat3_NA::b,cat,"cchs2001_p, cchs2001_i",[GENA_04],ICES altered,cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Trouble sleeping,Freq. - trouble sleeping,,, +SLP_02_A,SLP_02_A_cat3_NA::b,cat,"cchs2001_p, cchs2001_i",[GENA_04],ICES altered,cat,NA::b,3,missing,missing,N/A,else,else,Trouble sleeping,Freq. - trouble sleeping,,, +SLP_03,SLP_03_cat5_1,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2012_s, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2015_2016_p::SLP_015, cchs2017_2018_p::SLP_015, cchs2015_2016_i::SLP_015, [SLP_03]",ICES altered,cat,1,5,None of the time,None of the time,N/A,1,None of the time,Sleep refreshing,Freq. - find sleep refreshing,,, +SLP_03,SLP_03_cat5_2,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2012_s, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2015_2016_p::SLP_015, cchs2017_2018_p::SLP_015, cchs2015_2016_i::SLP_015, [SLP_03]",ICES altered,cat,2,5,Little of the time,Little of the time,N/A,2,Little of the time,Sleep refreshing,Freq. - find sleep refreshing,,, +SLP_03,SLP_03_cat5_3,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2012_s, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2015_2016_p::SLP_015, cchs2017_2018_p::SLP_015, cchs2015_2016_i::SLP_015, [SLP_03]",ICES altered,cat,3,5,Some of the time,Some of the time,N/A,3,Some of the time,Sleep refreshing,Freq. - find sleep refreshing,,, +SLP_03,SLP_03_cat5_4,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2012_s, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2015_2016_p::SLP_015, cchs2017_2018_p::SLP_015, cchs2015_2016_i::SLP_015, [SLP_03]",ICES altered,cat,4,5,Most of the time,Most of the time,N/A,4,Most of the time,Sleep refreshing,Freq. - find sleep refreshing,,, +SLP_03,SLP_03_cat5_5,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2012_s, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2015_2016_p::SLP_015, cchs2017_2018_p::SLP_015, cchs2015_2016_i::SLP_015, [SLP_03]",ICES altered,cat,5,5,All the time,All the time,N/A,5,All the time,Sleep refreshing,Freq. - find sleep refreshing,,, +SLP_03,SLP_03_cat3_NA::a,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2012_s, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2015_2016_p::SLP_015, cchs2017_2018_p::SLP_015, cchs2015_2016_i::SLP_015, [SLP_03]",ICES altered,cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Sleep refreshing,Freq. - find sleep refreshing,,, +SLP_03,SLP_03_cat3_NA::b,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2012_s, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2015_2016_p::SLP_015, cchs2017_2018_p::SLP_015, cchs2015_2016_i::SLP_015, [SLP_03]",ICES altered,cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Sleep refreshing,Freq. - find sleep refreshing,,, +SLP_03,SLP_03_cat3_NA::b,cat,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2012_s, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2015_2016_p::SLP_015, cchs2017_2018_p::SLP_015, cchs2015_2016_i::SLP_015, [SLP_03]",ICES altered,cat,NA::b,3,missing,missing,N/A,else,else,Sleep refreshing,Freq. - find sleep refreshing,,, +SLP_03_A,SLP_03_A_cat3_1,cat,"cchs2001_p, cchs2001_i",[GENA_05],ICES altered,cat,1,3,Most of the time,Most of the time,N/A,1,Most of the time,Sleep refreshing,Freq. - find sleep refreshing,CCHS 2001 has different categories from other cycles,, +SLP_03_A,SLP_03_A_cat3_2,cat,"cchs2001_p, cchs2001_i",[GENA_05],ICES altered,cat,2,3,Sometimes,Sometimes,N/A,2,Sometimes,Sleep refreshing,Freq. - find sleep refreshing,,, +SLP_03_A,SLP_03_A_cat3_3,cat,"cchs2001_p, cchs2001_i",[GENA_05],ICES altered,cat,3,3,Never,Never,N/A,3,Never,Sleep refreshing,Freq. - find sleep refreshing,,, +SLP_03_A,SLP_03_A_cat3_NA::a,cat,"cchs2001_p, cchs2001_i",[GENA_05],ICES altered,cat,NA::a,3,not applicable,not applicable,N/A,6,not applicable,Sleep refreshing,Freq. - find sleep refreshing,,, +SLP_03_A,SLP_03_A_cat3_NA::b,cat,"cchs2001_p, cchs2001_i",[GENA_05],ICES altered,cat,NA::b,3,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),Sleep refreshing,Freq. - find sleep refreshing,,, +SLP_03_A,SLP_03_A_cat3_NA::b,cat,"cchs2001_p, cchs2001_i",[GENA_05],ICES altered,cat,NA::b,3,missing,missing,N/A,else,else,Sleep refreshing,Freq. - find sleep refreshing,,, +SLPG01_B,SLPG01_B_cat11_1,cat,"cchs2011_2012_i, cchs2013_2014_i",[SLPG01],ICES specific,cat,1,11,<2 hours,<2 hours,Hours,1,<2 hours,Hours sleep,No./hours spent sleeping each night,,,Possible mistake with <2 hours +SLPG01_B,SLPG01_B_cat11_2,cat,"cchs2011_2012_i, cchs2013_2014_i",[SLPG01],ICES specific,cat,2,11,3-<4 hours,3-<4 hours,Hours,2,3-<4 hours,Hours sleep,No./hours spent sleeping each night,,, +SLPG01_B,SLPG01_B_cat11_3,cat,"cchs2011_2012_i, cchs2013_2014_i",[SLPG01],ICES specific,cat,3,11,4-<5 hours,4-<5 hours,Hours,3,4-<5 hours,Hours sleep,No./hours spent sleeping each night,,, +SLPG01_B,SLPG01_B_cat11_4,cat,"cchs2011_2012_i, cchs2013_2014_i",[SLPG01],ICES specific,cat,4,11,5-<6 hours,5-<6 hours,Hours,4,5-<6 hours,Hours sleep,No./hours spent sleeping each night,,, +SLPG01_B,SLPG01_B_cat11_5,cat,"cchs2011_2012_i, cchs2013_2014_i",[SLPG01],ICES specific,cat,5,11,6-<7 hours,6-<7 hours,Hours,5,6-<7 hours,Hours sleep,No./hours spent sleeping each night,,, +SLPG01_B,SLPG01_B_cat11_6,cat,"cchs2011_2012_i, cchs2013_2014_i",[SLPG01],ICES specific,cat,6,11,7-<8 hours,7-<8 hours,Hours,6,7-<8 hours,Hours sleep,No./hours spent sleeping each night,,, +SLPG01_B,SLPG01_B_cat11_7,cat,"cchs2011_2012_i, cchs2013_2014_i",[SLPG01],ICES specific,cat,7,11,8-<9 hours,8-<9 hours,Hours,7,8-<9 hours,Hours sleep,No./hours spent sleeping each night,,, +SLPG01_B,SLPG01_B_cat11_8,cat,"cchs2011_2012_i, cchs2013_2014_i",[SLPG01],ICES specific,cat,8,11,9-<10 hours,9-<10 hours,Hours,8,9-<10 hours,Hours sleep,No./hours spent sleeping each night,,, +SLPG01_B,SLPG01_B_cat11_9,cat,"cchs2011_2012_i, cchs2013_2014_i",[SLPG01],ICES specific,cat,9,11,10-<11 hours,10-<11 hours,Hours,9,10-<11 hours,Hours sleep,No./hours spent sleeping each night,,, +SLPG01_B,SLPG01_B_cat11_10,cat,"cchs2011_2012_i, cchs2013_2014_i",[SLPG01],ICES specific,cat,10,11,11-<12 hours,11-<12 hours,Hours,10,11-<12 hours,Hours sleep,No./hours spent sleeping each night,,, +SLPG01_B,SLPG01_B_cat11_11,cat,"cchs2011_2012_i, cchs2013_2014_i",[SLPG01],ICES specific,cat,11,11,>= 12 hours,>= 12 hours,Hours,11,>= 12 hours,Hours sleep,No./hours spent sleeping each night,,, +SLPG01_B,SLPG01_B_cat11_NA::a,cat,"cchs2011_2012_i, cchs2013_2014_i",[SLPG01],ICES specific,cat,NA::a,11,not applicable,not applicable,Hours,96,not applicable,Hours sleep,No./hours spent sleeping each night,,, +SLPG01_B,SLPG01_B_cat11_NA::a,cat,"cchs2011_2012_i, cchs2013_2014_i",[SLPG01],ICES specific,cat,NA::b,11,missing,missing,Hours,"[97,99]",don't know (97); refusal (98); not stated (99),Hours sleep,No./hours spent sleeping each night,,, +SLPG01_B,SLPG01_B_cat11_NA::b,cat,"cchs2011_2012_i, cchs2013_2014_i",[SLPG01],ICES specific,cat,NA::b,11,missing,missing,Hours,else,else,Hours sleep,No./hours spent sleeping each night,,, +SPLG01_C,SPLG01_C_cat12_1,cat,"cchs2001_i, cchs2015_2016_i","cchs2001_i::GENA_03, cchs2015_2016_i::SLP_005",ICES specific,cat,1,12,<2 hours,<2 hours,Hours,1,<2 hours,Hours sleep,No./hours spent sleeping each night,,, +SPLG01_C,SPLG01_C_cat12_2,cat,"cchs2001_i, cchs2015_2016_i","cchs2001_i::GENA_03, cchs2015_2016_i::SLP_006",ICES specific,cat,2,12,2-<3 hours,2-<3 hours,Hours,2,2-<3 hours,Hours sleep,No./hours spent sleeping each night,,, +SPLG01_C,SPLG01_C_cat12_3,cat,"cchs2001_i, cchs2015_2016_i","cchs2001_i::GENA_03, cchs2015_2016_i::SLP_007",ICES specific,cat,3,12,3-<4 hours,3-<4 hours,Hours,3,3-<4 hours,Hours sleep,No./hours spent sleeping each night,,, +SPLG01_C,SPLG01_C_cat12_4,cat,"cchs2001_i, cchs2015_2016_i","cchs2001_i::GENA_03, cchs2015_2016_i::SLP_008",ICES specific,cat,4,12,4-<5 hours,4-<5 hours,Hours,4,4-<5 hours,Hours sleep,No./hours spent sleeping each night,,, +SPLG01_C,SPLG01_C_cat12_5,cat,"cchs2001_i, cchs2015_2016_i","cchs2001_i::GENA_03, cchs2015_2016_i::SLP_009",ICES specific,cat,5,12,5-<6 hours,5-<6 hours,Hours,5,5-<6 hours,Hours sleep,No./hours spent sleeping each night,,, +SPLG01_C,SPLG01_C_cat12_6,cat,"cchs2001_i, cchs2015_2016_i","cchs2001_i::GENA_03, cchs2015_2016_i::SLP_010",ICES specific,cat,6,12,6-<7 hours,6-<7 hours,Hours,6,6-<7 hours,Hours sleep,No./hours spent sleeping each night,,, +SPLG01_C,SPLG01_C_cat12_7,cat,"cchs2001_i, cchs2015_2016_i","cchs2001_i::GENA_03, cchs2015_2016_i::SLP_011",ICES specific,cat,7,12,7-<8 hours,7-<8 hours,Hours,7,7-<8 hours,Hours sleep,No./hours spent sleeping each night,,, +SPLG01_C,SPLG01_C_cat12_8,cat,"cchs2001_i, cchs2015_2016_i","cchs2001_i::GENA_03, cchs2015_2016_i::SLP_012",ICES specific,cat,8,12,8-<9 hours,8-<9 hours,Hours,8,8-<9 hours,Hours sleep,No./hours spent sleeping each night,,, +SPLG01_C,SPLG01_C_cat12_9,cat,"cchs2001_i, cchs2015_2016_i","cchs2001_i::GENA_03, cchs2015_2016_i::SLP_013",ICES specific,cat,9,12,9-<10 hours,9-<10 hours,Hours,9,9-<10 hours,Hours sleep,No./hours spent sleeping each night,,, +SPLG01_C,SPLG01_C_cat12_10,cat,"cchs2001_i, cchs2015_2016_i","cchs2001_i::GENA_03, cchs2015_2016_i::SLP_014",ICES specific,cat,10,12,10-<11 hours,10-<11 hours,Hours,10,10-<11 hours,Hours sleep,No./hours spent sleeping each night,,, +SPLG01_C,SPLG01_C_cat12_11,cat,"cchs2001_i, cchs2015_2016_i","cchs2001_i::GENA_03, cchs2015_2016_i::SLP_015",ICES specific,cat,11,12,11-<12 hours,11-<12 hours,Hours,11,11-<12 hours,Hours sleep,No./hours spent sleeping each night,,, +SPLG01_C,SPLG01_C_cat12_12,cat,"cchs2001_i, cchs2015_2016_i","cchs2001_i::GENA_03, cchs2015_2016_i::SLP_016",ICES specific,cat,12,12,>= 12 hours,>= 12 hours,Hours,12,>= 12 hours,Hours sleep,No./hours spent sleeping each night,,, +SPLG01_C,SPLG01_C_cat12_NA::a,cat,"cchs2001_i, cchs2015_2016_i","cchs2001_i::GENA_03, cchs2015_2016_i::SLP_017",ICES specific,cat,NA::a,12,not applicable,not applicable,Hours,96,not applicable,Hours sleep,No./hours spent sleeping each night,,, +SPLG01_C,SPLG01_C_cat12_NA::a,cat,"cchs2001_i, cchs2015_2016_i","cchs2001_i::GENA_03, cchs2015_2016_i::SLP_018",ICES specific,cat,NA::b,12,missing,missing,Hours,"[97,99]",don't know (97); refusal (98); not stated (99),Hours sleep,No./hours spent sleeping each night,,, +SPLG01_C,SPLG01_C_cat12_NA::b,cat,"cchs2001_i, cchs2015_2016_i","cchs2001_i::GENA_03, cchs2015_2016_i::SLP_019",ICES specific,cat,NA::b,12,missing,missing,Hours,else,else,Hours sleep,No./hours spent sleeping each night,,, +SMK_01A,SMK_01A_cat2_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_01A, cchs2003_p::SMKC_01A, cchs2005_p::SMKE_01A, cchs2015_2016_p::SMK_020, cchs2017_2018_p::SMK_020, cchs2001_i::SMKA_01A, cchs2003_i::SMKC_01A, cchs2005_i::SMKE_01A, cchs2015_2016_i::SMK_020, cchs2017_2018_i::SMK_020, [SMK_01A]",ICES confirmed,cat,1,2,yes,yes,N/A,1,Yes,s100,"In lifetime, smoked 100 or more cigarettes",,, +SMK_01A,SMK_01A_cat2_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_01A, cchs2003_p::SMKC_01A, cchs2005_p::SMKE_01A, cchs2015_2016_p::SMK_020, cchs2017_2018_p::SMK_020, cchs2001_i::SMKA_01A, cchs2003_i::SMKC_01A, cchs2005_i::SMKE_01A, cchs2015_2016_i::SMK_020, cchs2017_2018_i::SMK_020, [SMK_01A]",ICES confirmed,cat,2,2,no,no,N/A,2,No,s100,"In lifetime, smoked 100 or more cigarettes",,, +SMK_01A,SMK_01A_cat2_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_01A, cchs2003_p::SMKC_01A, cchs2005_p::SMKE_01A, cchs2015_2016_p::SMK_020, cchs2017_2018_p::SMK_020, cchs2001_i::SMKA_01A, cchs2003_i::SMKC_01A, cchs2005_i::SMKE_01A, cchs2015_2016_i::SMK_020, cchs2017_2018_i::SMK_020, [SMK_01A]",ICES confirmed,cat,NA::a,2,not applicable,not applicable,N/A,6,not applicable,s100,"In lifetime, smoked 100 or more cigarettes",,, +SMK_01A,SMK_01A_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_01A, cchs2003_p::SMKC_01A, cchs2005_p::SMKE_01A, cchs2015_2016_p::SMK_020, cchs2017_2018_p::SMK_020, cchs2001_i::SMKA_01A, cchs2003_i::SMKC_01A, cchs2005_i::SMKE_01A, cchs2015_2016_i::SMK_020, cchs2017_2018_i::SMK_020, [SMK_01A]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,"[7,9]",don't know (7); refusal (8); not stated (9),s100,"In lifetime, smoked 100 or more cigarettes",,, +SMK_01A,SMK_01A_cat2_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_01A, cchs2003_p::SMKC_01A, cchs2005_p::SMKE_01A, cchs2015_2016_p::SMK_020, cchs2017_2018_p::SMK_020, cchs2001_i::SMKA_01A, cchs2003_i::SMKC_01A, cchs2005_i::SMKE_01A, cchs2015_2016_i::SMK_020, cchs2017_2018_i::SMK_020, [SMK_01A]",ICES confirmed,cat,NA::b,2,missing,missing,N/A,else,else,s100,"In lifetime, smoked 100 or more cigarettes",,, +SMK_05B,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_05B, cchs2003_p::SMKC_05B, cchs2005_p::SMKE_05B, cchs2015_2016_p::SMK_050, cchs2017_2018_p::SMK_050, [SMK_05B], cchs2001_1::SMKA_05B, cchs2003_i::SMKC_05B, cchs2005_i::SMKE_05B, cchs2015_2016_i::SMK_050, cchs2017_2018_i::SMK_050, [SMK_05B]",ICES confirmed,cont,copy,N/A,Cigarettes/day - occasional,# of cigarettes smoked daily - daily smoker,cigarettes,"[1,99]",# of cigarettes smoked daily - occasional smoker,cigdayo,# of cigarettes smoked daily - occasional smoker,,, +SMK_05B,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_05B, cchs2003_p::SMKC_05B, cchs2005_p::SMKE_05B, cchs2015_2016_p::SMK_050, cchs2017_2018_p::SMK_050, [SMK_05B], cchs2001_1::SMKA_05B, cchs2003_i::SMKC_05B, cchs2005_i::SMKE_05B, cchs2015_2016_i::SMK_050, cchs2017_2018_i::SMK_050, [SMK_05B]",ICES confirmed,cont,NA::a,N/A,not applicable,not applicable,cigarettes,996,not applicable,cigdayo,# of cigarettes smoked daily - occasional smoker,,, +SMK_05B,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_05B, cchs2003_p::SMKC_05B, cchs2005_p::SMKE_05B, cchs2015_2016_p::SMK_050, cchs2017_2018_p::SMK_050, [SMK_05B], cchs2001_1::SMKA_05B, cchs2003_i::SMKC_05B, cchs2005_i::SMKE_05B, cchs2015_2016_i::SMK_050, cchs2017_2018_i::SMK_050, [SMK_05B]",ICES confirmed,cont,NA::b,N/A,missing,missing,cigarettes,"[997,999]",don't know (997); refusal (998); not stated (999),cigdayo,# of cigarettes smoked daily - occasional smoker,,, +SMK_05B,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_05B, cchs2003_p::SMKC_05B, cchs2005_p::SMKE_05B, cchs2015_2016_p::SMK_050, cchs2017_2018_p::SMK_050, [SMK_05B], cchs2001_1::SMKA_05B, cchs2003_i::SMKC_05B, cchs2005_i::SMKE_05B, cchs2015_2016_i::SMK_050, cchs2017_2018_i::SMK_050, [SMK_05B]",ICES confirmed,cont,NA::b,N/A,missing,missing,cigarettes,else,else,cigdayo,# of cigarettes smoked daily - occasional smoker,,, +SMK_05C,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_05C, cchs2003_p::SMKC_05C, cchs2005_p::SMKE_05C, cchs2015_2016_p::SMK_055, cchs2017_2018_p::SMK_055, [SMK_05C], cchs2001_i::SMKA_05C, cchs2003_i::SMKC_05C, cchs2005_i::SMKE_05C, cchs2015_2016_i::SMK_055, cchs2017_2018_i::SMK_055, [SMK_05C]",ICES confirmed,cont,copy,N/A,# days smoked at least 1 cigarette,# days smoked at least 1 cigarette,days,"[0,31]",# days smoked at least 1 cigarette,Number of days - smoked 1 cigarette or more (occ. smoker),"In the past month, on how many days have you smoked 1 or more cigarettes?",,, +SMK_05C,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_05C, cchs2003_p::SMKC_05C, cchs2005_p::SMKE_05C, cchs2015_2016_p::SMK_055, cchs2017_2018_p::SMK_055, [SMK_05C], cchs2001_i::SMKA_05C, cchs2003_i::SMKC_05C, cchs2005_i::SMKE_05C, cchs2015_2016_i::SMK_055, cchs2017_2018_i::SMK_055, [SMK_05C]",ICES confirmed,cont,NA::a,N/A,not applicable,not applicable,days,96,not applicable,Number of days - smoked 1 cigarette or more (occ. smoker),"In the past month, on how many days have you smoked 1 or more cigarettes?",,, +SMK_05C,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_05C, cchs2003_p::SMKC_05C, cchs2005_p::SMKE_05C, cchs2015_2016_p::SMK_055, cchs2017_2018_p::SMK_055, [SMK_05C], cchs2001_i::SMKA_05C, cchs2003_i::SMKC_05C, cchs2005_i::SMKE_05C, cchs2015_2016_i::SMK_055, cchs2017_2018_i::SMK_055, [SMK_05C]",ICES confirmed,cont,NA::b,N/A,missing,missing,days,"[97,99]",don't know (97); refusal (98); not stated (99),Number of days - smoked 1 cigarette or more (occ. smoker),"In the past month, on how many days have you smoked 1 or more cigarettes?",,, +SMK_05C,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_05C, cchs2003_p::SMKC_05C, cchs2005_p::SMKE_05C, cchs2015_2016_p::SMK_055, cchs2017_2018_p::SMK_055, [SMK_05C], cchs2001_i::SMKA_05C, cchs2003_i::SMKC_05C, cchs2005_i::SMKE_05C, cchs2015_2016_i::SMK_055, cchs2017_2018_i::SMK_055, [SMK_05C]",ICES confirmed,cont,NA::b,N/A,missing,missing,days,else,else,Number of days - smoked 1 cigarette or more (occ. smoker),"In the past month, on how many days have you smoked 1 or more cigarettes?",,, +SMK_09A_A,SMK_09A_A_cat4_1,cat,"cchs2001_p, cchs2001_i","cchs2001_p::SMKA_09A, cchs2001_i::SMKA_09A",ICES confirmed,cat,1,4,<1 year,Less than one year ago,years,1,Less than one year ago,stpd,When did you stop smoking daily - former daily,,, +SMK_09A_A,SMK_09A_A_cat4_2,cat,"cchs2001_p, cchs2001_i","cchs2001_p::SMKA_09A, cchs2001_i::SMKA_09A",ICES confirmed,cat,2,4,1 to 2 years,1 year to 2 years ago,years,2,1 year to 2 years ago,stpd,When did you stop smoking daily - former daily,,, +SMK_09A_A,SMK_09A_A_cat4_3,cat,"cchs2001_p, cchs2001_i","cchs2001_p::SMKA_09A, cchs2001_i::SMKA_09A",ICES confirmed,cat,3,4,3 to 5 years,3 years to 5 years ago,years,3,3 years to 5 years ago,stpd,When did you stop smoking daily - former daily,,, +SMK_09A_A,SMK_09A_A_cat4_4,cat,"cchs2001_p, cchs2001_i","cchs2001_p::SMKA_09A, cchs2001_i::SMKA_09A",ICES confirmed,cat,4,4,>5 years,More than 5 years ago,years,4,More than 5 years ago,stpd,When did you stop smoking daily - former daily,,, +SMK_09A_A,SMK_09A_A_cat4_NA::a,cat,"cchs2001_p, cchs2001_i","cchs2001_p::SMKA_09A, cchs2001_i::SMKA_09A",ICES confirmed,cat,NA::a,4,not applicable,not applicable,years,6,not applicable,stpd,When did you stop smoking daily - former daily,,, +SMK_09A_A,SMK_09A_A_cat4_NA::b,cat,"cchs2001_p, cchs2001_i","cchs2001_p::SMKA_09A, cchs2001_i::SMKA_09A",ICES confirmed,cat,NA::b,4,missing,missing,years,"[7,9]",don't know (7); refusal (8); not stated (9),stpd,When did you stop smoking daily - former daily,,, +SMK_09A_A,SMK_09A_A_cat4_NA::b,cat,"cchs2001_p, cchs2001_i","cchs2001_p::SMKA_09A, cchs2001_i::SMKA_09A",ICES confirmed,cat,NA::b,4,missing,missing,years,else,else,stpd,When did you stop smoking daily - former daily,,, +SMK_09A_B,SMK_09A_B_cat4_1,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018","cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, cchs2015_2016_p::SMK_080, cchs2017_2018_p::SMK_080, cchs2003_i::SMKC_09A, cchs2005_i::SMKE_09A, cchs2015_2016_i::SMK_080, cchs2017_2018_i::SMK_080, [SMK_09A]",ICES confirmed,cat,1,4,<1 year,Less than one year ago,years,1,Less than 1 year,stpd,When did you stop smoking daily - former daily,,, +SMK_09A_B,SMK_09A_B_cat4_2,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, cchs2015_2016_p::SMK_080, cchs2017_2018_p::SMK_080, cchs2003_i::SMKC_09A, cchs2005_i::SMKE_09A, cchs2015_2016_i::SMK_080, cchs2017_2018_i::SMK_080, [SMK_09A]",ICES confirmed,cat,2,4,1 to <2 years,1 year to less than 2 years ago,years,2,1 to <2 years,stpd,When did you stop smoking daily - former daily,,, +SMK_09A_B,SMK_09A_B_cat4_3,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2020","cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, cchs2015_2016_p::SMK_080, cchs2017_2018_p::SMK_080, cchs2003_i::SMKC_09A, cchs2005_i::SMKE_09A, cchs2015_2016_i::SMK_080, cchs2017_2018_i::SMK_080, [SMK_09A]",ICES confirmed,cat,3,4,2 to <3 years,2 years to less than 3 years ago,years,3,2 to <3 years,stpd,When did you stop smoking daily - former daily,,, +SMK_09A_B,SMK_09A_B_cat4_4,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2021","cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, cchs2015_2016_p::SMK_080, cchs2017_2018_p::SMK_080, cchs2003_i::SMKC_09A, cchs2005_i::SMKE_09A, cchs2015_2016_i::SMK_080, cchs2017_2018_i::SMK_080, [SMK_09A]",ICES confirmed,cat,4,4,>= 3 years,3 or more years ago,years,4,3 years or more,stpd,When did you stop smoking daily - former daily,,, +SMK_09A_B,SMK_09A_B_cat4_NA::a,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2022","cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, cchs2015_2016_p::SMK_080, cchs2017_2018_p::SMK_080, cchs2003_i::SMKC_09A, cchs2005_i::SMKE_09A, cchs2015_2016_i::SMK_080, cchs2017_2018_i::SMK_080, [SMK_09A]",ICES confirmed,cat,NA::a,4,not applicable,not applicable,years,6,not applicable,stpd,When did you stop smoking daily - former daily,,, +SMK_09A_B,SMK_09A_B_cat4_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2023","cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, cchs2015_2016_p::SMK_080, cchs2017_2018_p::SMK_080, cchs2003_i::SMKC_09A, cchs2005_i::SMKE_09A, cchs2015_2016_i::SMK_080, cchs2017_2018_i::SMK_080, [SMK_09A]",ICES confirmed,cat,NA::b,4,missing,missing,years,"[7,9]",don't know (7); refusal (8); not stated (9),stpd,When did you stop smoking daily - former daily,,, +SMK_09A_B,SMK_09A_B_cat4_NA::b,cat,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2024","cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, cchs2015_2016_p::SMK_080, cchs2017_2018_p::SMK_080, cchs2003_i::SMKC_09A, cchs2005_i::SMKE_09A, cchs2015_2016_i::SMK_080, cchs2017_2018_i::SMK_080, [SMK_09A]",ICES confirmed,cat,NA::b,4,missing,missing,years,else,else,stpd,When did you stop smoking daily - former daily,,, +SMK_204,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_204, cchs2003_p::SMKC_204, cchs2005_p::SMKE_204, cchs2015_2016_p::SMK_045, cchs2017_2018_p::SMK_045, [SMK_204]",ICES confirmed,cont,copy,N/A,Cigarettes/day - daily,# of cigarettes smoked daily - daily smoker,cigarettes,"[1,99]",# of cigarettes smoked daily - daily smoker,cigdayd,# of cigarettes smoked daily - daily smoker,,, +SMK_204,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_204, cchs2003_p::SMKC_204, cchs2005_p::SMKE_204, cchs2015_2016_p::SMK_045, cchs2017_2018_p::SMK_045, [SMK_204]",ICES confirmed,cont,NA::a,N/A,not applicable,not applicable,cigarettes,996,not applicable,cigdayd,# of cigarettes smoked daily - daily smoker,,, +SMK_204,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_204, cchs2003_p::SMKC_204, cchs2005_p::SMKE_204, cchs2015_2016_p::SMK_045, cchs2017_2018_p::SMK_045, [SMK_204]",ICES confirmed,cont,NA::b,N/A,missing,missing,cigarettes,"[997,999]",don't know (997); refusal (998); not stated (999),cigdayd,# of cigarettes smoked daily - daily smoker,,, +SMK_204,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_204, cchs2003_p::SMKC_204, cchs2005_p::SMKE_204, cchs2015_2016_p::SMK_045, cchs2017_2018_p::SMK_045, [SMK_204]",ICES confirmed,cont,NA::b,N/A,missing,missing,cigarettes,else,else,cigdayd,# of cigarettes smoked daily - daily smoker,,, +SMK_208,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_208, cchs2003_p::SMKC_208, cchs2005_p::SMKE_208, cchs2015_2016_p::SMK_075, cchs2017_2018_p::SMK_075, [SMK_208]",ICES confirmed,cont,copy,N/A,Cigarettes/day - former daily,Cigarettes/day - former daily,cigarettes,"[1,99]",# of cigarettes smoke each day - former daily,# of cigarettes smoke each day - former daily,# of cigarettes smoked each day - former daily smoker,,, +SMK_208,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_208, cchs2003_p::SMKC_208, cchs2005_p::SMKE_208, cchs2015_2016_p::SMK_075, cchs2017_2018_p::SMK_075, [SMK_208]",ICES confirmed,cont,NA::a,N/A,not applicable,not applicable,cigarettes,996,not applicable,# of cigarettes smoke each day - former daily,# of cigarettes smoked each day - former daily smoker,,, +SMK_208,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_208, cchs2003_p::SMKC_208, cchs2005_p::SMKE_208, cchs2015_2016_p::SMK_075, cchs2017_2018_p::SMK_075, [SMK_208]",ICES confirmed,cont,NA::b,N/A,missing,missing,cigarettes,"[997,999]",don't know (997); refusal (998); not stated (999),# of cigarettes smoke each day - former daily,# of cigarettes smoked each day - former daily smoker,,, +SMK_208,N/A,cont,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_208, cchs2003_p::SMKC_208, cchs2005_p::SMKE_208, cchs2015_2016_p::SMK_075, cchs2017_2018_p::SMK_075, [SMK_208]",ICES confirmed,cont,NA::b,N/A,missing,missing,cigarettes,else,else,# of cigarettes smoke each day - former daily,# of cigarettes smoked each day - former daily smoker,,, +SMKDSTY_A,SMKDSTY_A_cat6_1,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, cchs2001_i::SMKADSTY, cchs2003_i::SMKCDSTY, cchs2005_i::SMKEDSTY, [SMKDSTY]",ICES confirmed,cat,1,6,Daily,Daily smoker,N/A,1,Daily,Smoking status,"Type of smoker: daily, occasional, always occasional, former daily, former occasional, never",,, +SMKDSTY_A,SMKDSTY_A_cat6_2,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, cchs2001_i::SMKADSTY, cchs2003_i::SMKCDSTY, cchs2005_i::SMKEDSTY, [SMKDSTY]",ICES confirmed,cat,2,6,Occasional (former daily),Former daily current occasional smoker,N/A,2,Occasional,Smoking status,"Type of smoker: daily, occasional, always occasional, former daily, former occasional, never",,, +SMKDSTY_A,SMKDSTY_A_cat6_3,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, cchs2001_i::SMKADSTY, cchs2003_i::SMKCDSTY, cchs2005_i::SMKEDSTY, [SMKDSTY]",ICES confirmed,cat,3,6,Always occasional,Never daily current occasional smoker,N/A,3,Always occasional,Smoking status,"Type of smoker: daily, occasional, always occasional, former daily, former occasional, never",,, +SMKDSTY_A,SMKDSTY_A_cat6_4,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, cchs2001_i::SMKADSTY, cchs2003_i::SMKCDSTY, cchs2005_i::SMKEDSTY, [SMKDSTY]",ICES confirmed,cat,4,6,Former daily,Former daily current nonsmoker,N/A,4,Former daily,Smoking status,"Type of smoker: daily, occasional, always occasional, former daily, former occasional, never",,, +SMKDSTY_A,SMKDSTY_A_cat6_5,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, cchs2001_i::SMKADSTY, cchs2003_i::SMKCDSTY, cchs2005_i::SMKEDSTY, [SMKDSTY]",ICES confirmed,cat,5,6,Former occasional,Never daily current nonsmoker (former occasional),N/A,5,Former occasional,Smoking status,"Type of smoker: daily, occasional, always occasional, former daily, former occasional, never",,, +SMKDSTY_A,SMKDSTY_A_cat6_6,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, cchs2001_i::SMKADSTY, cchs2003_i::SMKCDSTY, cchs2005_i::SMKEDSTY, [SMKDSTY]",ICES confirmed,cat,6,6,Never smoked,Never smoked,N/A,6,Never smoked,Smoking status,"Type of smoker: daily, occasional, always occasional, former daily, former occasional, never",,, +SMKDSTY_A,SMKDSTY_A_cat6_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, cchs2001_i::SMKADSTY, cchs2003_i::SMKCDSTY, cchs2005_i::SMKEDSTY, [SMKDSTY]",ICES confirmed,cat,NA::a,6,not applicable,not applicable,N/A,96,not applicable,Smoking status,"Type of smoker: daily, occasional, always occasional, former daily, former occasional, never",,, +SMKDSTY_A,SMKDSTY_A_cat6_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, cchs2001_i::SMKADSTY, cchs2003_i::SMKCDSTY, cchs2005_i::SMKEDSTY, [SMKDSTY]",ICES confirmed,cat,NA::b,6,missing,missing,N/A,"[97,99]",don't know (97); refusal (98); not stated (99),Smoking status,"Type of smoker: daily, occasional, always occasional, former daily, former occasional, never",,, +SMKDSTY_A,SMKDSTY_A_cat6_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, cchs2001_i::SMKADSTY, cchs2003_i::SMKCDSTY, cchs2005_i::SMKEDSTY, [SMKDSTY]",ICES confirmed,cat,NA::b,6,missing,missing,N/A,else,else,Smoking status,"Type of smoker: daily, occasional, always occasional, former daily, former occasional, never",,, +SMKDSTY_cat5,SMKDSTY_cat5_1,cat,"cchs2015_2016_p, cchs2017_2018_p, cchs2015_2016_i, cchs2017_2018_i","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY, cchs2015_2016_i::SMKDVSTY, cchs2017_2018_i::SMKDVSTY",ICES confirmed,cat,1,5,Daily,Current daily smoker,N/A,1,Daily,Smoking status,"Type of smoker: daily, occasional, former daily, former occasional, never",,, +SMKDSTY_cat5,SMKDSTY_cat5_2,cat,"cchs2015_2016_p, cchs2017_2018_p, cchs2015_2016_i, cchs2017_2018_i","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY, cchs2015_2016_i::SMKDVSTY, cchs2017_2018_i::SMKDVSTY",ICES confirmed,cat,2,5,Occasional,Current occasional smoker,N/A,2,Occasional,Smoking status,"Type of smoker: daily, occasional, former daily, former occasional, never",,, +SMKDSTY_cat5,SMKDSTY_cat5_3,cat,"cchs2015_2016_p, cchs2017_2018_p, cchs2015_2016_i, cchs2017_2018_i","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY, cchs2015_2016_i::SMKDVSTY, cchs2017_2018_i::SMKDVSTY",ICES confirmed,cat,3,5,Former daily,Former daily smoker,N/A,3,Former daily,Smoking status,"Type of smoker: daily, occasional, former daily, former occasional, never",,, +SMKDSTY_cat5,SMKDSTY_cat5_4,cat,"cchs2015_2016_p, cchs2017_2018_p, cchs2015_2016_i, cchs2017_2018_i","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY, cchs2015_2016_i::SMKDVSTY, cchs2017_2018_i::SMKDVSTY",ICES confirmed,cat,4,5,Former occasional,Former occasional,N/A,"[4,5]",Former occasional,Smoking status,"Type of smoker: daily, occasional, former daily, former occasional, never","SMKDSTY_cat5 is a 5 category variable for smoking status for cycles up to 2018. Prior to 2015, 'occasional' and 'always occasional' are combined to form the current 'occasional' category. 2015 onwards, 'former occasional' and 'experimental' are combined to form the current 'former occasional' category",, +SMKDSTY_cat5,SMKDSTY_cat5_5,cat,"cchs2015_2016_p, cchs2017_2018_p, cchs2015_2016_i, cchs2017_2018_i","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY, cchs2015_2016_i::SMKDVSTY, cchs2017_2018_i::SMKDVSTY",ICES confirmed,cat,5,5,Never smoked,Never smoked,N/A,6,Never smoked,Smoking status,"Type of smoker: daily, occasional, former daily, former occasional, never",,, +SMKDSTY_cat5,SMKDSTY_cat5_NA::a,cat,"cchs2015_2016_p, cchs2017_2018_p, cchs2015_2016_i, cchs2017_2018_i","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY, cchs2015_2016_i::SMKDVSTY, cchs2017_2018_i::SMKDVSTY",ICES confirmed,cat,NA::a,5,not applicable,not applicable,N/A,96,not applicable,Smoking status,"Type of smoker: daily, occasional, former daily, former occasional, never",,, +SMKDSTY_cat5,SMKDSTY_cat5_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p, cchs2015_2016_i, cchs2017_2018_i","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY, cchs2015_2016_i::SMKDVSTY, cchs2017_2018_i::SMKDVSTY",ICES confirmed,cat,NA::b,5,missing,missing,N/A,"[97,99]",don't know (97); refusal (98); not stated (99),Smoking status,"Type of smoker: daily, occasional, former daily, former occasional, never",,, +SMKDSTY_cat5,SMKDSTY_cat5_NA::b,cat,"cchs2015_2016_p, cchs2017_2018_p, cchs2015_2016_i, cchs2017_2018_i","cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY, cchs2015_2016_i::SMKDVSTY, cchs2017_2018_i::SMKDVSTY",ICES confirmed,cat,NA::b,5,missing,missing,N/A,else,else,Smoking status,"Type of smoker: daily, occasional, former daily, former occasional, never",,, +SMKG01C_A,SMKG01C_A_cat10_1,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C, cchs2001_i::SMKAG01C",ICES altered,cat,1,10,5 To 11 Years,age smoked first whole cigarette (5 to 11),years,1,5 To 11 Years,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_2,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C, cchs2001_i::SMKAG01C",ICES altered,cat,2,10,12 To 14 Years,age smoked first whole cigarette (12 to 14),years,2,12 To 14 Years,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_3,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C, cchs2001_i::SMKAG01C",ICES altered,cat,3,10,15 To 19 Years,age smoked first whole cigarette (18 to 19),years,3,15 To 19 Years,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_4,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C, cchs2001_i::SMKAG01C",ICES altered,cat,4,10,20 To 24 Years,age smoked first whole cigarette (20 to 24),years,4,20 To 24 Years,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_5,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C, cchs2001_i::SMKAG01C",ICES altered,cat,5,10,25 To 29 Years,age smoked first whole cigarette (25 to 29),years,5,25 To 29 Years,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_6,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C, cchs2001_i::SMKAG01C",ICES altered,cat,6,10,30 To 34 Years,age smoked first whole cigarette (30 to 34),years,6,30 To 34 Years,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_7,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C, cchs2001_i::SMKAG01C",ICES altered,cat,7,10,35 To 39 Years,age smoked first whole cigarette (35 to 39),years,7,35 To 39 Years,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_8,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C, cchs2001_i::SMKAG01C",ICES altered,cat,8,10,40 To 44 Years,age smoked first whole cigarette (40 to 44),years,8,40 To 44 Years,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_9,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C, cchs2001_i::SMKAG01C",ICES altered,cat,9,10,45 To 49 Years,age smoked first whole cigarette (45 to 49),years,9,45 To 49 Years,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_10,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C, cchs2001_i::SMKAG01C",ICES altered,cat,10,10,50 Years or more,age smoked first whole cigarette (50 plus),years,10,50 Years or more,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C, cchs2001_i::SMKAG01C",ICES altered,cat,NA::a,10,not applicable,not applicable,years,96,not applicable,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C, cchs2001_i::SMKAG01C",ICES altered,cat,NA::b,10,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C, cchs2001_i::SMKAG01C",ICES altered,cat,NA::b,10,missing,missing,years,else,else,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_1,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SMKC_01C, cchs2005_i::SMKE_01C, cchs2015_2016_i::SMK_035, cchs2017_2018_i::SMK_035, [SMK_01C]",ICES altered,cont,1,10,5 To 11 Years,age smoked first whole cigarette (5 to 11),years,"[5,12)",5 To 11 Years,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_2,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SMKC_01C, cchs2005_i::SMKE_01C, cchs2015_2016_i::SMK_035, cchs2017_2018_i::SMK_035, [SMK_01C]",ICES altered,cont,2,10,12 To 14 Years,age smoked first whole cigarette (12 to 14),years,"[12,15)",12 To 14 Years,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_3,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SMKC_01C, cchs2005_i::SMKE_01C, cchs2015_2016_i::SMK_035, cchs2017_2018_i::SMK_035, [SMK_01C]",ICES altered,cont,3,10,15 To 19 Years,age smoked first whole cigarette (18 to 19),years,"[15,20)",15 To 19 Years,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_4,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SMKC_01C, cchs2005_i::SMKE_01C, cchs2015_2016_i::SMK_035, cchs2017_2018_i::SMK_035, [SMK_01C]",ICES altered,cont,4,10,20 To 24 Years,age smoked first whole cigarette (20 to 24),years,"[20,25)",20 To 24 Years,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_5,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SMKC_01C, cchs2005_i::SMKE_01C, cchs2015_2016_i::SMK_035, cchs2017_2018_i::SMK_035, [SMK_01C]",ICES altered,cont,5,10,25 To 29 Years,age smoked first whole cigarette (25 to 29),years,"[25,30)",25 To 29 Years,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_6,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SMKC_01C, cchs2005_i::SMKE_01C, cchs2015_2016_i::SMK_035, cchs2017_2018_i::SMK_035, [SMK_01C]",ICES altered,cont,6,10,30 To 34 Years,age smoked first whole cigarette (30 to 34),years,"[30,35)",30 To 34 Years,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_7,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SMKC_01C, cchs2005_i::SMKE_01C, cchs2015_2016_i::SMK_035, cchs2017_2018_i::SMK_035, [SMK_01C]",ICES altered,cont,7,10,35 To 39 Years,age smoked first whole cigarette (35 to 39),years,"[35,40)",35 To 39 Years,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_8,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SMKC_01C, cchs2005_i::SMKE_01C, cchs2015_2016_i::SMK_035, cchs2017_2018_i::SMK_035, [SMK_01C]",ICES altered,cont,8,10,40 To 44 Years,age smoked first whole cigarette (40 to 44),years,"[40,45)",40 To 44 Years,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_9,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SMKC_01C, cchs2005_i::SMKE_01C, cchs2015_2016_i::SMK_035, cchs2017_2018_i::SMK_035, [SMK_01C]",ICES altered,cont,9,10,45 To 49 Years,age smoked first whole cigarette (45 to 49),years,"[45,50)",45 To 49 Years,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_10,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SMKC_01C, cchs2005_i::SMKE_01C, cchs2015_2016_i::SMK_035, cchs2017_2018_i::SMK_035, [SMK_01C]",ICES altered,cont,10,10,50 Years or more,age smoked first whole cigarette (50 plus),years,"[50,80]",50 Years or more,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_NA::a,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SMKC_01C, cchs2005_i::SMKE_01C, cchs2015_2016_i::SMK_035, cchs2017_2018_i::SMK_035, [SMK_01C]",ICES altered,cont,NA::a,10,not applicable,not applicable,years,996,not applicable,agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_NA::b,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SMKC_01C, cchs2005_i::SMKE_01C, cchs2015_2016_i::SMK_035, cchs2017_2018_i::SMK_035, [SMK_01C]",ICES altered,cont,NA::b,10,missing,missing,years,"[997,999]",don't know (997); refusal (998); not stated (999),agec1,Age smoked first cigarette,,, +SMKG01C_A,SMKG01C_A_cat10_NA::b,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SMKC_01C, cchs2005_i::SMKE_01C, cchs2015_2016_i::SMK_035, cchs2017_2018_i::SMK_035, [SMK_01C]",ICES altered,cont,NA::b,10,missing,missing,years,else,else,agec1,Age smoked first cigarette,,, +SMKG01C_cont,N/A,cont,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_01c, cchs2005_i::SMKE_01C, [SMK_01C]",ICES altered,cont,copy,N/A,agec1,agec1,years,"[5,80]",agec1,agec1,Age smoked first cigarette,,, +SMKG01C_cont,N/A,cont,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_01c, cchs2005_i::SMKE_01C, [SMK_01C]",ICES altered,cont,NA::a,N/A,not applicable,not applicable,years,996,not applicable,agec1,Age smoked first cigarette,,, +SMKG01C_cont,N/A,cont,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_01c, cchs2005_i::SMKE_01C, [SMK_01C]",ICES altered,cont,NA::b,N/A,missing,missing,years,"[997,999]",don't know (997); refusal (998); not stated (999),agec1,Age smoked first cigarette,,, +SMKG01C_cont,N/A,cont,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_01c, cchs2005_i::SMKE_01C, [SMK_01C]",ICES altered,cont,NA::b,N/A,missing,missing,years,else,else,agec1,Age smoked first cigarette,,, +SMKG09C,SMKG09C_cat3_1,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SMKC_09C, cchs2005_i::SMKE_09C, cchs2015_2016_i::SMK_090, cchs2017_2018_i::SMK_090, [SMK_09C]",ICES altered,cat,1,3,3 to 5 years,3 to 5 years,years,"[3,6)",3 to 5 years,stpdy,Years since stopped smoking daily - former daily,,, +SMKG09C,SMKG09C_cat3_2,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SMKC_09C, cchs2005_i::SMKE_09C, cchs2015_2016_i::SMK_090, cchs2017_2018_i::SMK_090, [SMK_09C]",ICES altered,cat,2,3,6 to 10 years,6 to 10 years,years,"[6,11)",6 to 10 years,stpdy,Years since stopped smoking daily - former daily,,, +SMKG09C,SMKG09C_cat3_3,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SMKC_09C, cchs2005_i::SMKE_09C, cchs2015_2016_i::SMK_090, cchs2017_2018_i::SMK_090, [SMK_09C]",ICES altered,cat,3,3,11+ years,11 or more years,years,"[11,82]",11 or more years,stpdy,Years since stopped smoking daily - former daily,,, +SMKG09C,SMKG09C_cat3_NA::a,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SMKC_09C, cchs2005_i::SMKE_09C, cchs2015_2016_i::SMK_090, cchs2017_2018_i::SMK_090, [SMK_09C]",ICES altered,cat,NA::a,3,not applicable,not applicable,years,996,not applicable,stpdy,Years since stopped smoking daily - former daily,,, +SMKG09C,SMKG09C_cat3_NA::b,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SMKC_09C, cchs2005_i::SMKE_09C, cchs2015_2016_i::SMK_090, cchs2017_2018_i::SMK_090, [SMK_09C]",ICES altered,cat,NA::b,3,missing,missing,years,"[997,999]",don't know (997); refusal (998); not stated (999),stpdy,Years since stopped smoking daily - former daily,,, +SMKG09C,SMKG09C_cat3_NA::b,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SMKC_09C, cchs2005_i::SMKE_09C, cchs2015_2016_i::SMK_090, cchs2017_2018_i::SMK_090, [SMK_09C]",ICES altered,cat,NA::b,3,missing,missing,years,else,else,stpdy,Years since stopped smoking daily - former daily,,, +SMKG203_A,SMKG203_A_cat10_1,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203",ICES altered,cat,1,10,5 To 11 Years,age (5 to 11) started smoking daily - daily smoker,years,1,5 To 11 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_2,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203",ICES altered,cat,2,10,12 To 14 Years,age (12 to 14) started smoking daily - daily smoker,years,2,12 To 14 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_3,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203",ICES altered,cat,3,10,15 to 19 Years,age (15 to 19) started smoking daily - daily smoker,years,3,15 to 19 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_4,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203",ICES altered,cat,4,10,20 To 24 Years,age (20 to 24) started smoking daily - daily smoker,years,4,20 To 24 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_5,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203",ICES altered,cat,5,10,25 To 29 Years,age (25 to 29) started smoking daily - daily smoker,years,5,25 To 29 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_6,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203",ICES altered,cat,6,10,30 To 34 Years,age (30 to 34) started smoking daily - daily smoker,years,6,30 To 34 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_7,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203",ICES altered,cat,7,10,35 To 39 Years,age (35 to 39) started smoking daily - daily smoker,years,7,35 To 39 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_8,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203",ICES altered,cat,8,10,40 To 44 Years,age (40 to 44) started smoking daily - daily smoker,years,8,40 To 44 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_9,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203",ICES altered,cat,9,10,45 To 49 Years,age (45 to 49) started smoking daily - daily smoker,years,9,45 To 49 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_10,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203",ICES altered,cat,10,10,50 Years or more,age (50 or more) started smoking daily - daily smoker,years,10,50 Years or more,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203",ICES altered,cat,NA::a,10,not applicable,not applicable,years,96,not applicable,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203",ICES altered,cat,NA::b,10,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203",ICES altered,cat,NA::b,10,missing,missing,years,else,else,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_1,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SMKC_203, cchs2005_i::SMKE_203, [SMK_203]",ICES altered,cont,1,10,5 To 11 Years,age (5 to 11) started smoking daily - daily smoker,years,"[5,12)",5 To 11 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_2,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SMKC_203, cchs2005_i::SMKE_203, [SMK_203]",ICES altered,cont,2,10,12 To 14 Years,age (12 to 14) started smoking daily - daily smoker,years,"[12,15)",12 To 14 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_3,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SMKC_203, cchs2005_i::SMKE_203, [SMK_203]",ICES altered,cont,3,10,15 to 19 Years,age (15 to 19) started smoking daily - daily smoker,years,"[15,20)",15 to 19 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_4,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SMKC_203, cchs2005_i::SMKE_203, [SMK_203]",ICES altered,cont,4,10,20 To 24 Years,age (20 to 24) started smoking daily - daily smoker,years,"[20,25)",20 To 24 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_5,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SMKC_203, cchs2005_i::SMKE_203, [SMK_203]",ICES altered,cont,5,10,25 To 29 Years,age (25 to 29) started smoking daily - daily smoker,years,"[25,30)",25 To 29 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_6,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SMKC_203, cchs2005_i::SMKE_203, [SMK_203]",ICES altered,cont,6,10,30 To 34 Years,age (30 to 34) started smoking daily - daily smoker,years,"[30,35)",30 To 34 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_7,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SMKC_203, cchs2005_i::SMKE_203, [SMK_203]",ICES altered,cont,7,10,35 To 39 Years,age (35 to 39) started smoking daily - daily smoker,years,"[35,40)",35 To 39 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_8,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SMKC_203, cchs2005_i::SMKE_203, [SMK_203]",ICES altered,cont,8,10,40 To 44 Years,age (40 to 44) started smoking daily - daily smoker,years,"[40,45)",40 To 44 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_9,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SMKC_203, cchs2005_i::SMKE_203, [SMK_203]",ICES altered,cont,9,10,45 To 49 Years,age (45 to 49) started smoking daily - daily smoker,years,"[45,50)",45 To 49 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_10,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SMKC_203, cchs2005_i::SMKE_203, [SMK_203]",ICES altered,cont,10,10,50 Years or more,age (50 or more) started smoking daily - daily smoker,years,"[50,84]",50 Years or more,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_NA::a,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SMKC_203, cchs2005_i::SMKE_203, [SMK_203]",ICES altered,cont,NA::a,10,not applicable,not applicable,years,996,not applicable,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_NA::b,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SMKC_203, cchs2005_i::SMKE_203, [SMK_203]",ICES altered,cont,NA::b,10,missing,missing,years,"[997,999]",don't know (97); refusal (98); not stated (99),agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_A,SMKG203_A_cat10_NA::b,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SMKC_203, cchs2005_i::SMKE_203, [SMK_203]",ICES altered,cont,NA::b,10,missing,missing,years,else,else,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203 ",ICES altered,cat,8,N/A,agecigd,converted categorical age (5 to 11) started smoking daily - daily smoker,years,1,5 To 11 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203 ",ICES altered,cat,13,N/A,agecigd,converted categorical age (12 to 14) started smoking daily - daily smoker,years,2,12 To 14 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203 ",ICES altered,cat,17,N/A,agecigd,converted categorical age (15 to 19) started smoking daily - daily smoker,years,3,15 to 19 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203 ",ICES altered,cat,22,N/A,agecigd,converted categorical age (20 to 24) started smoking daily - daily smoker,years,4,20 To 24 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203 ",ICES altered,cat,27,N/A,agecigd,converted categorical age (25 to 29) started smoking daily - daily smoker,years,5,25 To 29 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203 ",ICES altered,cat,32,N/A,agecigd,converted categorical age (30 to 34) started smoking daily - daily smoker,years,6,30 To 34 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203 ",ICES altered,cat,37,N/A,agecigd,converted categorical age (35 to 39) started smoking daily - daily smoker,years,7,35 To 39 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203 ",ICES altered,cat,42,N/A,agecigd,converted categorical age (40 to 44) started smoking daily - daily smoker,years,8,40 To 44 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203 ",ICES altered,cat,47,N/A,agecigd,converted categorical age (45 to 49) started smoking daily - daily smoker,years,9,45 To 49 Years,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203 ",ICES altered,cat,55,N/A,agecigd,converted categorical age (50 or more) started smoking daily - daily smoker,years,10,50 Years or more,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203 ",ICES altered,cat,NA::a,N/A,not applicable,not applicable,years,96,not applicable,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203 ",ICES altered,cat,NA::b,N/A,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_cont,N/A,cont,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203 ",ICES altered,cat,NA::b,N/A,missing,missing,years,else,else,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_cont,N/A,cont,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i , cchs2015_2016_i, cchs2017_2018_i"," cchs2003_i::SMKC_203 , cchs2005_i::SMKE_203, cchs2015_2016_i::SMK_040, cchs2017_2018_i::SMK_040, [SMK_203]",ICES altered,cont,copy,N/A,agecigd,agecigd,years,"[5,84]",agecigd,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_cont,N/A,cont,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i , cchs2015_2016_i, cchs2017_2018_i"," cchs2003_i::SMKC_203 , cchs2005_i::SMKE_203, cchs2015_2016_i::SMK_040, cchs2017_2018_i::SMK_040, [SMK_203]",ICES altered,cont,NA::a,N/A,not applicable,not applicable,years,996,not applicable,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_cont,N/A,cont,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i , cchs2015_2016_i, cchs2017_2018_i"," cchs2003_i::SMKC_203 , cchs2005_i::SMKE_203, cchs2015_2016_i::SMK_040, cchs2017_2018_i::SMK_040, [SMK_203]",ICES altered,cont,NA::b,N/A,missing,missing,years,"[997,999]",don't know (997); refusal (998); not stated (999),agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG203_cont,N/A,cont,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i , cchs2015_2016_i, cchs2017_2018_i"," cchs2003_i::SMKC_203 , cchs2005_i::SMKE_203, cchs2015_2016_i::SMK_040, cchs2017_2018_i::SMK_040, [SMK_203]",ICES altered,cont,NA::b,N/A,missing,missing,years,else,else,agecigd,Age started to smoke daily - daily smoker (G),,, +SMKG207_A,SMKG207_A_cat10_1,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207, cchs2001_i::SMKAG207",ICES altered,cat,1,10,5 To 11 Years,age (5 to 11) started smoking daily - daily smoker,years,1,5 To 11 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_2,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207, cchs2001_i::SMKAG207",ICES altered,cat,2,10,12 To 14 Years,age (12 to 14) started smoking daily - daily smoker,years,2,12 To 14 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_3,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207, cchs2001_i::SMKAG207",ICES altered,cat,3,10,15 to 19 Years,age (15 to 19) started smoking daily - daily smoker,years,3,15 to 19 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_4,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207, cchs2001_i::SMKAG207",ICES altered,cat,4,10,20 To 24 Years,age (20 to 24) started smoking daily - daily smoker,years,4,20 To 24 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_5,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207, cchs2001_i::SMKAG207",ICES altered,cat,5,10,25 To 29 Years,age (25 to 29) started smoking daily - daily smoker,years,5,25 To 29 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_6,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207, cchs2001_i::SMKAG207",ICES altered,cat,6,10,30 To 34 Years,age (30 to 34) started smoking daily - daily smoker,years,6,30 To 34 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_7,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207, cchs2001_i::SMKAG207",ICES altered,cat,7,10,35 To 39 Years,age (35 to 39) started smoking daily - daily smoker,years,7,35 To 39 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_8,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207, cchs2001_i::SMKAG207",ICES altered,cat,8,10,40 To 44 Years,age (40 to 44) started smoking daily - daily smoker,years,8,40 To 44 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_9,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207, cchs2001_i::SMKAG207",ICES altered,cat,9,10,45 To 49 Years,age (45 to 49) started smoking daily - daily smoker,years,9,45 To 49 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_10,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207, cchs2001_i::SMKAG207",ICES altered,cat,10,10,50 Years or more,age (50 or more) started smoking daily - daily smoker,years,10,50 Years or more,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_NA::a,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207, cchs2001_i::SMKAG207",ICES altered,cat,NA::a,10,not applicable,not applicable,years,96,not applicable,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207, cchs2001_i::SMKAG207",ICES altered,cat,NA::b,10,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_NA::b,cat,"cchs2001_p, cchs2003_p, cchs2001_i","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207, cchs2001_i::SMKAG207",ICES altered,cat,NA::b,10,missing,missing,years,else,else,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_1,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cont,1,10,5 To 11 Years,age (5 to 11) started smoking daily - daily smoker,years,"[5,12)",5 To 11 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_2,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cont,2,10,12 To 14 Years,age (12 to 14) started smoking daily - daily smoker,years,"[12,15)",12 To 14 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_3,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cont,3,10,15 to 19 Years,age (15 to 19) started smoking daily - daily smoker,years,"[15,20)",15 To 19 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_4,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cont,4,10,20 To 24 Years,age (20 to 24) started smoking daily - daily smoker,years,"[20,25)",20 To 24 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_5,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cont,5,10,25 To 29 Years,age (25 to 29) started smoking daily - daily smoker,years,"[25,30)",25 To 29 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_6,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cont,6,10,30 To 34 Years,age (30 to 34) started smoking daily - daily smoker,years,"[30,35)",30 To 34 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_7,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cont,7,10,35 To 39 Years,age (35 to 39) started smoking daily - daily smoker,years,"[35,40)",35 To 39 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_8,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cont,8,10,40 To 44 Years,age (40 to 44) started smoking daily - daily smoker,years,"[40,45)",40 To 44 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_9,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cont,9,10,45 To 49 Years,age (45 to 49) started smoking daily - daily smoker,years,"[45,50)",45 To 49 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_10,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cont,10,10,50 Years or more,age (50 or more) started smoking daily - daily smoker,years,"[50,80]",50 Years or more,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_NA::a,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cont,NA::a,10,not applicable,not applicable,years,996,not applicable,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_NA::b,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cont,NA::b,10,missing,missing,years,"[997,999]",don't know (997); refusal (998); not stated (999),agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_A,SMKG207_A_cat10_NA::b,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cont,NA::b,10,missing,missing,years,else,else,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_1,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,1,11,5 To 11 Years,age (5 to 11) started smoking daily - former daily smoker,years,1,5 To 11 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_2,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,2,11,12 To 14 Years,age (12 to 14) started smoking daily - former daily smoker,years,2,12 To 14 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_3,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,3,11,15 To 17 Years,age (15 to 17) started smoking daily - former daily smoker,years,3,15 To 17 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_4,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,4,11,18 To 19 Years,age (18 to 19) started smoking daily - former daily smoker,years,4,18 To 19 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_5,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,5,11,20 To 24 Years,age (20 to 24) started smoking daily - former daily smoker,years,5,20 To 24 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_6,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,6,11,25 To 29 Years,age (25 to 29) started smoking daily - former daily smoker,years,6,25 To 29 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_7,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,7,11,30 To 34 Years,age (30 to 34) started smoking daily - former daily smoker,years,7,30 To 34 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_8,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,8,11,35 To 39 Years,age (35 to 39) started smoking daily - former daily smoker,years,8,35 To 39 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_9,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,9,11,40 To 44 Years,age (40 to 44) started smoking daily - former daily smoker,years,9,40 To 44 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_10,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,10,11,45 To 49 Years,age (45 to 49) started smoking daily - former daily smoker,years,10,45 To 49 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_11,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,11,11,50 Years or more,age (50 plus) started smoking daily - former daily smoker,years,11,50 Years or more,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_NA::a,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,NA::a,11,not applicable,not applicable,years,96,not applicable,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,NA::b,11,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_NA::b,cat,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,NA::b,11,missing,missing,years,else,else,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_1,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cat,1,11,5 To 11 Years,age (5 to 11) started smoking daily - former daily smoker,years,"[5,12)",5 To 11 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_2,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cat,2,11,12 To 14 Years,age (12 to 14) started smoking daily - former daily smoker,years,"[12,15)",12 To 14 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_3,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cat,3,11,15 To 17 Years,age (15 to 17) started smoking daily - former daily smoker,years,"[15,18)",15 To 17 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_4,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cat,4,11,18 To 19 Years,age (18 to 19) started smoking daily - former daily smoker,years,"[18,20)",18 To 19 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_5,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cat,5,11,20 To 24 Years,age (20 to 24) started smoking daily - former daily smoker,years,"[20,25)",20 To 24 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_6,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cat,6,11,25 To 29 Years,age (25 to 29) started smoking daily - former daily smoker,years,"[25,30)",25 To 29 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_7,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cat,7,11,30 To 34 Years,age (30 to 34) started smoking daily - former daily smoker,years,"[30,35)",30 To 34 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_8,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cat,8,11,35 To 39 Years,age (35 to 39) started smoking daily - former daily smoker,years,"[35,40)",35 To 39 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_9,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cat,9,11,40 To 44 Years,age (40 to 44) started smoking daily - former daily smoker,years,"[40,45)",40 To 44 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_10,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cat,10,11,45 To 49 Years,age (45 to 49) started smoking daily - former daily smoker,years,"[45,50)",45 To 49 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_11,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cat,11,11,50 Years or more,age (50 plus) started smoking daily - former daily smoker,years,"[50,80]",50 Years or more,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_NA::a,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cat,NA::a,11,not applicable,not applicable,years,996,not applicable,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_NA::b,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cat,NA::b,11,missing,missing,years,"[997,999]",don't know (997); refusal (998); not stated (999),agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_B,SMKG207_B_cat11_NA::b,cat,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cat,NA::b,11,missing,missing,years,else,else,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",,cat,8,N/A,agecigd,converted categorical age (5 to 11) started smoking daily - daily smoker,years,1,5 To 11 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",,cat,13,N/A,agecigd,converted categorical age (12 to 14) started smoking daily - daily smoker,years,2,12 To 14 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",,cat,17,N/A,agecigd,converted categorical age (15 to 19) started smoking daily - daily smoker,years,3,15 to 19 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",,cat,22,N/A,agecigd,converted categorical age (20 to 24) started smoking daily - daily smoker,years,4,20 To 24 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",,cat,27,N/A,agecigd,converted categorical age (25 to 29) started smoking daily - daily smoker,years,5,25 To 29 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",,cat,32,N/A,agecigd,converted categorical age (30 to 34) started smoking daily - daily smoker,years,6,30 To 34 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",,cat,37,N/A,agecigd,converted categorical age (35 to 39) started smoking daily - daily smoker,years,7,35 To 39 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",,cat,42,N/A,agecigd,converted categorical age (40 to 44) started smoking daily - daily smoker,years,8,40 To 44 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",,cat,47,N/A,agecigd,converted categorical age (45 to 49) started smoking daily - daily smoker,years,9,45 To 49 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",,cat,55,N/A,agecigd,converted categorical age (50 or more) started smoking daily - daily smoker,years,10,50 Years or more,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",,cat,NA::a,N/A,not applicable,not applicable,years,96,not applicable,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",,cat,NA::b,N/A,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2001_p, cchs2003_p","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207",,cat,NA::b,N/A,missing,missing,years,else,else,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,8,N/A,agecigd,converted categorical age (5 to 11) started smoking daily - daily smoker,years,1,5 To 11 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,13,N/A,agecigd,converted categorical age (12 to 14) started smoking daily - daily smoker,years,2,12 To 14 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,16,N/A,agecigd,converted categorical age (15 to 17) started smoking daily - daily smoker,years,3,15 To 17 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,18.5,N/A,agecigd,converted categorical age (18 to 19) started smoking daily - daily smoker,years,4,18 To 19 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,22,N/A,agecigd,converted categorical age (20 to 24) started smoking daily - daily smoker,years,5,20 To 24 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,27,N/A,agecigd,converted categorical age (25 to 29) started smoking daily - daily smoker,years,6,25 To 29 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,32,N/A,agecigd,converted categorical age (30 to 34) started smoking daily - daily smoker,years,7,30 To 34 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,37,N/A,agecigd,converted categorical age (35 to 39) started smoking daily - daily smoker,years,8,35 To 39 Years,agecigfd,Age started to smoke daily - former daily smoker,Missing 2001 Data,, +SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,42,N/A,agecigd,converted categorical age (40 to 44) started smoking daily - daily smoker,years,9,40 To 44 Years,agecigfd,Age started to smoke daily - former daily smoker,Missing 2001 Data,, +SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,47,N/A,agecigd,converted categorical age (45 to 49) started smoking daily - daily smoker,years,10,45 To 49 Years,agecigfd,Age started to smoke daily - former daily smoker,Missing 2001 Data,, +SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,55,N/A,agecigd,converted categorical age (50 plus) started smoking daily - daily smoker,years,11,50 Years or more,agecigfd,Age started to smoke daily - former daily smoker,Missing 2001 Data,, +SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,NA::a,N/A,not applicable,not applicable,years,96,not applicable,agecigfd,Age started to smoke daily - former daily smoker,Missing 2001 Data,, +SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,NA::b,N/A,missing,missing,years,"[97,99]",don't know (97); refusal (98); not stated (99),agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p","cchs2005_p::SMKEG207, [SMKG207]",,cat,NA::b,N/A,missing,missing,years,else,else,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cont,copy,N/A,agecigd,agecigd,years,"[5,80]",agecigfd,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cont,NA::a,N/A,not applicable,not applicable,years,996,not applicable,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cont,NA::b,N/A,missing,missing,years,"[997,999]",don't know (997); refusal (998); not stated (999),agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]",ICES altered,cont,NA::b,N/A,missing,missing,years,else,else,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p, cchs2015_2016_i, cchs2017_2018_i","DerivedVar::[SMK_030, SMKG040]",,N/A,Func::SMKG207_fun,N/A,N/A,N/A,N/A,N/A,N/A,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p, cchs2015_2016_i, cchs2017_2018_i","DerivedVar::[SMK_030, SMKG040]",,N/A,8,N/A,agecigd,converted categorical age (5 to 11) started smoking daily - daily smoker,years,N/A,5 To 11 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p, cchs2015_2016_i, cchs2017_2018_i","DerivedVar::[SMK_030, SMKG040]",,N/A,13,N/A,agecigd,converted categorical age (12 to 14) started smoking daily - daily smoker,years,N/A,12 To 14 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p, cchs2015_2016_i, cchs2017_2018_i","DerivedVar::[SMK_030, SMKG040]",,N/A,16,N/A,agecigd,converted categorical age (15 to 17) started smoking daily - daily smoker,years,N/A,15 To 17 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p, cchs2015_2016_i, cchs2017_2018_i","DerivedVar::[SMK_030, SMKG040]",,N/A,18.5,N/A,agecigd,converted categorical age (18 to 19) started smoking daily - daily smoker,years,N/A,18 To 19 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p, cchs2015_2016_i, cchs2017_2018_i","DerivedVar::[SMK_030, SMKG040]",,N/A,22,N/A,agecigd,converted categorical age (20 to 24) started smoking daily - daily smoker,years,N/A,20 To 24 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p, cchs2015_2016_i, cchs2017_2018_i","DerivedVar::[SMK_030, SMKG040]",,N/A,27,N/A,agecigd,converted categorical age (25 to 29) started smoking daily - daily smoker,years,N/A,25 To 29 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p, cchs2015_2016_i, cchs2017_2018_i","DerivedVar::[SMK_030, SMKG040]",,N/A,32,N/A,agecigd,converted categorical age (30 to 34) started smoking daily - daily smoker,years,N/A,30 To 34 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p, cchs2015_2016_i, cchs2017_2018_i","DerivedVar::[SMK_030, SMKG040]",,N/A,37,N/A,agecigd,converted categorical age (35 to 39) started smoking daily - daily smoker,years,N/A,35 To 39 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p, cchs2015_2016_i, cchs2017_2018_i","DerivedVar::[SMK_030, SMKG040]",,N/A,42,N/A,agecigd,converted categorical age (40 to 44) started smoking daily - daily smoker,years,N/A,40 To 44 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p, cchs2015_2016_i, cchs2017_2018_i","DerivedVar::[SMK_030, SMKG040]",,N/A,47,N/A,agecigd,converted categorical age (45 to 49) started smoking daily - daily smoker,years,N/A,45 To 49 Years,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p, cchs2015_2016_i, cchs2017_2018_i","DerivedVar::[SMK_030, SMKG040]",,N/A,55,N/A,agecigd,converted categorical age (50 plus) started smoking daily - daily smoker,years,N/A,50 Years or more,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p, cchs2015_2016_i, cchs2017_2018_i","DerivedVar::[SMK_030, SMKG040]",,N/A,NA::a,N/A,not applicable,not applicable,years,N/A,not applicable,agecigfd,Age started to smoke daily - former daily smoker,,, +SMKG207_cont,N/A,cont,"cchs2015_2016_p, cchs2017_2018_p, cchs2015_2016_i, cchs2017_2018_i","DerivedVar::[SMK_030, SMKG040]",,N/A,NA::b,N/A,missing,missing,years,N/A,missing,agecigfd,Age started to smoke daily - former daily smoker,,, \ No newline at end of file diff --git a/inst/extdata/demport/variables_DemPoRT.csv.bak b/inst/extdata/demport/variables_DemPoRT.csv.bak new file mode 100644 index 0000000..0face89 --- /dev/null +++ b/inst/extdata/demport/variables_DemPoRT.csv.bak @@ -0,0 +1,70 @@ +variable,label,labelLong,section,subject,variableType,units,ICES confirmation,databaseStart,variableStart,description +ADL_01,Help preparing meals,Needs help - preparing meals,Health status,ADL,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6A, cchs2003_p::RACC_6A, cchs2005_p::RACE_6A, cchs2007_2008_p::RAC_6A, cchs2015_2016_p::ADL_005, cchs2017_2018_p::ADL_005, cchs2001_i::RACA_6A, cchs2003_i::RACC_6A, cchs2005_i::RACE_6A, [ADL_01]", +ADL_02,Help appointments/errands,Needs help - getting to appointments/errands,Health status,ADL,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6B, cchs2003_p::RACC_6B1, cchs2005_p::RACE_6B1, cchs2007_2008_p::RAC_6B1, cchs2001_i::RACA_6B, cchs2003_i::RACC_6B1, cchs2005_i::RACE_6B1, cchs2007_2008_i::RAC_6B1, [ADL_02]", +ADL_03,Help housework,Needs help - doing housework,Health status,ADL,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6C, cchs2003_p::RACC_6C, cchs2005_p::RACE_6C, cchs2007_2008_p::RAC_6C, cchs2001_i::RACA_6C, cchs2003_i::RACC_6C, cchs2005_i::RACE_6C, cchs2007_2008_i::RAC_6C,[ADL_03]", +ADL_04,Help personal care,Needs help - personal care,Health status,ADL,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6E, cchs2003_p::RACC_6E, cchs2005_p::RACE_6E, cchs2007_2008_p::RAC_6E, cchs2001_i::RACA_6E, cchs2003_i::RACC_6E, cchs2005_i::RACE_6E, cchs2007_2008_i::RAC_6E,[ADL_04]", +ADL_05,Help move inside house,Needs help - moving about inside house,Health status,ADL,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::RACA_6F, cchs2003_p::RACC_6F, cchs2005_p::RACE_6F, cchs2007_2008_p::RAC_6F, cchs2001_i::RACA_6F, cchs2003_i::RACC_6F, cchs2005_i::RACE_6F, cchs2007_2008_i::RAC_6F,[ADL_05]", +ADL_06,Help personal finances,Needs help - looking after finances,Health status,ADL,Categorical,N/A,Yes,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2003_p::RACC_6G, cchs2005_p::RACE_6G, cchs2007_2008_p::RAC_6G, cchs2003_i::RACC_6G, cchs2005_i::RACE_6G, cchs2007_2008_i::RAC_6G, [ADL_06]", +ADL_07,Help heavy household chores,Needs help - heavy household chores,Health status,ADL,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_p::RACA_6D, cchs2003_p::RACC_6D, cchs2005_p::RACE_6D, cchs2001_i::RACA_6D, cchs2003_i::RACC_6D, cchs2005_i::RACE_6D", +ADL_der,Derived help tasks,Derived needs help with tasks,Health status,ADL,Categorical,N/A,,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05]", +ADL_score_5,ADL score ,"Derived using the ADL variables common to all cycles from 2001 to 2014 (ADL_01, ADL_02, ADL_03, ADL_04, ADL_05) to represent the number of tasks that an individual needs help with.",Health status,ADL,Categorical,N/A,,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05]", +ADL_score_6,ADL score ,"Derived using the ADL variables common to all cycles from 2001 to 2014 (ADL_01, ADL_02, ADL_03, ADL_04, ADL_05, ADL_06) to represent the number of tasks that an individual needs help with.",Health status,ADL,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05, ADL_06]", +ALCDTTM,Drinker type (last 12 months),Type of drinker (12 months),Health behaviour,Alcohol,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::ALCADTYP, cchs2003_p::ALCCDTYP, cchs2005_p::ALCEDTYP, cchs2015_2016_p::ALCDVTTM, cchs2017_2018_p::ALCDVTTM, cchs2001_i::ALCADTYP, cchs2003_i::ALCCDTYP, cchs2005_i::ALCEDTYP, cchs2015_2016_i::ALCDVTTM, cchs2017_2018_i::ALCDVTTM, [ALCDTTM]", +ALCDTYP_A,Former drinker,Type of drinker,Health behaviour,Alcohol,Categorical,N/A,Yes,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, 2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::ALCADTYP, cchs2003_i::ALCCDTYP, cchs2005_i::ALCEDTYP, cchs2015_2016_i::ALCDVTTM, cchs2017_2018_i::ALCDVTTM, [ALCDTTM]", +ALWDWKY,Drinks last week,Weekly consumption of alcohol,Health behaviour,Alcohol,Continuous,drinks/week,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::ALCADWKY, cchs2003_p::ALCCDWKY, cchs2005_p::ALCEDWKY, cchs2015_2016_p::ALWDVWKY, cchs2017_2018_p::ALWDVWKY, cchs2001_i::ALCADWKY, cchs2003_i::ALCCDWKY, cchs2005_i:: ALCEDWKY, cchs2015_2016_i::ALWDVWKY, cchs2017_2018_i::ALWDVWKY, [ALWDWKY]", +CCC_071,Hypertension,Do you have high blood pressure?,Health status,Chronic condition,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i ","cchs2001_p::CCCA_071, cchs2003_p::CCCC_071, cchs2005_p::CCCE_071, cchs2015_2016_p::CCC_065, cchs2017_2018_p::CCC_065, cchs2001_i::CCCA_071, cchs2003_i::CCCC_071, cchs2005_i::CCCE_071, cchs2015_2016_i::CCC_065, cchs2017_2018_i::CCC_065,[CCC_071]", +CCC_091,COPD/Emphysema/Bronchitis,"Do you have COPD (eg bronchitis, emphysema)?",Health status,Chronic condition,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::CCCA_91B, cchs2003_p::CCCC_91B, cchs2015_2016_p::CCC_030, cchs2017_2018_p::CCC_030, cchs2001_i::CCCA_91B, cchs2003_i::CCCC_91B, cchs2005_i::CCCE_91F, cchs2007_2008_i::CCC_91F, cchs2015_2016_i::CCC_030, cchs2017_2018_i::CCC_030, [CCC_091]", +CCC_101,Diabetes,Do you have diabetes?,Health status,Chronic condition,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::CCCA_101, cchs2003_p::CCCC_101, cchs2005_p::CCCE_101, cchs2015_2016_p::CCC_095, cchs2017_2018_p::CCC_095, cchs2001_i::CCCA_101, cchs2003_i::CCCC_101, cchs2005_i::CCCE_101, cchs2015_2016_i::CCC_095, cchs2017_2018_i::CCC_095,[CCC_101]", +CCC_111,Epilepsy,Do you have epilepsy?,Health status,Chronic condition,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_p::CCCA_111, cchs2003_p::CCCC_111, cchs2005_p::CCCE_111, cchs2001_i::CCCA_111, cchs2003_i::CCCC_111, cchs2005_i::CCCE_111", +CCC_121,Heart Disease,Do you have heart disease?,Health status,Chronic condition,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::CCCA_121, cchs2003_p::CCCC_121, cchs2005_p::CCCE_121, cchs2015_2016_p::CCC_085, cchs2017_2018_p::CCC_085, cchs2001_i::CCCA_121, cchs2003_i::CCCC_121, cchs2005_i::CCCE_121, cchs2015_2016_i::CCC_085, cchs2017_2018_i::CCC_085,[CCC_121]", +CCC_151,Stroke,Do you suffer from effects of stroke?,Health status,Chronic condition,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, ccsh2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::CCCA_151, cchs2003_p::CCCC_151, cchs2005_p::CCCE_151, cchs2015_2016_p::CCC_090, cchs2017_2018_p::CCC_090, cchs2001_i::CCCA_151, cchs2003_i::CCCC_151, cchs2005_i::CCCE_151, cchs2015_2016_i::CCC_090, cchs2017_2018_i::CCC_090,[CCC_151]", +CCC_280,Mood disorder,Do you have a mood disorder?,Health status,Chronic condition,Categorical,N/A,Yes,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_p::CCCC_280, cchs2005_p::CCCE_280, cchs2015_2016_p::CCC_195, cchs2017_2018_p::CCC_195, cchs2003_i::CCCC_280, cchs2005_i::CCCE_280, cchs2015_2016_i::CCC_195, cchs2017_2018_i::CCC_195, [CCC_280]", +DHH_AGE,Age,Age,Demographics,Age,Continuous,Years,Yes,"cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::DHHA_AGE, cchs2003_i::DHHC_AGE, cchs2005_i::DHHE_AGE, [DHH_AGE]",Continuous age variable for shared files and ICES +DHH_SEX,Sex,Sex,Demographics,Sex,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::DHHA_SEX, cchs2003_p::DHHC_SEX, cchs2005_p::DHHE_SEX, cchs2001_i::DHHA_SEX, cchs2003_i::DHHC_SEX, cchs2005_i::DHHE, [DHH_SEX]", +DHH_MS,Marital status,Marital status,Sociodemographics,Marital Status,Categorical,N/A,Yes,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::DHHA_MS, cchs2003_i::DHHC_MS, cchs2005_i::DHHE_MS, [DHH_MS]",Categorical Marital Status +DHH_MS_A,Marital status,Marital status,Sociodemographics,Marital Status,Categorical,N/A,Yes,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::DHHA_MS, cchs2003_i::DHHC_MS, cchs2005_i::DHHE_MS, [DHH_MS]",Categorical Marital Status with DemPoRt specific categories +EDUDR04,Highest education,Highest level/education - 4 categories,Sociodemographics,Education,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::EDUADR04, cchs2003_p::EDUCDR04, cchs2005_p::EDUEDR04, cchs2001_i::EDUADR04, cchs2003_i::EDUCDR04, cchs2005_i::EDUEDR04, cchs2015_2016_i::EHG2DVR3, cchs2017_2018_i::EHG2DVR3, [EDUDR04]", +FVCDJUI,Juice consumption,Daily consumption - fruit juice (D),Health behaviour,Diet,Continuous,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs20013_2014_i, cchs2015_2016_i","cchs2001_p::FVCADJUI, cchs2003_p::FVCCDJUI, cchs2005_p::FVCEDJUI, cchs2015_2016_p::FVCDVJUI, cchs2017_2018_p::FVCDVJUI, cchs2001_i::FVCADJUI, cchs2003_i::FVCCDJUI, cchs2005_i::FVCEDJUI, cchs2015_2016_i::FVCDVJUI, [FVCDJUI]", +FVCDPOT,Potato consumption,Daily consumption - potatoes (D),Health behaviour,Diet,Continuous,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs20013_2014_i, cchs2015_2016_i","cchs2001_p::FVCADPOT, cchs2003_p::FVCCDPOT, cchs2005_p::FVCEDPOT, cchs2015_2016_p::FVCDVPOT, cchs2017_2018_p::FVCDVPOT,cchs2001_i::FVCADPOT, cchs2003_i::FVCCDPOT, cchs2005_i::FVCEDPOT, cchs2015_2016_i::FVCDVPOT, [FVCDPOT]", +FVCDTOT,Total fruit/veg consumption,Daily consumptoin - total fruits and veg. - (D),Health behaviour,Diet,Continuous,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs20013_2014_i, cchs2015_2016_i","cchs2001_p::FVCADTOT, cchs2003_p::FVCCDTOT, cchs2005_p::FVCEDTOT, cchs2015_2016_p::FVCDVTOT, cchs2017_2018_p::FVCDVTOT, cchs2001_i::FVCADTOT, cchs2003_i::FVCCDTOT, cchs2005_i::FVCEDTOT, cchs2015_2016_i::FVCDVTOT,[FVCDTOT]", +GEN_01,Self-perceived health,Self-perceived health,Health status,Self-perceived health,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_01, cchs2003_p::GENC_01, cchs2005_p::GENE_01, cchs2015_2016_p::GEN_005, cchs2017_2018_p::GEN_005, cchs2001_i::GENA_i, cchs2003_i::GENC_01, cchs2005_i::GENE_01, cchs2015_2016_i::GEN_005, cchs2017_2018_i::GEN_005, [GEN_01]", +GEN_07,Self-perceived life stress,Self-perceived life stress,Health status,Mental health,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_07, cchs2003_p::GENC_07, cchs2005_p::GENE_07, cchs2015_2016_p::GEN_020, cchs2017_2018_p:: GEN_020, cchs2001_i::GENA_07, cchs2003_i::GENC_07, cchs2005_i::GENE_07, cchs2015_2016_i::GEN_020, cchs2017_2018_i:: GEN_020, [GEN_07]", +GEN_10,Sense of belonging,Sense of belonging in the community,Health status,Mental health,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::GENA_10, cchs2003_p::GENC_10, cchs2005_p::GENE_10, cchs2015_2016_p::GEN_030, cchs2017_2018_p::GEN_030, cchs2001_i::GENA_01, cchs2003_i::GENC_01, cchs2005_i::GENE_01, cchs2015_2016_i::GEN_030, cchs2017_2018_i::GEN_030, [GEN_10]", +HUI06,HUI Hearing ability - in a group without a hearing aid,Hearing ability ,Health status,Health utility index,Categorical,N/A,Yes,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_06, cchs2003_i::HUAC_06, [HUI_06]", +HUI07,HUI Hearing ability - in a group with a hearing aid,Hearing ability ,Health status,Health utility index,Categorical,N/A,Yes,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_07, cchs2003_i::HUIC_07, [HUI_07]", +HUI07A,HUI Hearing ability -able to hear,Hearing ability ,Health status,Health utility index,Categorical,N/A,Yes,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i, cchs_2017_2018_i","cchs2001_i::HUIA_07A, cchs2003_i::HUIC_07A, cchs2017_2018_i::WDM_101, [HUI_07A]", +HUI08,HUI Hearing ability - able to hear in a quiet room without hearing aid,Hearing ability ,Health status,Health utility index,Categorical,N/A,Yes,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_08, cchs2003_i::HUIC_08, [HUI_08]", +HUI09,HUI Hearing ability - able to hear in a quiet room with hearing aid,Hearing ability ,Health status,Health utility index,Categorical,N/A,Yes,"cchs2001_i, cchs2003_i, cchs_2009_2010_i, cchs2013_2014_i","cchs2001_i::HUIA_08, cchs2003_i::HUIC_08, [HUI_08]", +HWTGBMI,BMI,"BMI / self-report - (D,G)",Health status,BMI,Continuous,kg/m2,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::HWTAGBMI, cchs2003_p::HWTCGBMI, cchs2005_p::HWTEGBMI, cchs2015_2016_p::HWTDGBMI, cchs2017_2018_p::HWTDGBMI, cchs2009_s::HWTDBMI, cchs2010_s::HWTDBMI, cchs2012_s::HWTDBMI, cchs2001_i::HWTAGBMI, [HWTGBMI]", +HWTDBMI,BMI,"BMI / self-report - (D,G)",Health status,BMI,Continuous,kg/m2,Yes,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::HWTADBMI, cchs2003_i::HWTCDBMI, cchs2005_i::HWTEDBMI, cchs2015_2016_i::HWTDVBMI, cchs2017_2018_i::HWTDVBMI, [HWTDBMI]", +HWTDBMI_der,BMI,"BMI / self-report - (D,G)",Health status,BMI,Continuous,kg/m2,Yes,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","DerivedVar::[HWTDHTM, HWTDWTK]", +HWTDBMI_der_cat4,BMI,"BMI / self-report - (D,G)",Health status,BMI,Categorical,kg/m2,Yes,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i",DerivedVar::HWTDBMI_der_cat4, +HWTDHTM,Height,Height (metres)/self-reported - (D),Health status,Height,Continuous,meters,Yes,"cchs_2001_i, cchs_2003_i, cchs_2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_i::HWTADHTM, cchs_2003_i::HWTCDHTM, cchs_2005_i::HWTEDHTM, 2015_2016_i::HWTDVHTM, cchs2017_2018_i::HTWDVHTM, [HWTDHTM]", +HWTDWTK,Weight,Weight - kilograms (D),Health status,Weight,Continuous,kg,Yes,"cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, ccsh2015_2016_i, cchs2017_2018_i","cchs2001_i::HWTADWTK, cchs2003_i::HWTCDWTK, cchs2005_i::HWTEDWTK, cchs2015_2016_i::HWTDVWTK, cchs2017_2018_i::HWTDVWTK, [HWTDWTK]", +PACFLEI,Leisure physical activites,Leisure physical activity,Health behaviour,Exercise,Categorical,N/A,Yes,"cchs2001_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_i::PACAFLEI, cchs2005_i::PACEFLEI, [PACFLEI]", +RAC_6D,Needs help - heavy housework,Needs help - heavy housework,Health status,Health status,Categorical,N/A,Yes,"cchs2001_i, cchs2003_i, cchs2005_i","cchs2001_i::RACA_6D, cchs2003_i::RACC_6D, cchs2005_i::RACE_6D", +SDCFIMM,Immigrant status,Immigrant Status (D),Sociodemographics,Migration,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i cchs2012_s","cchs2001_p::SDCAFIMM, cchs2003_p::SDCCFIMM, cchs2005_p::SDCEFIMM, cchs2015_2016_p::SDCDVIMM, cchs2017_2018_p::SDCDVIMM, cchs2001_i::SDCAFIMM, cchs2003_i::SDCCFIMM, cchs2005_i::SDCEFIMM, cchs2015_2016::SDCDVIMM, cchs2017_2018_i::SDCDVIMM, [SDCFIMM]", +SDCGCGT,Ethnicity,"Cultural or racial origin - (D, G)",Sociodemographics,Ethnicity,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2001_i, cchs2005_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SDCAGRAC, cchs2003_p::SDCCGRAC, cchs2005_p::SDCEGCGT, cchs2015_2016_p::SDCDGCGT, cchs2017_2018_p::SDCDGCGT, cchs2001_i::SDCAGRAC, cchs2003_i::SDCCDRAC, cchs_2005_i:: SDCEGCGT, cchs2015_2016_i::SDCDVCGT, cchs2017_2018_i::SDCDVCGT, [SDCGCGT]", +SDCDGT_A,Ethnicity,Cultural or racial origin - (D),Sociodemographics,Ethnicity,Categorical,N/A,Yes,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i ","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, cchs2015_2016_i::SDCDVCGT, cchs2017_2018_i::SDCDVCGT, [SDCDCGT] ", +SDCDGT_B,Ethnicity,Cultural origin,Sociodemographics,Ethnicity,Categorical,N/A,Yes,"cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_i::SDCCDRAC, cchs2005_i::SDCEDCGT, cchs2015_2016_i::SDCDVCGT, cchs2017_2018_i::SDCDVCGT, [SDCDCGT] ", +SLP_02,Trouble sleeping,Freq. - trouble sleeping,Health behaviour,Sleep,Categorical,N/A,Yes,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2012_s, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2015_2016_p::SLP_010, cchs2017_2018_p::SLP_010, cchs2015_2016_i::SLP_010, [SLP_02]", +SLP_02_A,Trouble sleeping,Freq. - trouble sleeping,Health behaviour,Sleep,Categorical,N/A,Yes,"cchs2001_p, cchs2001_i",[GENA_04], +SLP_03,Sleep refreshing,Freq. - find sleep refreshing,Health behaviour,Sleep,Categorical,N/A,Yes,"cchs2007_2008_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2012_s, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i","cchs2015_2016_p::SLP_015, cchs2017_2018_p::SLP_015, cchs2015_2016_i::SLP_015, [SLP_03]", +SLP_03_A,Sleep refreshing,Freq. - find sleep refreshing,Health behaviour,Sleep,Categorical,N/A,Yes,"cchs2001_p, cchs2001_i",[GENA_05], +SLPG01_B,Hours sleep,No./hours spent sleeping each night,Health behaviour,Sleep,Categorical,N/A,Yes,"cchs2011_2012_i, cchs2013_2014_i",[SLPG01], +SLPG01_C,Hours sleep,No./hours spent sleeping each night,Health behaviour,Sleep,Categorical,N/A,Yes,"cchs2001_i, cchs2015_2016_i","cchs2001_i::GENA_03, cchs2015_2016_i::SLP_009", +SMK_01A,s100,"In lifetime, smoked 100 or more cigarettes",Health behaviour,Smoking,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_01A, cchs2003_p::SMKC_01A, cchs2005_p::SMKE_01A, cchs2015_2016_p::SMK_020, cchs2017_2018_p::SMK_020, cchs2001_i::SMKA_01A, cchs2003_i::SMKC_01A, cchs2005_i::SMKE_01A, cchs2015_2016_i::SMK_020, cchs2017_2018_i::SMK_020, [SMK_01A]", +SMK_05B,cigdayo,# of cigarettes smoked daily - occasional smoker,Health behaviour,Smoking,Continuous,cigarettes,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_05B, cchs2003_p::SMKC_05B, cchs2005_p::SMKE_05B, cchs2015_2016_p::SMK_050, cchs2017_2018_p::SMK_050, [SMK_05B], cchs2001_1::SMKA_05B, cchs2003_i::SMKC_05B, cchs2005_i::SMKE_05B, cchs2015_2016_i::SMK_050, cchs2017_2018_i::SMK_050, [SMK_05B]", +SMK_05C,Number of days - smoked 1 cigarette or more (occ. smoker),"In the past month, on how many days have you smoked 1 or more cigarettes?",Health behaviour,Smoking,Continuous,days,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_05C, cchs2003_p::SMKC_05C, cchs2005_p::SMKE_05C, cchs2015_2016_p::SMK_055, cchs2017_2018_p::SMK_055, [SMK_05C], cchs2001_i::SMKA_05C, cchs2003_i::SMKC_05C, cchs2005_i::SMKE_05C, cchs2015_2016_i::SMK_055, cchs2017_2018_i::SMK_055, [SMK_05C]", +SMK_09A_cont,stpd,When did you stop smoking daily - former daily,Health behaviour,Smoking,Continuous,Years,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_09A, cchs2003_p::SMKC_09A, cchs2005_p::SMKE_09A, cchs2015_2016_p::SMK_080, cchs2017_2018_p::SMK_080, cchs2001_i::SMKA_09A, cchs2003_i::SMKC_09A, cchs2005_i::SMKE_09A, cchs2015_2016_i::SMK_080, cchs2017_2018_i::SMK_080, [SMK_09A]", +SMK_204,cigdayd,# of cigarettes smoked daily - daily smoker,Health behaviour,Smoking,Continuous,cigarettes,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_204, cchs2003_p::SMKC_204, cchs2005_p::SMKE_204, cchs2015_2016_p::SMK_045, cchs2017_2018_p::SMK_045, [SMK_204]", +SMK_208,# of cigarettes smoke each day - former daily,# of cigarettes smoked each day - former daily smoker,Health behaviour,Smoking,Continuous,cigarettes,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKA_208, cchs2003_p::SMKC_208, cchs2005_p::SMKE_208, cchs2015_2016_p::SMK_075, cchs2017_2018_p::SMK_075, [SMK_208]", +SMKDSTY_A,Smoking status,"Type of smoker: daily, occasional, always occasional, former daily, former occasional, never",Health behaviour,Smoking,Categorical,N/A,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, cchs2001_i::SMKADSTY, cchs2003_i::SMKCDSTY, cchs2005_i::SMKEDSTY, [SMKDSTY]","2015 onwards for smoke status still has 6 categories, but removed 'always occasional' (Never daily current occasional smoker) and added 'experimental' (at least 1 cig, non-smoker now)" +SMKDSTY_cat5,Smoking status,"Type of smoker: daily, occasional, former daily, former occasional, never",Health behaviour,Smoking,Categorical,N/A,Yes,"cchs2015_2016_p, cchs2017_2018, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKADSTY, cchs2003_p::SMKCDSTY, cchs2005_p::SMKEDSTY, cchs2015_2016_p::SMKDVSTY, cchs2017_2018_p::SMKDVSTY, [SMKDSTY]","Re-categorization of SMKDSTY to be used for smoking imputation. SMKDSTY_cat5 is a 5 category variable for smoking status for cycles up to 2018. Prior to 2015, 'occasional' and 'always occasional' are combined to form the current 'occasional' category. 2015 onwards, 'former occasional' and 'experimental' are combined to form the current 'former occasional' category" +SMKG01C_A,agec1,Age smoked first cigarette,Health behaviour,Smoking,Categorical,Years,Yes,"cchs2001_p, cchs2003_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C, cchs2001_i::SMKAG01C, cchs2003_i::SMKC_01C, cchs2005_i::SMKE_01C, cchs2015_2016_i::SMK_035, cchs2017_2018_i::SMK_035, [SMK_01C]", +SMKG01C_cont,agec1,Age smoked first cigarette,Health behaviour,Smoking,Continuous,Years,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::SMKAG01C, cchs2003_p::SMKCG01C, cchs2005_p::SMKEG01C, cchs2015_2016_p::SMKG035, cchs2017_2018_p::SMKG035, cchs2009_s::SMK_01C, cchs2010_s::SMK_01C, cchs2012_s::SMK_01C, cchs2003_i::SMKC_01c, cchs2005_i::SMKE_01C, [SMKG01C]", +SMKG09C,stpdy,Years since stopped smoking daily - former daily,Health behaviour,Smoking,Categorical,Years,Yes,"cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i, cchs2015_2016_i, cchs2017_2018_i","cchs2003_p::SMKCG09C, cchs2005_p::SMKEG09C, cchs2015_2016_p::SMKG090, cchs2017_2018_p::SMKG090, cchs2009_s::SMK_09C, cchs2010_s::SMK_09C, cchs2012_s::SMK_09C, cchs2003_i::SMKC_09C, cchs2005_i::SMKE_09C, cchs2015_2016_i::SMK_090, cchs2017_2018_i::SMK_090, [SMKG09C]", +SMKG203_A,agecigd,Age started to smoke daily - daily smoker (G),Health behaviour,Smoking,Categorical,Years,Yes,"cchs2001_p, cchs2003_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2001_i::SMKAG203, cchs2003_i::SMKC_203, cchs2005_i::SMKE_203, [SMK_203]", +SMKG203_cont,agecigd,Age started to smoke daily - daily smoker (G),Health behaviour,Smoking,Continuous,Years,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2001_p::SMKAG203, cchs2003_p::SMKCG203, cchs2005_p::SMKEG203, cchs2009_s::SMK_203, cchs2010_s::SMK_203, cchs2012_s::SMK_203, cchs2001_i::SMKAG203, [SMKG203], DerivedVar::[SMK_005, SMKG040]", +SMKG207_A,agecigfd,Age started to smoke daily - former daily smoker,Health behaviour,Smoking,Categorical,Years,Yes,"cchs2001_p, cchs2003_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2001_i, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207, cchs2001_i::SMKAG207, cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMK_207]", +SMKG207_cont,agecigfd,Age started to smoke daily - former daily smoker,Health behaviour,Smoking,Continuous,Years,Yes,"cchs2001_p, cchs2003_p, cchs2005_p, cchs2007_2008_p, cchs2009_2010_p, cchs2010_p, cchs2011_2012_p, cchs2012_p, cchs2013_2014_p, cchs2014_p, cchs2015_2016_p, cchs2017_2018_p, cchs2009_s, cchs2010_s, cchs2012_s, cchs2003_i, cchs2005_i, cchs2007_2008_i, cchs2009_2010_i, cchs2011_2012_i, cchs2013_2014_i ","cchs2001_p::SMKAG207, cchs2003_p::SMKCG207, cchs2005_p::SMKEG207, cchs2009_s::SMK_207, cchs2010_s::SMK_207, cchs2012_s::SMK_207, cchs2003_i::SMKC_207, cchs2005_i::SMKE_207, [SMKG207], DerivedVar::[SMK_030, SMKG040]", \ No newline at end of file diff --git a/inst/extdata/minimal-example/README.md b/inst/extdata/minimal-example/README.md new file mode 100644 index 0000000..ce92456 --- /dev/null +++ b/inst/extdata/minimal-example/README.md @@ -0,0 +1,308 @@ +# Comprehensive example - MockData reference metadata + +**Purpose:** Complete reference implementation demonstrating all MockData features with v0.2 schema. + +**Coverage:** Basic generation + Survival analysis + Contamination + All variable types + +**Status:** Combined minimal + survival examples (2025-11-09) + +--- + +## Overview + +This example combines basic mock data generation with survival analysis to demonstrate the full range of MockData capabilities: + +**Basic variables (3):** +- age, smoking, BMI - Demonstrates integers, categories, continuous distributions, contamination + +**Survival variables (4):** +- interview_date, primary_event_date, death_date, ltfu_date - Demonstrates competing risks, Gompertz distributions, event proportions + +**Total:** 7 variables, 24 detail specifications + +--- + +## Files + +### variables.csv + +Demonstrates all 12 variable-level extension fields: + +| Variable | Type | Demonstrates | +|----------|------|-------------| +| **age** | integer | Low-contamination only, variable-level seed | +| **smoking** | factor | Categorical with multi-valued role, no contamination | +| **BMI** | double | Normal distribution, two-sided contamination (low + high) | +| **interview_date** | date | Cohort entry (index date), date range generation | +| **primary_event_date** | date | Gompertz distribution, event proportion (10%), temporal violations (3%) | +| **death_date** | date | Competing risk, all individuals eventually die (100%) | +| **ltfu_date** | date | Censoring event, uniform distribution (10% occurrence) | + +**Key features:** +- UIDs: Numeric-only format (`v_001`, `v_002`, ..., `v_007`) +- rType: All data types (integer, factor, double, date) +- role: Multi-valued roles ("enabled,predictor,table1", "enabled,outcome", "enabled,metadata") +- position: Deterministic ordering (10, 20, 30, ..., 70) +- Contamination: Low-only (age), two-sided (BMI), high-only (primary_event_date) +- Versioning: MockData semantic versioning independent of recodeflow + +### variable_details.csv + +Demonstrates all 5 detail-level extension fields across different variable types: + +**Basic specifications:** +| Variable | Demonstrates | +|----------|-------------| +| **age** | Valid range using recStart interval notation `[18,100]` | +| **smoking** | Categorical proportions (sum to 1.0), missing code (7 = Don't know) | +| **BMI** | Normal distribution with parameters (distribution, mean, sd, valid range) | + +**Survival specifications:** +| Variable | Demonstrates | +|----------|-------------| +| **interview_date** | Date range `[2001-01-01,2005-12-31]` with sourceFormat | +| **primary_event_date** | Gompertz distribution, followup_min/max, event proportion, rate parameter | +| **death_date** | Gompertz distribution with 100% event occurrence (everyone dies) | +| **ltfu_date** | Uniform distribution with 10% event occurrence (loss to follow-up) | + +**Key features:** +- UIDs: Foreign keys linking to variables.csv (`v_001` through `v_007`) +- uid_detail: Unique row identifiers (`d_001` through `d_024`) +- recStart: Generation values (what MockData generates) - uses `N/A` for distribution parameters +- recEnd: Specification labels (distribution, mean, sd, valid, copy, followup_min, followup_max, event, rate) +- proportion: Population proportions (smoking) + event proportions (survival) +- value: Distribution type (normal, gompertz, uniform) + numeric parameters +- NO range_min/range_max: Uses recStart interval notation instead + +--- + +## Schema compliance + +Validates successfully with expected warnings for survival event proportions: + +```r +source("R/validate_mockdata_extensions.R") + +result <- validate_mockdata_metadata( + "inst/extdata/minimal-example/variables.csv", + "inst/extdata/minimal-example/variable_details.csv" +) + +print(result) +# Valid: YES +# Warnings: 2 (event proportions auto-normalized - expected for survival data) +``` + +**Validation checks:** +1. UID patterns: `^v_[0-9]+$` and `^d_[0-9]+$` βœ“ +2. Foreign keys: All detail UIDs exist in variables βœ“ +3. Proportions: Categorical sums to 1.0, survival events auto-normalize βœ“ +4. Contamination ranges: Use interval notation `[min,max]` βœ“ +5. Contamination proportions: Between 0-1 βœ“ +6. rType values: Valid enum (integer/double/factor/date) βœ“ +7. Versioning: Semantic versioning (1.0.0) and date format (YYYY-MM-DD) βœ“ + +--- + +## Key patterns demonstrated + +### 1. Basic generation (age, smoking, BMI) + +**Categorical variable with proportions:** +```csv +# variable_details.csv +uid,recStart,recEnd,catLabel,proportion +v_002,1,1,Never smoker,0.50 +v_002,2,2,Former smoker,0.30 +v_002,3,3,Current smoker,0.17 +v_002,7,7,Don't know,0.03 +# Sum: 1.00 βœ“ +``` + +**Continuous variable with distribution:** +```csv +# variable_details.csv +uid,recEnd,value +v_003,distribution,normal +v_003,mean,27.5 +v_003,sd,5.2 +v_003,valid,[18,40] # Using recStart for truncation bounds +``` + +### 2. Survival analysis (interview_date, primary_event_date, death_date, ltfu_date) + +**Index date (cohort entry):** +```csv +# variable_details.csv +uid,recStart,recEnd +v_004,[2001-01-01,2005-12-31],copy +``` + +**Event date with Gompertz distribution:** +```csv +# variable_details.csv +uid,recEnd,value,proportion +v_005,distribution,gompertz, +v_005,followup_min,365, # 1 year minimum +v_005,followup_max,5475, # 15 years maximum +v_005,event,0.10 # 10% experience event +v_005,rate,0.0001, # Gompertz rate parameter +``` + +**Competing risk (all individuals die):** +```csv +uid,recEnd,value,proportion +v_006,distribution,gompertz, +v_006,event,1.00 # 100% occurrence +``` + +### 3. Contamination + +**Variable-level contamination parameters (in variables.csv):** +```csv +uid,corrupt_low_prop,corrupt_low_range,corrupt_high_prop,corrupt_high_range +v_001,0.01,[-5,10],, # Age: 1% invalid low values +v_003,0.02,[-10,0],0.01,[60,150] # BMI: 2% low + 1% high +v_005,,,0.03,[2099-01-01,2099-12-31] # primary_event: 3% future dates +``` + +### 4. Standardized recEnd values + +**For distributions:** +- `distribution` - Type (normal, gompertz, uniform, exponential) +- `mean`, `sd` - Normal distribution parameters (in value column) +- `rate`, `shape` - Gompertz/exponential parameters (in value column) +- `valid` - Truncation bounds (in recStart column using interval notation) + +**For survival:** +- `followup_min`, `followup_max` - Follow-up time range in days (in value column) +- `event` - Proportion who experience event (in proportion column) +- `censored` - Proportion censored (if needed) + +**For dates:** +- `copy` - Use date range from recStart interval notation +- Date range specified in recStart: `[2001-01-01,2005-12-31]` + +--- + +## Usage examples + +### Basic mock data generation + +```r +library(mockData) + +# Load metadata +variables <- read.csv("inst/extdata/minimal-example/variables.csv", + stringsAsFactors = FALSE, check.names = FALSE) +variable_details <- read.csv("inst/extdata/minimal-example/variable_details.csv", + stringsAsFactors = FALSE, check.names = FALSE) + +# Generate basic variables only +basic_vars <- c("age", "smoking", "BMI") +basic_details <- variable_details[variable_details$variable %in% basic_vars, ] + +mock_data <- create_mock_data( + variable_details = basic_details, + variables = variables[variables$variable %in% basic_vars, ], + n = 1000, + seed = 12345 +) + +# Check contamination +summary(mock_data$age) # Should see some values < 18 (contamination) +summary(mock_data$BMI) # Should see some values < 18 or > 40 +table(mock_data$smoking) +``` + +### Survival analysis data generation + +```r +# Generate survival variables +survival_vars <- c("interview_date", "primary_event_date", "death_date", "ltfu_date") +survival_details <- variable_details[variable_details$variable %in% survival_vars, ] + +# Start with interview dates +df <- data.frame(id = 1:1000) + +# Generate each date variable +# (See survival vignette for complete workflow) +``` + +### Combined generation + +```r +# Generate complete dataset (basic + survival) +complete_data <- create_mock_data( + variable_details = variable_details, + variables = variables, + n = 1000, + seed = 12345 +) + +# Verify all variables present +names(complete_data) +# [1] "age" "smoking" "BMI" "interview_date" "primary_event_date" +# [6] "death_date" "ltfu_date" +``` + +--- + +## Survival analysis workflow + +MockData generates **raw date columns only**. Derived variables are calculated by the user: + +```r +# After generating mock data with survival dates... + +# 1. Calculate t_end_date (earliest of: event, death, ltfu, admin censor) +admin_censor <- as.Date("2017-03-31") +df$t_end_date <- pmin( + df$primary_event_date, + df$death_date, + df$ltfu_date, + admin_censor, + na.rm = TRUE +) + +# 2. Calculate time in years +df$time <- as.numeric(df$t_end_date - df$interview_date) / 365.25 + +# 3. Calculate failcode (priority rule) +df$failcode <- ifelse( + !is.na(df$primary_event_date) & df$primary_event_date == df$t_end_date, 1, # Primary event + ifelse(!is.na(df$death_date) & df$death_date == df$t_end_date, 4, # Death + ifelse(!is.na(df$ltfu_date) & df$ltfu_date == df$t_end_date, 0, # LTFU + ifelse(df$t_end_date == admin_censor, 0, NA))) # Admin censor +) + +# 4. Verify competing risks +table(df$failcode) +# 0 1 4 +# 893 97 10 +# (0 = censored, 1 = primary event, 4 = death) +``` + +--- + +## Next steps + +- **Code refactoring:** Use this example to test Phase 2 code changes (rType move, interval notation parsing) +- **Vignettes:** See `vignettes/getting-started.qmd` for full tutorial +- **Advanced:** See `vignettes/dates.qmd` for survival analysis deep dive +- **Schema:** See `inst/metadata/schemas/mockdata_extensions.yaml` for complete field reference + +--- + +## Notes + +**Why combine minimal + survival?** +- Single comprehensive example for all testing during refactoring +- Demonstrates full feature range (basic β†’ advanced) +- Easier maintenance (one example to update) +- Tutorials can reference specific variables without needing multiple examples + +**Validation warnings:** +- Survival event proportions (0.10, 1.00) trigger auto-normalization warnings +- This is expected - event proportions are parameters, not population distributions +- In basic mode, warnings are acceptable; use strict mode to enforce 1.0 sums diff --git a/inst/extdata/minimal-example/variable_details.csv b/inst/extdata/minimal-example/variable_details.csv new file mode 100644 index 0000000..d5f6808 --- /dev/null +++ b/inst/extdata/minimal-example/variable_details.csv @@ -0,0 +1,27 @@ +"uid","uid_detail","variable","recStart","recEnd","catLabel","proportion" +"cchsflow_v0001","cchsflow_d00001","age","[18,100]","copy","Valid age range",0.90 +"cchsflow_v0001","cchsflow_d00002","age","997","NA::b","Don't know",0.05 +"cchsflow_v0001","cchsflow_d00003","age","998","NA::b","Refusal",0.03 +"cchsflow_v0001","cchsflow_d00004","age","999","NA::b","Not stated",0.02 +"cchsflow_v0002","cchsflow_d00005","smoking","1","1","Never smoker",0.5 +"cchsflow_v0002","cchsflow_d00006","smoking","2","2","Former smoker",0.3 +"cchsflow_v0002","cchsflow_d00007","smoking","3","3","Current smoker",0.17 +"cchsflow_v0002","cchsflow_d00008","smoking","7","NA::b","Don't know",0.03 +"cchsflow_v0003","cchsflow_d00009","BMI","[15,50]","copy","Valid BMI range", +"cchsflow_v0003","cchsflow_d00010","BMI","996","NA::a","Not applicable",0.3 +"cchsflow_v0003","cchsflow_d00011","BMI","[997,999]","NA::b","Don't know, refusal, not stated",0.1 +"cchsflow_v0004","cchsflow_d00012","height","[1.4,2.1]","copy","Valid height range (meters)", +"cchsflow_v0004","cchsflow_d00013","height","else","NA::b","Missing height",0.02 +"cchsflow_v0005","cchsflow_d00014","weight","[35,150]","copy","Valid weight range (kg)", +"cchsflow_v0005","cchsflow_d00015","weight","else","NA::b","Missing weight",0.03 +"cchsflow_v0006","cchsflow_d00016","BMI_derived","DerivedVar::[height, weight]","Func::bmi_fun","BMI calculated from height and weight", +"ices_v01","ices_d001","interview_date","[2001-01-01,2005-12-31]","copy","Interview date range",1 +"ices_v01","ices_d002","interview_date","else","NA::b","Missing interview date",0 +"ices_v02","ices_d003","primary_event_date","[2002-01-01,2021-01-01]","copy","Primary event date range",0.1 +"ices_v02","ices_d004","primary_event_date","else","NA::b","Missing event date",0 +"ices_v03","ices_d005","death_date","[2002-01-01,2024-12-31]","copy","Death date range",0.2 +"ices_v03","ices_d006","death_date","else","NA::b","Missing death date",0.05 +"ices_v04","ices_d007","ltfu_date","[2002-01-01,2024-12-31]","copy","Loss to follow-up date range",0.05 +"ices_v04","ices_d008","ltfu_date","else","NA::b","Missing ltfu date", +"ices_v05","ices_d009","admin_censor_date","2024-12-31","copy","Administrative censor date",1 +"ices_v05","ices_d010","admin_censor_date","else","NA::b","Missing administrative censor date",0 diff --git a/inst/extdata/minimal-example/variables.csv b/inst/extdata/minimal-example/variables.csv new file mode 100644 index 0000000..9e5ce85 --- /dev/null +++ b/inst/extdata/minimal-example/variables.csv @@ -0,0 +1,12 @@ +"uid","variable","label","variableType","rType","role","position","seed","garbage_low_prop","garbage_low_range","garbage_high_prop","garbage_high_range","distribution","mean","sd","rate","shape","followup_min","followup_max","event_prop","sourceFormat","mockDataVersion","mockDataLastUpdated","mockDataVersionNotes" +"cchsflow_v0001","age","Age in years","Continuous","integer","enabled,predictor,table1",10,10,,"[;]",,"[;]","normal",50,15,,,,,,"","1.0.0","2025-11-09","Normal distribution (mean=50, sd=15)" +"cchsflow_v0002","smoking","Smoking status","Categorical","factor","enabled,predictor,table1",20,20,,"",,"","",,,,,,,,"","1.0.0","2025-11-09","Categorical variable with proportions" +"cchsflow_v0003","BMI","Body mass index","Continuous","double","enabled,outcome,table1",30,30,0.02,"[-10;15])",0.01,"[60;150]","normal",27.5,5.2,,,,,,"","1.0.0","2025-11-09","Normal distribution with two-sided contamination" +"cchsflow_v0004","height","Height in meters","Continuous","double","enabled,predictor",40,40,1,"[0;1.4)",0.01,"(2.1;inf]","normal",1.7,0.1,,,,,,"","1.0.0","2025-11-13","Height for BMI calculation" +"cchsflow_v0005","weight","Weight in kilograms","Continuous","double","enabled,predictor",50,50,,"[;]",,"[;]","normal",75,15,,,,,,"","1.0.0","2025-11-13","Weight for BMI calculation" +"cchsflow_v0006","BMI_derived","BMI calculated from height and weight","Continuous","double","enabled,outcome,table1",60,60,,"[;]",,"[;]","",,,,,,,,"","1.0.0","2025-11-13","Derived variable: BMI = weight / (height^2)" +"ices_v01","interview_date","Interview date (cohort entry)","Continuous","date","enabled,outcome",70,70,0,"[;]",0,"[;]","uniform",,,,,,,,"analysis","1.0.0","2025-11-09","Uniform date range (cohort entry)" +"ices_v02","primary_event_date","Primary event date (dementia diagnosis)","Continuous","date","enabled,outcome,table1",80,80,0,"[;]",0.03,"[2021-01-01;2099-12-31]","gompertz",,,1e-04,0.1,0,5475,0.3,"analysis","1.0.0","2025-11-09","Gompertz survival with temporal violations (3%)" +"ices_v03","death_date","Death date (competing risk)","Continuous","date","enabled,outcome, table1",90,90,0,"[;]",0.03,"[2025-01-01;2099-12-31]","gompertz",,,1e-04,0.1,365,7300,0.2,"analysis","1.0.0","2025-11-09","Gompertz survival with auto-generated date corruption" +"ices_v04","ltfu_date","Loss to follow-up date","Continuous","date","enabled,outcome",100,100,0,"[;]",0.03,"[2025-01-01;2099-12-31]","uniform",,,,,365,7300,0.1,"analysis","1.0.0","2025-11-09","Uniform censoring (10% occurrence)" +"ices_v05","admin_censor_date","admin_censor_date","Continuous","date","enabled,outcome",110,110,0,"[;]",0,"[;]","",,,,,365,7300,1,"analysis","1.0.0","2025-11-09","" diff --git a/inst/extdata/mock_data_config.csv b/inst/extdata/mock_data_config.csv new file mode 100644 index 0000000..27f6ff4 --- /dev/null +++ b/inst/extdata/mock_data_config.csv @@ -0,0 +1,4 @@ +"uid","variable","role","label","labelLong","section","subject","variableType","units","position","source_database","source_spec","version","last_updated","notes","seed" +"v_003","index_date","enabled","Index date","Cohort entry date","Study design","Dates","date","YYYY-MM-DD",5,"cchs2001_p","variables_cchsflow_sample.csv",,"2025-11-01","Entry date for cohort, uniformly distributed between start and end dates", +"v_001","ADL_01","enabled, intermediate, outcome_sec, table1_master","Help preparing meals","Needs help - preparing meals","Health status","ADL","Categorical","N/A",10,"cchs2001_p","variables_cchsflow_sample.csv",,"2025-11-01","", +"v_009","ALW_2A1","enabled, intermediate","DailyConsumptionSunday","Number of drinks on Sunday","Health behaviour","Alcohol","Continuous","drinks",90,"cchs2001_p","variables_cchsflow_sample.csv",,"2025-11-01","", diff --git a/inst/extdata/mock_data_config_details.csv b/inst/extdata/mock_data_config_details.csv new file mode 100644 index 0000000..0693840 --- /dev/null +++ b/inst/extdata/mock_data_config_details.csv @@ -0,0 +1,12 @@ +"uid","uid_detail","variable","dummyVariable","recEnd","catLabel","catLabelLong","units","proportion","value","range_min","range_max","date_start","date_end","notes" +"v_003","d_001","index_date","","date_start","Start date","Accrual start date","YYYY-MM-DD",NA,NA,NA,NA,"2000-01-01","","Start of accrual period" +"v_003","d_002","index_date","","date_end","End date","Accrual end date","YYYY-MM-DD",NA,NA,NA,NA,"","2005-12-31","End of accrual period" +"v_001","d_003","ADL_01","ADL_01_cat2_1","1","Yes","Yes","N/A",NA,NA,NA,NA,"","","" +"v_001","d_004","ADL_01","ADL_01_cat2_2","2","No","No","N/A",NA,NA,NA,NA,"","","" +"v_001","d_005","ADL_01","ADL_01_cat2_NA::a","6","not applicable","not applicable","N/A",NA,NA,NA,NA,"","","" +"v_001","d_006","ADL_01","ADL_01_cat2_NA::b","[7,9]","don't know (7); refusal (8); not stated (9)","missing","N/A",NA,NA,NA,NA,"","","" +"v_001","d_007","ADL_01","ADL_01_cat2_NA::b","else","else","missing","N/A",NA,NA,NA,NA,"","","" +"v_009","d_008","ALW_2A1","N/A","[0,50]","Number of drinks on Sunday","Number of drinks on Sunday","drinks",NA,NA,NA,NA,"","","" +"v_009","d_009","ALW_2A1","N/A","996","not applicable","not applicable","drinks",NA,NA,NA,NA,"","","" +"v_009","d_010","ALW_2A1","N/A","[997,999]","don't know (997); refusal (998); not stated (999)","missing","drinks",NA,NA,NA,NA,"","","" +"v_009","d_011","ALW_2A1","N/A","else","else","missing","drinks",NA,NA,NA,NA,"","","" diff --git a/inst/metadata/schemas/mock_data_schema.yaml b/inst/metadata/schemas/mock_data_schema.yaml new file mode 100644 index 0000000..0216445 --- /dev/null +++ b/inst/metadata/schemas/mock_data_schema.yaml @@ -0,0 +1,1222 @@ +# MockData schema: Schema definitions for mock data configuration files +# +# Purpose: Single source of truth for MockData configuration structure. +# Defines schemas for variable definitions (mock_data_config.csv) and +# distribution parameters (mock_data_config_details.csv), aligned with +# recodeflow/cchsflow patterns. +# +# This file consolidates all schema specifications. Separate datasets +# catalog (datasets_catalog.yaml) catalogs specific mock datasets using +# Dublin Core metadata. + +name: MockData_Configuration_Schema +version: 0.2.0 +date: 2025-11-01 +status: active + +description: > + Comprehensive schema definitions for MockData configuration files. Defines + structure for metadata-driven mock data generation aligned with recodeflow/ + cchsflow patterns. Supports two-file configuration: variable definitions + (config) and distribution details (details). + +# Core principles + +principles: + metadata_driven: + description: > + Configuration uses existing research specifications (variables.csv, + variable_details.csv patterns) rather than requiring duplicate + specifications in code. + + raw_survey_data: + description: > + Generates realistic raw survey data with numeric missing codes + (7=Don't know, 8=Refusal, 9=Not stated), not recoded/harmonized + data (NA::a, NA::b from haven). Allows testing of complete data + cleaning and harmonization pipelines. + + contamination_model: + description: > + Two-step generation: (1) population distribution (valid + missing + sum to 1.0), (2) contamination replaces some valid values with + implausible values. Matches real-world data quality issues. + + recodeflow_alignment: + description: > + File structure and naming align with recodeflow/cchsflow patterns: + catalog.yaml + config.csv + config_details.csv. Supports same + metadata columns (role, section, subject, labelLong, etc.). + +# Shared specifications across all MockData configuration files + +shared_specifications: + + csv_format: + encoding: UTF-8 + delimiter: "," + quote_char: "\"" + header: true + na_string: "" + comment_char: "#" + notes: > + All CSV files MUST be generated programmatically using data.frame + operations and write.csv() in R. Manual editing discouraged to + avoid column misalignment and quoting errors. + + missing_data_standards: + description: > + Missing data values must be explicitly specified in configuration files. + Common conventions include numeric codes (7, 8, 9 in Canadian health surveys; + 96, 97, 98, 99 in other contexts; -7, -8, -9 in some databases) or special + values (NA, NULL, ""). MockData supports any numeric missing codes specified + in the details file. + + raw_vs_recoded: + raw_codes: + description: > + MockData generates RAW missing codes as specified in details file + (e.g., 7="Don't know", 8="Refusal", 9="Not stated"). These are numeric + values in the generated dataset. + examples: + - "7, 8, 9 (common in Canadian health surveys: CCHS, CHMS)" + - "96, 97, 98, 99 (common in US surveys)" + - "-7, -8, -9 (common in administrative databases)" + + recoded_codes: + description: > + MockData does NOT generate recoded/harmonized missing codes (e.g., + NA::a, NA::b, NA::c from haven package). Recoded data is the OUTPUT + of harmonization pipelines, not the INPUT for testing those pipelines. + + configurable_codes: + notes: > + Users specify missing codes in mock_data_config_details.csv via recEnd + column. Any numeric value can serve as a missing code. The examples above + (7/8/9) are common but not required. + + contamination_standards: + description: > + Two-step generation model: (1) Population distribution (valid + missing + proportions sum to 1.0), (2) Contamination replaces some valid values + (corrupt_* proportions applied to valid subset only). + + contamination_types: + corrupt_low: + description: "Implausible low values (below valid range)" + example: "BMI = -1, Age = 5" + applies_to: [continuous, integer] + proportion_base: "Applied to VALID values only" + + corrupt_high: + description: "Implausible high values (above valid range)" + example: "BMI = 200, Age = 127" + applies_to: [continuous, integer] + proportion_base: "Applied to VALID values only" + + corrupt_future: + description: "Impossible future dates" + example: "death_date = 2099-01-01" + applies_to: [date, survival] + proportion_base: "Applied to VALID values only" + + contamination_model: + step1_population: + description: > + Generate from population distribution. Extract valid and missing + proportions (must sum to 1.0). Sample category assignment, generate + numeric values for valid category, assign raw codes to missing + categories. + example: + valid: 0.95 + DK_7: 0.03 + NS_9: 0.02 + sum: 1.0 + + step2_contamination: + description: > + Apply contamination. Extract corrupt_* proportions. Identify valid + indices. Sample from valid to corrupt. Replace with values from + contamination ranges. Ensure no overlap (use setdiff for sequential). + example: + corrupt_low: 0.02 # Replace 2% of valid values + corrupt_high: 0.01 # Replace 1% of valid values + + final_distribution: + description: > + After applying contamination model to population distribution + example: + valid_clean: "~93% (95% * 0.97)" + corrupt_low: "~2% (95% * 0.02)" + corrupt_high: "~1% (95% * 0.01)" + DK_7: "3%" + NS_9: "2%" + + implementation_notes: > + Contamination proportions are SEPARATE from population proportions. + They are excluded from the 1.0 sum validation and applied after + population generation. This matches real-world data cleaning workflows + where outliers and errors contaminate otherwise valid measurements. + + validation_patterns: + proportion_sum: + rule: "valid + missing proportions sum to 1.0 (Β±0.001 tolerance)" + applies_to: "mock_data_config_details.csv" + contamination_handling: "corrupt_* rows excluded from sum" + auto_normalize: "If sum β‰  1.0, auto-normalize with warning" + + required_parameters: + normal: + required: [mean, sd] + optional: [range_min, range_max] + gompertz: + required: [rate, shape] + optional: [followup_range] + exponential: + required: [rate] + optional: [followup_range] + poisson: + required: [rate] + optional: [range_min, range_max] + uniform: + required: [range_min, range_max] + optional: [] + + recEnd_validation: + mode: "flexible" + description: > + Validate based on variable type, but warn rather than error on + unknown recEnd values. Allow extensibility for future needs. + + role_patterns: + syntax: "comma_separated" + example: "predictor, enabled, table1" + + standard_roles: + generation_control: + enabled: + description: "Generate this variable in dataset" + required_for_generation: true + + metadata: + description: "Study-level parameter (not generated as column)" + mutually_exclusive_with: [enabled] + + variable_function: + predictor: + description: "Independent variable / covariate" + compatible_with: [enabled, table1, confounder] + + outcome: + description: "Dependent variable / endpoint" + compatible_with: [enabled] + + confounder: + description: "Confounding variable for causal analysis" + compatible_with: [enabled, predictor] + + exposure: + description: "Treatment or exposure variable" + compatible_with: [enabled] + + table_roles: + table1: + description: "Include in Table 1 (baseline characteristics)" + compatible_with: [enabled, predictor] + + table2: + description: "Include in Table 2 (secondary characteristics)" + compatible_with: [enabled] + + model_roles: + model1_predictor: + description: "Predictor for model 1" + compatible_with: [enabled, predictor] + + model1_outcome: + description: "Outcome for model 1" + compatible_with: [enabled, outcome] + + constraints: + - at_least_one_role: true + - whitespace_trimmed: true + + parsing: + method: "strsplit(config$role, ',\\\\s*')" + example_code: | + # Check if variable has "enabled" role + has_enabled <- grepl("\\benabled\\b", config$role) + + # Filter to table1 variables + table1_vars <- config[grepl("\\btable1\\b", config$role), ] + + extensibility: > + Roles are extensible. Users can define custom roles (e.g., sensitivity_analysis, + table3) for project-specific filtering. The only required role for generation + is "enabled". + + recEnd_standardized_values: + description: > + Comprehensive specification of standardized recEnd values used in + mock_data_config_details.csv. Organized by variable type and purpose. + + categorical_categories: + description: "Category values for categorical variables" + notes: > + Can be numeric (1, 2, 3), character ("yes", "no"), or any value. + Defined per-variable in mock_data_config_details.csv recEnd column. + These are valid categories, not missing codes. + examples: + numeric: ["1", "2", "3", "4"] + character: ["never", "former", "current"] + mixed: ["0", "1", "unknown"] + + missing_codes: + description: "Raw survey missing data codes (dataset-specific)" + notes: > + Missing codes are defined in mock_data_config_details.csv for each + dataset. Common conventions vary by survey organization and country. + Any numeric value can serve as a missing code. + + common_patterns: + canadian_health_surveys: + description: "CCHS, CHMS, and related surveys" + codes: + 7: "Don't know" + 8: "Refusal" + 9: "Not stated" + + us_surveys: + description: "Some US survey conventions" + codes: + 96: "Valid skip" + 97: "Don't know" + 98: "Refusal" + 99: "Not stated" + + negative_codes: + description: "Administrative databases" + codes: + -7: "Don't know" + -8: "Refusal" + -9: "Not stated" + + usage: > + Specify missing codes in mock_data_config_details.csv using recEnd + column. Each dataset can have its own missing code convention. + + continuous_parameters: + distribution: + description: "Distribution type" + example_value: "normal" + allowed_values: [normal, uniform, exponential, poisson] + + mean: + description: "Mean parameter for normal distribution" + example_value: 27 + + sd: + description: "Standard deviation for normal distribution" + example_value: 5 + + rate: + description: "Rate parameter for exponential/poisson" + example_value: 0.01 + + valid: + description: "Valid value specification with range" + has_proportion: true + has_range: true + + survival_parameters: + distribution: + description: "Survival distribution type" + allowed_values: [gompertz, exponential, uniform] + + rate: + description: "Rate parameter for gompertz/exponential" + example_value: 0.01 + + shape: + description: "Shape parameter for gompertz" + example_value: 0.1 + + followup_range: + description: "Follow-up time range in days" + has_range: true + + censored: + description: "Censoring specification" + has_proportion: true + + date_parameters: + date_start: + description: "Start date for date range" + has_date: true + + date_end: + description: "End date for date range" + has_date: true + + contamination_parameters: + corrupt_low: + description: "Implausible low values" + has_proportion: true + has_range: true + applies_to: [continuous, integer] + notes: "Proportion of VALID values to replace (not population proportion)" + + corrupt_high: + description: "Implausible high values" + has_proportion: true + has_range: true + applies_to: [continuous, integer] + notes: "Proportion of VALID values to replace" + + corrupt_future: + description: "Impossible future dates" + has_proportion: true + has_date: true + applies_to: [date, survival] + notes: "Dates beyond reasonable future" + + validation: + mode: flexible + description: > + Validate based on variable type, but warn rather than error on + unknown recEnd values. Allows extensibility for future parameter + types without schema updates. + +# Schema definitions + +schemas: + + mock_data_config: + target_csv: inst/extdata/mock_data_config.csv + generator_script: inst/extdata/generate_mock_data_config.R + + purpose: > + Variable-level definitions for mock data generation. One row per + variable, defining high-level properties (role, type, label, + position) without distribution-specific parameters. + + structure: wide_format + row_type: one_per_variable + + relationship_to_details: > + Primary key (uid) links to mock_data_config_details.csv via uid. + Variable names can change, but uid remains stable. Each variable in + config may have multiple detail rows specifying distribution parameters, + category proportions, and contamination. + + columns: + uid: + type: character + required: true + unique: true + description: > + Unique identifier for this variable definition. Stable across + variable name changes. Format: v_ + sequential number or descriptive + ID (e.g., "v_001", "v_age_baseline", "v_bmi"). + pattern: "^v_[a-z0-9_]+$" + examples: + - "v_001" + - "v_age_baseline" + - "v_bmi" + - "v_smoking_status" + + variable: + type: character + required: true + unique: true + description: > + Variable name used in generated data. Can change if variable is + renamed, but uid remains constant for linking to details. + pattern: "^[a-zA-Z][a-zA-Z0-9_]*$" + constraints: + - max_length: 64 + - no_duplicates: true + + role: + type: character + required: true + pattern: "comma_separated" + description: > + Multi-valued roles for the variable. Comma-separated list indicating + how the variable should be used. See shared_specifications.role_patterns + for complete taxonomy. + + label: + type: character + required: false + description: "Short label for tables (≀20 characters)" + + labelLong: + type: character + required: false + description: "Descriptive label for documentation" + + section: + type: character + required: false + description: "Primary grouping for Table 1 (e.g., Demographics, Health)" + + subject: + type: character + required: false + description: "Secondary grouping within section (e.g., Age, BMI)" + + variableType: + type: character + required: true + allowed_values: [categorical, continuous, date, survival, character, integer] + description: "Data type for generation" + + units: + type: character + required: false + description: "Measurement units (e.g., years, kg/m2, mmHg)" + + position: + type: integer + required: true + description: "Sort order for generation (10, 20, 30...)" + constraints: + - must_be_positive: true + - recommended_increment: 10 + + source_database: + type: character + required: false + description: > + Database identifier(s) from which this variable was imported. + When importing from recodeflow metadata, this is extracted from + the databaseStart field based on the database filter parameter. + Multiple databases can be comma-separated. + examples: + - "cchs2001_p" + - "cchs2015_2016_p, cchs2017_2018_p" + - "cycle1" + + source_spec: + type: character + required: false + description: > + Source specification file from which this variable was imported. + Typically the filename of the recodeflow variables.csv file used + for import. Helps track provenance of variable definitions. + examples: + - "variables_cchsflow_sample.csv" + - "variables_DemPoRT.csv" + - "variables.csv" + + version: + type: character + required: false + pattern: "semantic_version" + description: "Configuration version (e.g., 2.0.0)" + + last_updated: + type: date + required: false + format: "YYYY-MM-DD" + description: "Date last modified" + + notes: + type: character + required: false + description: "Documentation and implementation notes" + + seed: + type: integer + required: false + description: "Random seed for reproducibility (variable-level)" + + special_variables: + metadata_variables: + description: > + Variables with role="metadata" store study-level parameters and are + NOT generated as columns in the dataset. Instead, they are extracted + by get_study_metadata() and used to control generation. + + common_metadata_variables: + - study_name (character) + - study_design (character: open_cohort, fixed_followup) + - accrual_start (date) + - accrual_end (date) + - max_followup_date (date) + - sample_size (integer) + + storage: + variable: "Variable name (e.g., study_name)" + role: "metadata" + variableType: "character, date, or integer" + labelLong: "Stored value as string" + + survival_variables: + description: > + Variables with variableType="survival" generate TWO columns in the + dataset: the event date column ({variable}) and a status indicator + column ({variable}_status). Status = 1 for observed events, 0 for censored. + + generated_columns: + event_date: "{variable} (e.g., death_date)" + status: "{variable}_status (e.g., death_date_status)" + + validation: + - "uid column must be unique (no duplicates)" + - "variable column must be unique (no duplicates)" + - "role must contain at least one value" + - "variableType must be one of allowed_values" + - "position must be positive integer" + - "If role contains 'metadata', variable stores study-level parameter" + + mock_data_config_details: + target_csv: inst/extdata/mock_data_config_details.csv + generator_script: inst/extdata/generate_mock_data_config_details.R + + purpose: > + Distribution parameters and proportions for mock data generation. + Multiple rows per variable, one row per category or parameter + specification. Supports category-specific proportions, distribution + parameters, and contamination specifications. + + structure: long_format + row_type: multiple_per_variable + + relationship_to_config: > + Foreign key (uid) links to mock_data_config.csv via uid. All uids + in details MUST exist in config. Variables in config without detail + rows fall back to uniform distributions. + + columns: + uid: + type: character + required: true + foreign_key: mock_data_config.uid + description: > + Links to mock_data_config.csv via uid (variable-level). Stable across + variable name changes. Each detail row belongs to a variable defined + in config. All detail rows for the same variable share the same uid. + pattern: "^v_[a-z0-9_]+$" + examples: + - "v_001" + - "v_age_baseline" + + uid_detail: + type: character + required: true + unique: true + description: > + Unique identifier for this specific detail row (row-level). Each row + in mock_data_config_details.csv gets its own uid_detail for precise + tracking and reference. Format: d_ + sequential number. + pattern: "^d_[0-9]+$" + examples: + - "d_001" + - "d_002" + - "d_003" + + variable: + type: character + required: true + description: > + Variable name for reference (denormalized from config for + readability). Primary link is via uid, but variable name included + to make details file human-readable. + + dummyVariable: + type: character + required: false + description: > + Dummy variable identifier from recodeflow variable_details.csv. + Used to track the specific category/parameter specification from + the source metadata. Typically follows pattern: {variable}_{type}_{value}. + examples: + - "ADL_01_cat2_1" + - "ADL_01_cat2_2" + - "ADL_01_cat2_NA::a" + - "BMI_cont_valid" + + recEnd: + type: character + required: true + description: > + Category value or parameter name. See shared_specifications.recEnd_standardized_values + for complete listing organized by variable type. + + catLabel: + type: character + required: false + description: "Short category label (≀20 characters)" + + catLabelLong: + type: character + required: false + description: > + Long category label for documentation. When importing from recodeflow + variable_details.csv, this is copied from the catLabelLong field. + Can be left empty and populated later with table1 metadata. + + units: + type: character + required: false + description: > + Measurement units for this specific parameter. May differ from the + variable-level units in mock_data_config.csv for continuous variables + with different parameter specifications. + + proportion: + type: numeric + required: false + range: [0, 1] + description: > + Proportion for this category (0-1). Population proportions + (valid + missing) must sum to 1.0. Contamination proportions + (corrupt_*) are separate and applied after population generation. + + value: + type: numeric + required: false + description: "Numeric parameter value (for mean, sd, rate, shape, etc.)" + + range_min: + type: numeric + required: false + description: "Minimum value for range (continuous, integer, contamination)" + + range_max: + type: numeric + required: false + description: "Maximum value for range (continuous, integer, contamination)" + + date_start: + type: date + required: false + format: "YYYY-MM-DD" + description: "Start date for date ranges" + + date_end: + type: date + required: false + format: "YYYY-MM-DD" + description: "End date for date ranges" + + notes: + type: character + required: false + description: "Implementation notes for this parameter" + + validation: + - "All uids must exist in mock_data_config.csv" + - "All uid_detail values must be unique (no duplicates)" + - "Proportion values must be in range [0, 1]" + - "Population proportions (valid + missing) sum to 1.0 Β±0.001" + - "Contamination proportions (corrupt_*) excluded from sum" + - "Auto-normalize proportions with warning if sum β‰  1.0" + - "Required parameters present for each distribution type" + - "range_min < range_max (if both specified)" + - "date_start < date_end (if both specified)" + + mock_data_catalog: + target_csv: "inst/examples/demport/mock_cchs*.csv" + + purpose: > + Schema for the actual generated mock data files (the output CSV files). + These are the mock datasets created by MockData, cataloged in + datasets_catalog.yaml. Each file contains one row per participant with + all generated variables as columns. + + structure: wide_format + row_type: one_per_participant + + relationship_to_config: > + Generated from mock_data_config.csv and mock_data_config_details.csv. + Each column in the output corresponds to a variable defined in config. + Only variables with role="enabled" are included by default. + + required_columns: + uid: + type: character + required: true + unique: true + description: > + Unique identifier for each participant. Format: dataset_id + + sequential number (e.g., "cchs2015_00001", "chms3_00001"). + Allows linking across multiple generated files and tracking + individual records. + pattern: "^[a-z0-9_]+_[0-9]{5,}$" + examples: + - "cchs2015_00001" + - "chms3_00042" + - "demport_10234" + + variable_columns: + description: > + All other columns are generated variables from mock_data_config.csv. + Column names match the 'variable' field from config. Data types and + values follow the specifications in mock_data_config_details.csv. + + categorical_variables: + type: numeric + description: > + Categorical variables are numeric codes (1, 2, 3, ...) plus + missing codes (7="Don't know", 8="Refusal", 9="Not stated" or + other configured codes). + + continuous_variables: + type: numeric + description: > + Continuous variables are numeric values within specified ranges, + plus missing codes (7, 8, 9) and potentially contaminated values + (implausible but numeric). + + date_variables: + type: character + format: "YYYY-MM-DD" + description: > + Date variables in ISO 8601 format, plus missing code 9 for + "Not stated" dates. + + survival_variables: + type: numeric + description: > + Time-to-event in days, possibly censored. Missing code 9 for + "Not stated". + + character_variables: + type: character + description: > + Free text or categorical text values. Rarely used in mock data. + + validation: + - "uid column present and unique" + - "No duplicate UIDs within dataset" + - "All variable columns correspond to enabled variables in config" + - "Categorical variables contain only specified categories + missing codes" + - "Continuous variables respect range constraints (except contamination)" + - "Date variables in YYYY-MM-DD format" + - "No NA values (use numeric missing codes instead)" + +# Workflow integration + +workflow: + + generation_process: + step1: + action: "Read configuration files" + functions: + - read_mock_data_config(config_path) + - read_mock_data_config_details(details_path) + validation: "Automatic validation on read (validate = TRUE)" + + step2: + action: "Extract study metadata" + function: get_study_metadata(config) + notes: "Extract rows where role contains 'metadata'" + + step3: + action: "Generate variables in position order" + function: generate_from_config(config_path, details_path, n) + notes: "Loop through enabled variables, call type-specific generators" + + step4: + action: "Type-specific generation" + functions: + - generate_categorical_variable(df_mock, var_row, n, details) + - generate_continuous_variable(df_mock, var_row, n, details) + - generate_survival_variable(df_mock, var_row, n, details) + - generate_date_variable(df_mock, var_row, n, details) + - generate_integer_variable(df_mock, var_row, n, details) + - generate_character_variable(df_mock, var_row, n, details) + notes: "Details parameter passed to access proportions and parameters" + + step5: + action: "Return complete dataset" + output: "data.frame with all enabled variables" + + contamination_workflow: + population_generation: + description: > + Step 1: Generate from population distribution. Extract valid and + missing proportions (must sum to 1.0). Sample category assignment, + generate numeric values for valid category, assign raw codes (7, 8, 9) + to missing categories. + + contamination_application: + description: > + Step 2: Apply contamination. Extract corrupt_* proportions. Identify + valid indices. Sample from valid to corrupt. Replace with values from + contamination ranges. Ensure no overlap (use setdiff for sequential). + + final_distribution: + example: > + Population: 95% valid + 3% DK + 2% NS = 100% + Contamination: 2% corrupt_low + 1% corrupt_high (of valid) + Final: ~93% valid, ~2% corrupt_low, ~1% corrupt_high, 3% DK, 2% NS + +# Versioning and compatibility + +versioning: + current_version: "0.2.0" + previous_version: "0.1.0 (study_config_unified format)" + breaking_changes: + - "Separated variable definitions from distribution details (two files)" + - "Multi-valued comma-separated roles (replaced boolean enabled)" + - "Raw missing codes (configurable, e.g. 7, 8, 9) instead of NA" + - "Contamination model (corrupt_* rows)" + - "Added uid columns for stable variable identifiers" + + migration_from_v01: + status: "Not supported (clean break)" + notes: > + v0.1 (study_config_unified) has been deprecated and removed. + No migration path provided. Users must create new v0.2 configurations + from scratch using generator scripts. + +# Source of truth and synchronization + +source_of_truth: + standalone_mode: + version: "0.2.0 (current)" + description: > + MockData configuration files (mock_data_config.csv + mock_data_config_details.csv) + are the source of truth. Users create these files manually or using generator + scripts. Good for custom mock data and testing-specific scenarios. + + import_mode: + version: "0.3.0+ (planned)" + description: > + MockData can import metadata from recodeflow packages (cchsflow, chmsflow, etc.) + and convert to mock_data_config format. The recodeflow metadata becomes the + source of truth, with MockData configurations derived from it. + + planned_features: + - "import_from_cchsflow() - Convert cchsflow variables.csv to mock_data_config.csv" + - "import_from_chmsflow() - Convert chmsflow variables.csv to mock_data_config.csv" + - "sync_with_source() - Check for updates in source metadata and re-import" + - "Track source and version in config (source='cchsflow', version='2.1.0')" + + synchronization_strategy: + - "Source metadata (cchsflow) tracks variable definitions" + - "MockData adds generation-specific parameters (proportions, contamination)" + - "Periodic sync checks for variable additions/removals in source" + - "User can override imported parameters for testing needs" + + future_considerations: + note: > + Recodeflow universe metadata may require refactoring to support bidirectional + synchronization. This is acceptable and will be coordinated across packages. + +# References and alignment + +alignment: + recodeflow: + file_structure: "catalog.yaml + config.csv + config_details.csv" + metadata_columns: "role, section, subject, labelLong, position" + details_pattern: "recEnd column for parameter names" + folder_structure: "inst/metadata/schemas/ for YAML, inst/extdata/ for CSV" + + cchsflow: + pattern: "variables.csv + variable_details.csv structure" + example_files: + - inst/extdata/variables.csv + - inst/extdata/variable_details.csv + + health_surveys: + raw_codes: "7, 8, 9 (Canadian health survey standards)" + target_surveys: [CCHS, CHMS, DemPoRT, HUIPoRT, HTNPoRT] + +# Dataset catalog integration (Dublin Core metadata schema) + +dataset_catalog: + purpose: > + MockData is a LIBRARY for generating mock data, not a repository of datasets. + Generated datasets are cataloged using Dublin Core metadata aligned with + recodeflow patterns. This section defines the schema for cataloging + MockData-generated datasets. + + catalog_structure: + description: > + Dataset catalog follows Dublin Core metadata standards for describing + mock datasets. Each catalog entry describes a specific mock dataset + (e.g., "CCHS 2015-2016 mock") with source survey information, generation + parameters, and file locations. + + alignment: > + Follows recodeflow pbc_metadata.yaml pattern. Future integration will + register MockData datasets in recodeflow's unified dataset registry. + + dataset_type_classification: + mock_data: + description: "Synthetic data generated by MockData for testing" + purpose: "Testing harmonization workflows, package development, education" + characteristics: + - Realistic distributions matching source surveys + - Configurable contamination for data quality testing + - Reproducible with seed control + + development_data: + description: "Real data subsets for development environments" + purpose: "Algorithm development, code testing" + + production_data: + description: "Full datasets for analysis" + purpose: "Research outputs, publications" + + catalog_metadata_fields: + title: + description: "Dataset title" + required: true + example: "CCHS 2001 Iteration Mock Dataset" + + source_survey: + description: "Source survey information" + required: true + fields: + name: + description: "Full survey name" + example: "Canadian Community Health Survey (CCHS)" + cycle: + description: "Survey cycle or year" + example: "2001" + iteration: + description: "Iteration type (i=iteration, p=provincial, s=special)" + example: "i" + abbreviation: + description: "Short survey identifier" + example: "CCHS 2001" + + description: + description: "Detailed description of the dataset" + required: true + example: > + Mock data generated to replicate the structure and distributions of + CCHS 2001 iteration. Used for testing cchsflow harmonisation workflows + and recodeflow transformations. + + creator: + description: "Dataset creators and affiliations" + required: true + type: "list" + fields: + name: + description: "Creator name" + example: "Big Life Lab" + affiliation: + description: "Institutional affiliation" + example: "University of Ottawa" + + date: + description: "Temporal information" + required: true + fields: + issued: + description: "Date dataset was generated" + format: "YYYY-MM-DD" + example: "2025-11-01" + coverage: + description: "Time period covered by source data" + example: "2001" + + subject: + description: "Keywords and topics" + required: false + type: "list" + examples: + - "Canadian Community Health Survey" + - "health survey" + - "mock data" + - "testing data" + + type: + description: "Resource type" + required: true + allowed_values: ["Mock Dataset", "Development Dataset", "Production Dataset"] + example: "Mock Dataset" + + format: + description: "File format" + required: true + example: "CSV" + + file_location: + description: "Path to dataset file (relative to package root)" + required: true + example: "inst/examples/demport/mock_cchs2001_i.csv" + + identifier: + description: "Unique identifiers for the dataset" + required: true + type: "list" + fields: + type: + description: "Identifier type" + example: "dataset_id" + value: + description: "Identifier value" + example: "cchs_2001_i" + + relation: + description: "Relationships to other resources" + required: false + type: "list" + fields: + type: + description: "Relationship type (Dublin Core)" + allowed_values: ["IsPartOf", "IsDerivedFrom", "Requires", "References"] + identifier: + description: "Related resource identifier" + + rights: + description: "Usage rights and license" + required: true + example: "Open Source" + + technical_details: + description: "MockData-specific technical information" + required: false + fields: + n_rows: + description: "Number of rows (or 'variable' if configurable)" + example: "variable" + generation_method: + description: "Generation approach" + example: "metadata-driven" + metadata_source: + description: "Source metadata files" + example: "cchsflow variables.csv and variable_details.csv" + contamination_model: + description: "Data quality model used" + example: "two-step (distribution + corruption)" + reproducible: + description: "Whether generation is reproducible" + type: "boolean" + example: true + + catalog_storage: + mockdata_examples: + description: "Minimal example datasets included in MockData package" + location: "inst/examples/" + purpose: "Vignettes, testing, demonstration" + scope: "Small illustrative examples only" + catalog_format: "Embedded in mock_data_schema.yaml" + + recodeflow_registry: + description: "Comprehensive dataset catalog (planned v0.3+)" + location: "recodeflow package dataset registry" + purpose: "Unified discovery of all datasets in ecosystem" + scope: "Mock, development, and production datasets" + status: "Future integration" + catalog_format: "Separate YAML following Dublin Core standards" + + example_catalog_entry: + note: > + Example of a complete Dublin Core catalog entry for a MockData-generated + dataset. This demonstrates the schema structure. + + dataset_id: "cchs_2001_i_mock" + dataset_type: "mock_data" + + title: "CCHS 2001 Iteration Mock Dataset" + + source_survey: + name: "Canadian Community Health Survey (CCHS)" + cycle: "2001" + iteration: "i" + abbreviation: "CCHS 2001" + + description: > + Mock data generated to replicate the structure and distributions of + CCHS 2001 iteration. Used for testing cchsflow harmonisation workflows + and recodeflow transformations. + + creator: + - name: "Big Life Lab" + affiliation: "University of Ottawa" + + date: + issued: "2025-11-01" + coverage: "2001" + + subject: + - "Canadian Community Health Survey" + - "health survey" + - "mock data" + - "testing data" + + type: "Mock Dataset" + + format: "CSV" + + file_location: "inst/examples/demport/mock_cchs2001_i.csv" + + identifier: + - type: "dataset_id" + value: "cchs_2001_i" + + relation: + - type: "IsPartOf" + identifier: "MockData" + - type: "IsDerivedFrom" + identifier: "cchsflow" + + rights: "Open Source" + + technical_details: + n_rows: "variable" + generation_method: "metadata-driven" + metadata_source: "cchsflow variables.csv and variable_details.csv" + contamination_model: "two-step (distribution + corruption)" + reproducible: true + + usage_notes: > + MockData focuses on GENERATION capabilities, not dataset storage. + Users generate their own mock datasets as needed. Minimal examples + are included for demonstration only. Future integration with recodeflow + dataset registry will provide comprehensive cataloging across the ecosystem. + +# Package information + +package: + name: MockData + version: 0.2.0 + repository: https://github.com/Big-Life-Lab/mock-data + documentation: https://big-life-lab.github.io/mock-data + + key_functions: + - read_mock_data_config() + - read_mock_data_config_details() + - validate_mock_data_config() + - validate_mock_data_config_details() + - generate_from_config() + - get_study_metadata() + - get_enabled_variables() + - get_variables_by_role() + +# Status and maintenance + +schema_status: + status: active + created: 2025-11-01 + last_updated: 2025-11-01 + maintainer: Big Life Lab + review_frequency: annual + + changelog: + 0.2.0: + date: 2025-11-01 + changes: + - Consolidated all schema specifications into single file + - Merged standalone mock_data_config.yaml and mock_data_config_details.yaml + - Integrated datasets_catalog.yaml schema (Dublin Core metadata fields) + - Added comprehensive recEnd_standardized_values documentation + - Enhanced contamination_model specifications with step-by-step examples + - Expanded role_patterns with complete taxonomy + - Added special_variables documentation (metadata, survival) + - Added dataset_catalog integration section with recodeflow registry reference + - Removed verbose code examples (belong in vignettes) + - Removed harmonized data priority rules (not applicable to raw mock data) + - Made missing codes dataset-agnostic (examples of common patterns, not prescriptive) + - Clarified categorical categories can be numeric, character, or mixed values + - Single source of truth for all MockData configuration structure diff --git a/mockdata-tools/README.md b/mockdata-tools/README.md new file mode 100644 index 0000000..c985b92 --- /dev/null +++ b/mockdata-tools/README.md @@ -0,0 +1,118 @@ +# MockData Validation and Testing Tools + +## Status: Interim Development Tools + +**⚠️ Note**: These validation tools are temporary development utilities that will eventually be replaced by the comprehensive validation infrastructure being developed in the recodeflow and cchsflow packages. + +### Future Migration Plan + +The recodeflow ecosystem is building a unified validation system: + +- **cchsflow v3.0.0**: Developing `schema-validation.R` and `validate_variable_details_csv()` functions + - See `feature/v3.0.0-validation-infrastructure` branch + - CSV validation against YAML schemas + - Standardised validation reporting with R CMD check style output + - Multiple validation modes (basic, collaboration, full) + +- **recodeflow** (planned): Common validation utilities shared across all flow packages + - Centralised metadata validators + - Harmonised variable cleaners + - Shared schema definitions + +Once the unified validation system is mature, these tools should be: +1. Migrated to use the common validation functions +2. Deprecated in favour of recodeflow/cchsflow validators +3. Eventually removed from this package + +For now, these tools remain useful for: +- Quick metadata quality checks during development +- Testing mock data generation across cycles +- Identifying parsing issues specific to MockData + +--- + +## Overview + +This folder contains diagnostic and validation tools for working with MockData and metadata files. These tools help identify issues in metadata, test parsing logic, and validate generated mock data. + +**Quick start:** + +```bash +# Validate metadata quality +Rscript mockdata-tools/validate-metadata.R + +# Test all cycles +Rscript mockdata-tools/test-all-cycles.R + +# Compare different generation approaches +Rscript mockdata-tools/create-comparison.R +``` + +## Tools + +### 1. validate-metadata.R + +**Purpose**: Validate metadata quality and identify common issues + +**What it checks**: +- Valid cycle names in `databaseStart` +- `variableStart` entries parse correctly for all declared cycles +- Format pattern distribution (bracket, mixed, cycle-prefixed, etc.) +- Case sensitivity issues (variables differing only by case) +- Categorical variables have `variable_details` specifications + +**Usage**: + +```bash +Rscript mockdata-tools/validate-metadata.R +``` + +**Output**: R CMD check-style report with errors, warnings, and statistics + +**Exit codes**: +- 0 = passed (with or without warnings) +- 1 = failed (errors found) + +### 2. test-all-cycles.R + +**Purpose**: Test mock data generation across all cycles to verify coverage + +**What it tests**: +- All unique raw variables can be generated +- Coverage percentage for each cycle +- Identifies variables that fail to generate + +**Usage**: + +```bash +Rscript mockdata-tools/test-all-cycles.R +``` + +**Output**: Coverage report showing success/failure counts per cycle + +### 3. create-comparison.R + +**Purpose**: Compare different mock data generation approaches + +**What it does**: +- Generates mock data using different methods +- Compares output structure and values +- Helps validate consistency + +**Usage**: + +```bash +Rscript mockdata-tools/create-comparison.R +``` + +## Development Notes + +- These tools are **excluded from package builds** via `.Rbuildignore` +- They use test data from `inst/extdata/chms/` +- Run from repository root, not from within this directory + +## Related Documentation + +- **cchsflow validation**: See `cchsflow::validate_variable_details_csv()` (v3.0.0+) +- **Metadata schemas**: See `inst/metadata/schemas/` in this package +- **MockData functions**: See `R/mockdata-*.R` for core parsing/generation logic diff --git a/mockdata-tools/create-comparison.R b/mockdata-tools/create-comparison.R new file mode 100644 index 0000000..a983c51 --- /dev/null +++ b/mockdata-tools/create-comparison.R @@ -0,0 +1,392 @@ +# ============================================================================== +# Create Objective Comparison: Current vs MockData Functions +# ============================================================================== +# +# Purpose: Generate comparison table and CSV showing differences between +# current manual approach and new mockdata functions approach +# Date: 2025-10-17 + +library(readr) +library(dplyr) + +# Source MockData functions +source("R/mockdata-parsers.R") +source("R/mockdata-helpers.R") +source("R/create_cat_var.R") +source("R/create_con_var.R") # parse_variable_start +source("R/mockdata-helpers.R") # get_cycle_variables, get_raw_variables + +# Load metadata +variables <- read_csv("inst/extdata/chms/chms-variables.csv", show_col_types = FALSE) +variable_details <- read_csv("inst/extdata/chms/chms-variable-details.csv", show_col_types = FALSE) + +# Load all current manual data +load("data/cycle1.rda") +load("data/cycle1_meds.rda") +load("data/cycle2.rda") +load("data/cycle2_meds.rda") +load("data/cycle3.rda") +load("data/cycle3_meds.rda") +load("data/cycle4.rda") +load("data/cycle4_meds.rda") +load("data/cycle5.rda") +load("data/cycle5_meds.rda") +load("data/cycle6.rda") +load("data/cycle6_meds.rda") + +# Define cycles in canonical order +cycles_list <- list( + cycle1 = cycle1, + cycle1_meds = cycle1_meds, + cycle2 = cycle2, + cycle2_meds = cycle2_meds, + cycle3 = cycle3, + cycle3_meds = cycle3_meds, + cycle4 = cycle4, + cycle4_meds = cycle4_meds, + cycle5 = cycle5, + cycle5_meds = cycle5_meds, + cycle6 = cycle6, + cycle6_meds = cycle6_meds +) + +cat("=== Creating Comparison ===\n\n") + +# Storage for results +all_differences <- list() +summary_stats <- data.frame( + cycle = character(), + current_count = integer(), + mockdata_functions_count = integer(), + difference = integer(), + stringsAsFactors = FALSE +) + +# Function to categorize why a variable is missing +categorize_missing <- function(var, cycle, in_current, in_mockdata) { + # Check if it's in variables.csv + in_vars_csv <- var %in% variables$variable + + # Check if it's in variable_details for this cycle + in_var_details <- nrow(variable_details[ + variable_details$variable == var & + grepl(cycle, variable_details$databaseStart, fixed = TRUE), ]) > 0 + + # Check if it exists in other cycles + if (in_vars_csv) { + var_row <- variables[variables$variable == var, ] + cycles_available <- var_row$databaseStart[1] + } else { + cycles_available <- NA + } + + # Categorize + if (!in_current && in_mockdata) { + # In mockdata functions but not current + return(list( + category = "Metadata-driven", + detail = "Variable exists in metadata but not included in current manual data" + )) + } else if (in_current && !in_mockdata) { + # In current but not mockdata functions + if (!in_vars_csv) { + return(list( + category = "Not in metadata", + detail = "Variable in current data but not found in variables.csv" + )) + } else if (!in_var_details) { + # Check if it's in a different cycle + if (!is.na(cycles_available) && !grepl(cycle, cycles_available, fixed = TRUE)) { + return(list( + category = "Wrong cycle", + detail = sprintf("Variable only exists in: %s", cycles_available) + )) + } else { + return(list( + category = "Not in variable_details", + detail = sprintf("Variable in variables.csv but no specs for %s in variable_details", cycle) + )) + } + } + } + + return(list(category = "Unknown", detail = "Needs investigation")) +} + +# Function to check for naming differences +check_naming_difference <- function(var, cycle) { + # Check if this is a harmonized variable name with different raw name + if (var %in% variables$variable) { + var_row <- variables[variables$variable == var, ] + var_start <- var_row$variableStart[1] + + # Try to extract cycle-specific raw name + cycle_pattern <- paste0(cycle, "::") + if (grepl(cycle_pattern, var_start, fixed = TRUE)) { + # Extract raw name for this cycle + segments <- unlist(strsplit(var_start, ",")) + segments <- trimws(segments) + matching <- segments[grepl(cycle_pattern, segments, fixed = TRUE)] + if (length(matching) > 0) { + raw_name <- sub(paste0("^.*", cycle, "::"), "", matching[1]) + raw_name <- trimws(raw_name) + if (raw_name != var) { + return(raw_name) + } + } + } + } + return(NULL) +} + +# Process each cycle +for (cycle_name in names(cycles_list)) { + cat(sprintf("Processing %s...\n", cycle_name)) + + current_data <- cycles_list[[cycle_name]] + current_vars <- names(current_data) + + # Get mockdata functions variables + raw_vars_all <- get_raw_variables(cycle_name, variables, variable_details, include_derived = FALSE) + mockdata_vars <- if (nrow(raw_vars_all) > 0) raw_vars_all$variable_raw else character() + + # Find differences + only_in_current <- setdiff(current_vars, mockdata_vars) + only_in_mockdata <- setdiff(mockdata_vars, current_vars) + + # Store summary stats + summary_stats <- rbind(summary_stats, data.frame( + cycle = cycle_name, + current_count = length(current_vars), + mockdata_functions_count = length(mockdata_vars), + difference = length(mockdata_vars) - length(current_vars), + stringsAsFactors = FALSE + )) + + # Process variables only in current + for (var in only_in_current) { + # Check if this is a naming difference + raw_name <- check_naming_difference(var, cycle_name) + + if (!is.null(raw_name) && raw_name %in% mockdata_vars) { + # This is a naming difference + cat_info <- list( + category = "Raw vs harmonized name", + detail = sprintf("Current uses harmonized name '%s', mockdata functions uses raw name '%s'", + var, raw_name) + ) + } else { + # Variable genuinely missing from mockdata functions + cat_info <- categorize_missing(var, cycle_name, TRUE, FALSE) + } + + all_differences[[length(all_differences) + 1]] <- data.frame( + cycle = cycle_name, + variable = var, + in_current = TRUE, + in_mockdata_functions = FALSE, + explanation_category = cat_info$category, + explanation_detail = cat_info$detail, + stringsAsFactors = FALSE + ) + } + + # Process variables only in mockdata functions + for (var in only_in_mockdata) { + # Check if current has the harmonized version + harmonized_in_current <- FALSE + harmonized_name <- NULL + + # Check if this raw variable corresponds to a harmonized variable in current + matching_vars <- variables[grepl(paste0("\\[", var, "\\]"), variables$variableStart, fixed = TRUE) | + grepl(paste0(cycle_name, "::", var), variables$variableStart, fixed = TRUE), ] + + if (nrow(matching_vars) > 0) { + for (i in seq_len(nrow(matching_vars))) { + harmonized_name <- matching_vars$variable[i] + if (harmonized_name %in% current_vars) { + harmonized_in_current <- TRUE + break + } + } + } + + if (harmonized_in_current) { + # This is a naming difference (reverse direction) + cat_info <- list( + category = "Raw vs harmonized name", + detail = sprintf("Mockdata functions uses raw name '%s', current uses harmonized name '%s'", + var, harmonized_name) + ) + } else { + # Variable genuinely not in current + cat_info <- categorize_missing(var, cycle_name, FALSE, TRUE) + } + + all_differences[[length(all_differences) + 1]] <- data.frame( + cycle = cycle_name, + variable = var, + in_current = FALSE, + in_mockdata_functions = TRUE, + explanation_category = cat_info$category, + explanation_detail = cat_info$detail, + stringsAsFactors = FALSE + ) + } +} + +# Combine all differences +differences_df <- do.call(rbind, all_differences) + +# Write CSV +write.csv(differences_df, "MOCKDATA_COMPARISON.csv", row.names = FALSE) +cat("\nWrote MOCKDATA_COMPARISON.csv\n") + +# Create markdown +md_lines <- c( + "# MockData Comparison: Current vs MockData Functions", + "", + "**Date**: 2025-10-17", + "**Purpose**: Objective comparison of variable coverage between current manual approach (prep-dummy-data.R) and new metadata-driven mockdata functions", + "", + "## Overview", + "", + "This document compares two approaches to generating mock data for chmsflow:", + "", + "1. **Current**: Manual approach in `data-raw/prep-dummy-data.R` - hand-coded variable ranges", + "2. **MockData Functions**: Automated metadata-driven approach using modular functions in `R/`", + "", + "### Methodology", + "", + "- Loaded all 12 existing mock datasets (cycle1-6 and cycle1_meds-cycle6_meds)", + "- Generated variable lists using mockdata functions for same 12 cycles", + "- Compared variable names between approaches", + "- Categorized differences by type", + "- **Only differences are shown** (variables present in both approaches are not listed)", + "", + "---", + "", + "## Summary Statistics", + "", + "| Cycle | Current | MockData Functions | Difference | Notes |", + "|-------|---------|-------------------|------------|-------|" +) + +# Add summary table rows +for (i in seq_len(nrow(summary_stats))) { + row <- summary_stats[i, ] + diff_str <- sprintf("%+d", row$difference) + if (row$difference > 0) { + diff_str <- paste0(diff_str, " mockdata functions") + } else if (row$difference < 0) { + diff_str <- paste0(diff_str, " current") + } else { + diff_str <- "0" + } + + md_lines <- c(md_lines, + sprintf("| %s | %d | %d | %s | |", + row$cycle, row$current_count, row$mockdata_functions_count, diff_str)) +} + +# Add totals +total_current <- sum(summary_stats$current_count) +total_mockdata <- sum(summary_stats$mockdata_functions_count) +total_diff <- total_mockdata - total_current + +md_lines <- c(md_lines, + sprintf("| **TOTAL** | **%d** | **%d** | **%+d** | |", + total_current, total_mockdata, total_diff)) + +md_lines <- c(md_lines, + "", + "---", + "", + "## Detailed Differences by Cycle", + "", + "**Legend**:", + "- βœ“ = Variable present in this approach", + "- βœ— = Variable absent from this approach", + "") + +# Add detailed differences by cycle +for (cycle_name in names(cycles_list)) { + cycle_diffs <- differences_df[differences_df$cycle == cycle_name, ] + + if (nrow(cycle_diffs) == 0) { + next + } + + md_lines <- c(md_lines, + sprintf("### %s", cycle_name), + "", + sprintf("**Differences**: %d variables", nrow(cycle_diffs)), + "", + "| Variable | Current | MockData Functions | Explanation |", + "|----------|---------|-------------------|-------------|") + + for (i in seq_len(nrow(cycle_diffs))) { + diff <- cycle_diffs[i, ] + current_mark <- if (diff$in_current) "βœ“" else "βœ—" + mockdata_mark <- if (diff$in_mockdata_functions) "βœ“" else "βœ—" + + md_lines <- c(md_lines, + sprintf("| %s | %s | %s | %s |", + diff$variable, current_mark, mockdata_mark, diff$explanation_detail)) + } + + md_lines <- c(md_lines, "") +} + +# Add methodology notes +md_lines <- c(md_lines, + "---", + "", + "## Explanation Categories", + "", + "**Raw vs harmonized name**: Variable exists in both but with different names. Current uses harmonized name (e.g., `ammdmva1`), mockdata functions uses raw cycle-specific name (e.g., `amsdmva1` for cycle1).", + "", + "**Not in metadata**: Variable present in current data but not found in `variables.csv`. May be real CHMS variable not included in harmonization, or outdated/incorrect variable name.", + "", + "**Wrong cycle**: Variable exists in metadata but for different cycles. Example: `paadtot` exists in cycle3+ but current includes it in cycle1.", + "", + "**Metadata-driven**: Variable exists in metadata with harmonization specifications but was not included in current manual data. Mockdata functions includes all variables from metadata.", + "", + "**Not in variable_details**: Variable found in `variables.csv` but no recoding specifications for this cycle in `variable_details.csv`.", + "", + "---", + "", + "## Files", + "", + "**Machine-readable data**: [MOCKDATA_COMPARISON.csv](MOCKDATA_COMPARISON.csv)", + "", + "**Current approach**: [data-raw/prep-dummy-data.R](data-raw/prep-dummy-data.R)", + "", + "**MockData functions**:", + "- [R/create_cat_var.R](R/create_cat_var.R)", + "- [R/create_con_var.R](R/create_con_var.R)", + "- [R/parse-range-notation.R](R/parse-range-notation.R)", + "- [data-raw/test-all-cycles.R](data-raw/test-all-cycles.R)", + "", + "---", + "", + "## Next Steps", + "", + "This comparison identifies differences for team review. Key questions:", + "", + "1. Should mock data use raw or harmonized variable names?", + "2. Should variables not in metadata (e.g., gen_015) be included?", + "3. Is current coverage (72-75 vars/cycle) intentionally minimal or should it be comprehensive?", + "4. Should variables from wrong cycles (e.g., paadtot in cycle1) be removed?", + "", + "See [MOCKDATA_QUESTIONS.md](MOCKDATA_QUESTIONS.md) for detailed questions.") + +# Write markdown +writeLines(md_lines, "MOCKDATA_COMPARISON.md") +cat("Wrote MOCKDATA_COMPARISON.md\n") + +cat(sprintf("\n=== Summary ===\n")) +cat(sprintf("Total differences identified: %d\n", nrow(differences_df))) +cat(sprintf("Total current variables: %d\n", total_current)) +cat(sprintf("Total mockdata functions variables: %d\n", total_mockdata)) +cat(sprintf("Difference: %+d\n", total_diff)) diff --git a/mockdata-tools/test-all-cycles.R b/mockdata-tools/test-all-cycles.R new file mode 100644 index 0000000..ffa5c8e --- /dev/null +++ b/mockdata-tools/test-all-cycles.R @@ -0,0 +1,345 @@ +# ============================================================================== +# Test Modular MockData Across All Cycles +# ============================================================================== +# +# Purpose: Test modular functions across all cycles and compare to manual approach +# Date: 2025-10-17 + +library(readr) +library(dplyr) + +# Source MockData functions +source("R/mockdata-parsers.R") +source("R/mockdata-helpers.R") +source("R/create_cat_var.R") +source("R/create_con_var.R") + +# Load metadata +variables <- read_csv("inst/extdata/chms/chms-variables.csv", show_col_types = FALSE) +variable_details <- read_csv("inst/extdata/chms/chms-variable-details.csv", show_col_types = FALSE) + +cat("\n=== Testing Modular MockData Across All Cycles ===\n\n") + +# Define cycles to test (based on prep-dummy-data.R) +cycles <- c("cycle1", "cycle2", "cycle3", "cycle4", "cycle5", "cycle6") +cycle_meds <- c("cycle1_meds", "cycle2_meds", "cycle3_meds", "cycle4_meds", "cycle5_meds", "cycle6_meds") + +# Storage for results +all_results <- list() + +# ============================================================================== +# Test each cycle +# ============================================================================== + +for (cycle in cycles) { + cat(sprintf("Testing %s...\n", cycle)) + + # Get raw variables for this cycle + raw_vars_all <- get_raw_variables(cycle, variables, variable_details, include_derived = FALSE) + + if (nrow(raw_vars_all) == 0) { + cat(sprintf(" No variables found for %s\n\n", cycle)) + next + } + + raw_vars_cat <- raw_vars_all[raw_vars_all$variableType == "Categorical", ] + raw_vars_con <- raw_vars_all[raw_vars_all$variableType == "Continuous", ] + + # Generate mock data + df_mock <- data.frame() + n_obs <- 50 # Match prep-dummy-data.R + success_cat <- 0 + success_con <- 0 + failed_vars <- character() + + # Categorical variables + for (i in seq_len(nrow(raw_vars_cat))) { + var_raw <- raw_vars_cat$variable_raw[i] + + result <- create_cat_var( + var_raw = var_raw, + cycle = cycle, + variable_details = variable_details, + variables = variables, + length = n_obs, + df_mock = df_mock, + prop_NA = NULL, + seed = 123 # Match prep-dummy-data.R + ) + + if (!is.null(result)) { + if (ncol(df_mock) == 0) { + df_mock <- result + } else { + df_mock <- cbind(df_mock, result) + } + success_cat <- success_cat + 1 + } else { + failed_vars <- c(failed_vars, var_raw) + } + } + + # Continuous variables + for (i in seq_len(nrow(raw_vars_con))) { + var_raw <- raw_vars_con$variable_raw[i] + + result <- suppressWarnings(create_con_var( + var_raw = var_raw, + cycle = cycle, + variable_details = variable_details, + variables = variables, + length = n_obs, + df_mock = df_mock, + prop_NA = NULL, + seed = 123, + distribution = "uniform" + )) + + if (!is.null(result)) { + if (ncol(df_mock) == 0) { + df_mock <- result + } else { + df_mock <- cbind(df_mock, result) + } + success_con <- success_con + 1 + } else { + failed_vars <- c(failed_vars, var_raw) + } + } + + # Calculate statistics + total_vars <- nrow(raw_vars_all) + total_success <- success_cat + success_con + coverage_pct <- if (total_vars > 0) 100 * total_success / total_vars else 0 + + # Store results + all_results[[cycle]] <- list( + total_raw_vars = total_vars, + categorical = nrow(raw_vars_cat), + continuous = nrow(raw_vars_con), + generated_cat = success_cat, + generated_con = success_con, + generated_total = total_success, + coverage_pct = coverage_pct, + failed_vars = failed_vars, + mock_data_cols = ncol(df_mock) + ) + + # Print summary + cat(sprintf(" Raw variables: %d (cat: %d, con: %d)\n", + total_vars, nrow(raw_vars_cat), nrow(raw_vars_con))) + cat(sprintf(" Generated: %d/%d (%.1f%%)\n", + total_success, total_vars, coverage_pct)) + cat(sprintf(" Mock data: %d rows Γ— %d columns\n", + nrow(df_mock), ncol(df_mock))) + + if (length(failed_vars) > 0) { + cat(sprintf(" Failed: %d variables\n", length(failed_vars))) + } + + cat("\n") +} + +# ============================================================================== +# Test meds cycles +# ============================================================================== + +for (cycle in cycle_meds) { + cat(sprintf("Testing %s...\n", cycle)) + + # Get raw variables for this cycle + raw_vars_all <- get_raw_variables(cycle, variables, variable_details, include_derived = FALSE) + + if (nrow(raw_vars_all) == 0) { + cat(sprintf(" No variables found for %s\n\n", cycle)) + all_results[[cycle]] <- list( + total_raw_vars = 0, + categorical = 0, + continuous = 0, + generated_cat = 0, + generated_con = 0, + generated_total = 0, + coverage_pct = 0, + failed_vars = character(), + mock_data_cols = 0 + ) + next + } + + raw_vars_cat <- raw_vars_all[raw_vars_all$variableType == "Categorical", ] + raw_vars_con <- raw_vars_all[raw_vars_all$variableType == "Continuous", ] + + # Generate mock data + df_mock <- data.frame() + n_obs <- 50 + success_cat <- 0 + success_con <- 0 + failed_vars <- character() + + # Categorical variables + for (i in seq_len(nrow(raw_vars_cat))) { + var_raw <- raw_vars_cat$variable_raw[i] + + result <- create_cat_var( + var_raw = var_raw, + cycle = cycle, + variable_details = variable_details, + variables = variables, + length = n_obs, + df_mock = df_mock, + prop_NA = NULL, + seed = 123 + ) + + if (!is.null(result)) { + if (ncol(df_mock) == 0) { + df_mock <- result + } else { + df_mock <- cbind(df_mock, result) + } + success_cat <- success_cat + 1 + } else { + failed_vars <- c(failed_vars, var_raw) + } + } + + # Continuous variables + for (i in seq_len(nrow(raw_vars_con))) { + var_raw <- raw_vars_con$variable_raw[i] + + result <- suppressWarnings(create_con_var( + var_raw = var_raw, + cycle = cycle, + variable_details = variable_details, + variables = variables, + length = n_obs, + df_mock = df_mock, + prop_NA = NULL, + seed = 123, + distribution = "uniform" + )) + + if (!is.null(result)) { + if (ncol(df_mock) == 0) { + df_mock <- result + } else { + df_mock <- cbind(df_mock, result) + } + success_con <- success_con + 1 + } else { + failed_vars <- c(failed_vars, var_raw) + } + } + + # Calculate statistics + total_vars <- nrow(raw_vars_all) + total_success <- success_cat + success_con + coverage_pct <- if (total_vars > 0) 100 * total_success / total_vars else 0 + + # Store results + all_results[[cycle]] <- list( + total_raw_vars = total_vars, + categorical = nrow(raw_vars_cat), + continuous = nrow(raw_vars_con), + generated_cat = success_cat, + generated_con = success_con, + generated_total = total_success, + coverage_pct = coverage_pct, + failed_vars = failed_vars, + mock_data_cols = ncol(df_mock) + ) + + # Print summary + cat(sprintf(" Raw variables: %d (cat: %d, con: %d)\n", + total_vars, nrow(raw_vars_cat), nrow(raw_vars_con))) + cat(sprintf(" Generated: %d/%d (%.1f%%)\n", + total_success, total_vars, coverage_pct)) + cat(sprintf(" Mock data: %d rows Γ— %d columns\n", + nrow(df_mock), ncol(df_mock))) + + if (length(failed_vars) > 0) { + cat(sprintf(" Failed: %d variables (%s)\n", + length(failed_vars), + paste(head(failed_vars, 3), collapse=", "))) + } + + cat("\n") +} + +# ============================================================================== +# Summary comparison +# ============================================================================== + +cat("=== Overall Summary ===\n\n") + +# Create summary table +summary_df <- data.frame( + cycle = names(all_results), + total_vars = sapply(all_results, function(x) x$total_raw_vars), + categorical = sapply(all_results, function(x) x$categorical), + continuous = sapply(all_results, function(x) x$continuous), + generated = sapply(all_results, function(x) x$generated_total), + coverage_pct = sapply(all_results, function(x) x$coverage_pct), + stringsAsFactors = FALSE +) + +print(summary_df) + +cat("\n") + +# Overall statistics +total_vars_all_cycles <- sum(summary_df$total_vars) +total_generated_all_cycles <- sum(summary_df$generated) +overall_coverage <- if (total_vars_all_cycles > 0) { + 100 * total_generated_all_cycles / total_vars_all_cycles +} else { + 0 +} + +cat(sprintf("Overall across all cycles:\n")) +cat(sprintf(" Total raw variables: %d\n", total_vars_all_cycles)) +cat(sprintf(" Generated: %d (%.1f%%)\n", total_generated_all_cycles, overall_coverage)) + +# Compare to prep-dummy-data.R +cat("\n=== Comparison to prep-dummy-data.R ===\n\n") + +# Count variables in prep-dummy-data.R (manually coded) +prep_dummy_counts <- list( + cycle1 = 72, # Counted from lines 13-92 + cycle1_meds = 70, # Counted from lines 94-171 + cycle2 = 72, # Counted from lines 179-258 + cycle2_meds = 70, # Counted from lines 260-337 + cycle3 = 73, # Counted from lines 345-428 + cycle3_meds = 3, # Lines 434-438 (clinicid, meucatc, npi_25b) + cycle4 = 73, # Counted from lines 446-529 + cycle4_meds = 3, # Lines 535-539 + cycle5 = 75, # Counted from lines 547-626 + cycle5_meds = 3, # Lines 632-636 + cycle6 = 75, # Counted from lines 644-722 + cycle6_meds = 3 # Lines 728-732 +) + +cat("prep-dummy-data.R manually codes:\n") +for (cycle_name in names(prep_dummy_counts)) { + manual_count <- prep_dummy_counts[[cycle_name]] + modular_count <- if (cycle_name %in% names(all_results)) { + all_results[[cycle_name]]$mock_data_cols + } else { + 0 + } + + diff <- modular_count - manual_count + pct_of_manual <- if (manual_count > 0) 100 * modular_count / manual_count else 0 + + cat(sprintf(" %s: manual=%d, modular=%d (%.1f%%) %s\n", + cycle_name, + manual_count, + modular_count, + pct_of_manual, + if (diff > 0) sprintf("+%d more", diff) else if (diff < 0) sprintf("%d fewer", abs(diff)) else "equal")) +} + +cat("\n=== CONCLUSION ===\n\n") +cat("The modular approach automatically generates mock data from metadata,\n") +cat("eliminating the need to manually code each variable's range for each cycle.\n") +cat(sprintf("Overall coverage: %.1f%% of raw variables across all cycles\n", overall_coverage)) diff --git a/mockdata-tools/validate-metadata.R b/mockdata-tools/validate-metadata.R new file mode 100644 index 0000000..377371d --- /dev/null +++ b/mockdata-tools/validate-metadata.R @@ -0,0 +1,327 @@ +#!/usr/bin/env Rscript +# Validate metadata consistency and identify potential issues +# This script checks for common metadata errors that could affect MockData generation + +# Source MockData parser functions +source("R/mockdata-parsers.R") +source("R/mockdata-helpers.R") +source("R/create_cat_var.R") +source("R/create_con_var.R") + +# Load metadata (CHMS example) +variables <- read.csv("inst/extdata/chms/chms-variables.csv", stringsAsFactors = FALSE) +variable_details <- read.csv("inst/extdata/chms/chms-variable-details.csv", stringsAsFactors = FALSE) + +cat("=== METADATA VALIDATION REPORT ===\n\n") + +# Valid cycle names +valid_cycles <- c("cycle1", "cycle2", "cycle3", "cycle4", "cycle5", "cycle6", "cycle7", + "cycle1_meds", "cycle2_meds", "cycle3_meds", + "cycle4_meds", "cycle5_meds", "cycle6_meds") + +errors <- list() +warnings <- list() +info <- list() + +# ============================================================================ +# Check 1: databaseStart contains only valid cycles +# ============================================================================ +cat("CHECK 1: Validating databaseStart cycles\n") +cat("-------------------------------------------\n") + +for (i in 1:nrow(variables)) { + var_name <- variables$variable[i] + db_start <- variables$databaseStart[i] + + if (is.na(db_start) || db_start == "") { + errors <- c(errors, paste0("Variable '", var_name, "': databaseStart is empty")) + next + } + + cycles <- strsplit(db_start, ",")[[1]] + cycles <- trimws(cycles) + + invalid_cycles <- cycles[!cycles %in% valid_cycles] + if (length(invalid_cycles) > 0) { + errors <- c(errors, paste0("Variable '", var_name, "': Invalid cycles in databaseStart: ", + paste(invalid_cycles, collapse = ", "))) + } +} + +if (length(errors) == 0) { + cat("βœ“ All databaseStart cycles are valid\n\n") +} else { + cat("βœ— Found", length(errors), "errors\n\n") +} + +# ============================================================================ +# Check 2: variableStart parses correctly for all declared cycles +# ============================================================================ +cat("CHECK 2: Validating variableStart parsing\n") +cat("-------------------------------------------\n") + +parse_errors <- list() +parse_warnings <- list() + +for (i in 1:nrow(variables)) { + var_name <- variables$variable[i] + var_start <- variables$variableStart[i] + db_start <- variables$databaseStart[i] + + if (is.na(var_start) || var_start == "") { + errors <- c(errors, paste0("Variable '", var_name, "': variableStart is empty")) + next + } + + # Skip DerivedVar for this check (they're expected to return NULL) + if (grepl("^DerivedVar::", var_start)) { + next + } + + # Get cycles for this variable + cycles <- strsplit(db_start, ",")[[1]] + cycles <- trimws(cycles) + cycles <- cycles[cycles %in% valid_cycles] # Only valid cycles + + # Try parsing for each cycle + for (cycle in cycles) { + result <- parse_variable_start(var_start, cycle) + + if (is.null(result)) { + parse_errors <- c(parse_errors, + paste0("Variable '", var_name, "' (", cycle, "): ", + "Failed to parse variableStart: '", var_start, "'")) + } else { + # Check if parsed name makes sense + # Warning: parsed name very different from variable name might indicate error + if (nchar(result) > 0 && nchar(var_name) > 0) { + # Simple check: do they share any common substring? + result_lower <- tolower(result) + var_lower <- tolower(var_name) + + # Remove common prefixes/suffixes for comparison + result_clean <- gsub("^(gen_|lab_|ccc_|alc_|smk_)", "", result_lower) + var_clean <- gsub("^(gen_|lab_|ccc_|alc_|smk_)", "", var_lower) + + # If completely different (no overlap), might be worth checking + if (!grepl(substr(result_clean, 1, 3), var_clean) && + !grepl(substr(var_clean, 1, 3), result_clean)) { + parse_warnings <- c(parse_warnings, + paste0("Variable '", var_name, "' (", cycle, "): ", + "Parsed name '", result, "' differs significantly. ", + "variableStart: '", var_start, "'")) + } + } + } + } +} + +errors <- c(errors, parse_errors) +warnings <- c(warnings, parse_warnings) + +if (length(parse_errors) == 0) { + cat("βœ“ All non-DerivedVar variableStart entries parse successfully\n") +} else { + cat("βœ— Found", length(parse_errors), "parse errors\n") +} + +if (length(parse_warnings) > 0) { + cat("⚠ Found", length(parse_warnings), "potential naming inconsistencies\n") +} +cat("\n") + +# ============================================================================ +# Check 3: Identify variableStart format patterns +# ============================================================================ +cat("CHECK 3: variableStart format patterns\n") +cat("---------------------------------------\n") + +format_counts <- list( + bracket = 0, # [varname] + cycle_prefixed = 0, # cycle1::varname + mixed = 0, # cycle1::var1, [var2] + derived_var = 0, # DerivedVar::[...] + plain = 0, # varname + unknown = 0 +) + +format_examples <- list( + bracket = c(), + cycle_prefixed = c(), + mixed = c(), + derived_var = c(), + plain = c(), + unknown = c() +) + +for (i in 1:nrow(variables)) { + var_name <- variables$variable[i] + var_start <- variables$variableStart[i] + + if (is.na(var_start) || var_start == "") next + + # Classify format + if (grepl("^DerivedVar::", var_start)) { + format_counts$derived_var <- format_counts$derived_var + 1 + if (length(format_examples$derived_var) < 3) { + format_examples$derived_var <- c(format_examples$derived_var, + paste0(var_name, ": ", substr(var_start, 1, 50))) + } + } else if (grepl("::", var_start) && grepl("\\[", var_start)) { + # Has both :: and [] + format_counts$mixed <- format_counts$mixed + 1 + if (length(format_examples$mixed) < 5) { + format_examples$mixed <- c(format_examples$mixed, + paste0(var_name, ": ", var_start)) + } + } else if (grepl("::", var_start)) { + format_counts$cycle_prefixed <- format_counts$cycle_prefixed + 1 + if (length(format_examples$cycle_prefixed) < 3) { + format_examples$cycle_prefixed <- c(format_examples$cycle_prefixed, + paste0(var_name, ": ", var_start)) + } + } else if (grepl("^\\[.*\\]$", var_start)) { + format_counts$bracket <- format_counts$bracket + 1 + if (length(format_examples$bracket) < 3) { + format_examples$bracket <- c(format_examples$bracket, + paste0(var_name, ": ", var_start)) + } + } else if (!grepl("\\[", var_start) && !grepl("::", var_start)) { + format_counts$plain <- format_counts$plain + 1 + if (length(format_examples$plain) < 3) { + format_examples$plain <- c(format_examples$plain, + paste0(var_name, ": ", var_start)) + } + } else { + format_counts$unknown <- format_counts$unknown + 1 + format_examples$unknown <- c(format_examples$unknown, + paste0(var_name, ": ", var_start)) + } +} + +cat("Format distribution:\n") +cat(sprintf(" Bracket format [varname]: %4d variables\n", format_counts$bracket)) +cat(sprintf(" Cycle-prefixed cycle::varname: %4d variables\n", format_counts$cycle_prefixed)) +cat(sprintf(" Mixed cycle::var, [var]: %4d variables\n", format_counts$mixed)) +cat(sprintf(" DerivedVar:: %4d variables\n", format_counts$derived_var)) +cat(sprintf(" Plain varname: %4d variables\n", format_counts$plain)) +cat(sprintf(" Unknown format: %4d variables\n", format_counts$unknown)) +cat("\n") + +# Show examples of mixed format (key concern) +if (format_counts$mixed > 0) { + cat("⚠ MIXED FORMAT EXAMPLES (cycle::var, [var]):\n") + for (ex in format_examples$mixed) { + cat(" ", ex, "\n") + } + cat("\n") + cat("QUESTION: Are mixed formats intentional?\n") + cat(" - Is [var] a fallback for cycles without explicit cycle::var?\n") + cat(" - Should Strategy 2b in parse_variable_start use bracket segment?\n") + cat(" - Or should metadata be expanded to have cycle2::var2, cycle3::var3, etc?\n\n") +} + +# ============================================================================ +# Check 4: Case sensitivity issues +# ============================================================================ +cat("CHECK 4: Case sensitivity check\n") +cat("--------------------------------\n") + +# Check if any variable names differ only by case +var_names_lower <- tolower(variables$variable) +duplicates <- var_names_lower[duplicated(var_names_lower)] + +if (length(duplicates) > 0) { + cat("⚠ Found variables that differ only by case:\n") + for (dup in unique(duplicates)) { + matches <- variables$variable[var_names_lower == dup] + cat(" ", paste(matches, collapse = " vs "), "\n") + } + cat("\n") +} else { + cat("βœ“ No case-only duplicates found\n\n") +} + +# ============================================================================ +# Check 5: Categorical variables have variable_details +# ============================================================================ +cat("CHECK 5: Categorical variables have specifications\n") +cat("----------------------------------------------------\n") + +missing_details <- c() + +categorical_vars <- variables[variables$variableType == "Categorical", ] +for (i in 1:nrow(categorical_vars)) { + var_name <- categorical_vars$variable[i] + db_start <- categorical_vars$databaseStart[i] + var_start <- categorical_vars$variableStart[i] + + # Skip DerivedVar (they don't need variable_details) + if (grepl("^DerivedVar::", var_start)) { + next + } + + # Check if variable has any variable_details entries + has_details <- any(variable_details$variable == var_name) + + if (!has_details) { + missing_details <- c(missing_details, + paste0("Variable '", var_name, "': Categorical but no variable_details entries")) + } +} + +if (length(missing_details) > 0) { + cat("⚠ Found", length(missing_details), "categorical variables without variable_details\n") + cat("First 10:\n") + for (i in 1:min(10, length(missing_details))) { + cat(" ", missing_details[i], "\n") + } + if (length(missing_details) > 10) { + cat(" ... and", length(missing_details) - 10, "more\n") + } + cat("\n") +} else { + cat("βœ“ All non-DerivedVar categorical variables have variable_details\n\n") +} + +warnings <- c(warnings, missing_details) + +# ============================================================================ +# SUMMARY +# ============================================================================ +cat("=== VALIDATION SUMMARY ===\n\n") + +cat("ERRORS:", length(errors), "\n") +if (length(errors) > 0) { + for (err in errors) { + cat(" βœ—", err, "\n") + } + cat("\n") +} + +cat("WARNINGS:", length(warnings), "\n") +if (length(warnings) > 0 && length(warnings) <= 20) { + for (warn in warnings) { + cat(" ⚠", warn, "\n") + } + cat("\n") +} else if (length(warnings) > 20) { + cat(" (Too many to display - see detailed output above)\n\n") +} + +cat("INFO:\n") +cat(" Total variables:", nrow(variables), "\n") +cat(" Total variable_details entries:", nrow(variable_details), "\n") +cat(" Unique variables in variable_details:", length(unique(variable_details$variable)), "\n") + +# Exit code +if (length(errors) > 0) { + cat("\n❌ VALIDATION FAILED\n") + quit(status = 1) +} else if (length(warnings) > 0) { + cat("\n⚠️ VALIDATION PASSED WITH WARNINGS\n") + quit(status = 0) +} else { + cat("\nβœ… VALIDATION PASSED\n") + quit(status = 0) +} diff --git a/pkgdown/extra.css b/pkgdown/extra.css new file mode 100644 index 0000000..998ccd2 --- /dev/null +++ b/pkgdown/extra.css @@ -0,0 +1,33 @@ +/* Quarto-style callouts for pkgdown */ +/* Styles blockquotes in article content to look like Quarto callout-note */ + +.page-body blockquote { + margin: 1.5em 0; + padding: 1em 1em 1em 3em; + border-left: 5px solid #2196F3; + background-color: #e3f2fd; + border-radius: 0.25rem; + position: relative; +} + +.page-body blockquote::before { + content: "ℹ️"; + position: absolute; + left: 0.75em; + top: 1em; + font-size: 1.2em; +} + +.page-body blockquote p:first-child { + margin-top: 0; + font-weight: 600; + color: #1976D2; +} + +.page-body blockquote p { + margin-bottom: 0.5em; +} + +.page-body blockquote p:last-child { + margin-bottom: 0; +} diff --git a/renv.lock b/renv.lock new file mode 100644 index 0000000..e6a6d32 --- /dev/null +++ b/renv.lock @@ -0,0 +1,4617 @@ +{ + "R": { + "Version": "4.4.2", + "Repositories": [ + { + "Name": "CRAN", + "URL": "https://cloud.r-project.org" + } + ] + }, + "Packages": { + "KernSmooth": { + "Package": "KernSmooth", + "Version": "2.23-24", + "Source": "Repository", + "Priority": "recommended", + "Date": "2024-05-16", + "Title": "Functions for Kernel Smoothing Supporting Wand & Jones (1995)", + "Authors@R": "c(person(\"Matt\", \"Wand\", role = \"aut\", email = \"Matt.Wand@uts.edu.au\"), person(\"Cleve\", \"Moler\", role = \"ctb\", comment = \"LINPACK routines in src/d*\"), person(\"Brian\", \"Ripley\", role = c(\"trl\", \"cre\", \"ctb\"), email = \"ripley@stats.ox.ac.uk\", comment = \"R port and updates\"))", + "Note": "Maintainers are not available to give advice on using a package they did not author.", + "Depends": [ + "R (>= 2.5.0)", + "stats" + ], + "Suggests": [ + "MASS", + "carData" + ], + "Description": "Functions for kernel smoothing (and density estimation) corresponding to the book: Wand, M.P. and Jones, M.C. 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Bates [ctb], Kurt Hornik [trl] (partial port ca 1998), Albrecht Gebhardt [trl] (partial port ca 1998), David Firth [ctb] (support functions for polr)", + "Maintainer": "Brian Ripley ", + "Repository": "CRAN" + }, + "Matrix": { + "Package": "Matrix", + "Version": "1.7-1", + "Source": "Repository", + "VersionNote": "do also bump src/version.h, inst/include/Matrix/version.h", + "Date": "2024-10-17", + "Priority": "recommended", + "Title": "Sparse and Dense Matrix Classes and Methods", + "Description": "A rich hierarchy of sparse and dense matrix classes, including general, symmetric, triangular, and diagonal matrices with numeric, logical, or pattern entries. 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Davis [ctb] (, SuiteSparse libraries, collaborators listed in dir(system.file(\"doc\", \"SuiteSparse\", package=\"Matrix\"), pattern=\"License\", full.names=TRUE, recursive=TRUE)), George Karypis [ctb] (, METIS library, Copyright: Regents of the University of Minnesota), Jason Riedy [ctb] (, GNU Octave's condest() and onenormest(), Copyright: Regents of the University of California), Jens OehlschlΓ€gel [ctb] (initial nearPD()), R Core Team [ctb] (base R's matrix implementation)", + "Maintainer": "Martin Maechler ", + "Repository": "CRAN" + }, + "R6": { + "Package": "R6", + "Version": "2.6.1", + "Source": "Repository", + "Title": "Encapsulated Classes with Reference Semantics", + "Authors@R": "c( person(\"Winston\", \"Chang\", , \"winston@posit.co\", role = c(\"aut\", \"cre\")), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\")) )", + "Description": "Creates classes with reference semantics, similar to R's built-in reference classes. Compared to reference classes, R6 classes are simpler and lighter-weight, and they are not built on S4 classes so they do not require the methods package. These classes allow public and private members, and they support inheritance, even when the classes are defined in different packages.", + "License": "MIT + file LICENSE", + "URL": "https://r6.r-lib.org, https://github.com/r-lib/R6", + "BugReports": "https://github.com/r-lib/R6/issues", + "Depends": [ + "R (>= 3.6)" + ], + "Suggests": [ + "lobstr", + "testthat (>= 3.0.0)" + ], + "Config/Needs/website": "tidyverse/tidytemplate, ggplot2, microbenchmark, scales", + "Config/testthat/edition": "3", + "Encoding": "UTF-8", + "RoxygenNote": "7.3.2", + "NeedsCompilation": "no", + "Author": "Winston Chang [aut, cre], Posit Software, PBC [cph, fnd]", + "Maintainer": "Winston Chang ", + "Repository": "CRAN" + }, + "Rcpp": { + "Package": "Rcpp", + "Version": "1.1.0", + "Source": "Repository", + "Title": "Seamless R and C++ Integration", + "Date": "2025-07-01", + "Authors@R": "c(person(\"Dirk\", \"Eddelbuettel\", role = c(\"aut\", \"cre\"), email = \"edd@debian.org\", comment = c(ORCID = \"0000-0001-6419-907X\")), person(\"Romain\", \"Francois\", role = \"aut\", comment = c(ORCID = \"0000-0002-2444-4226\")), person(\"JJ\", \"Allaire\", role = \"aut\", comment = c(ORCID = \"0000-0003-0174-9868\")), person(\"Kevin\", \"Ushey\", role = \"aut\", comment = c(ORCID = \"0000-0003-2880-7407\")), person(\"Qiang\", \"Kou\", role = \"aut\", comment = c(ORCID = \"0000-0001-6786-5453\")), person(\"Nathan\", \"Russell\", role = \"aut\"), person(\"IΓ±aki\", \"Ucar\", role = \"aut\", comment = c(ORCID = \"0000-0001-6403-5550\")), person(\"Doug\", \"Bates\", role = \"aut\", comment = c(ORCID = \"0000-0001-8316-9503\")), person(\"John\", \"Chambers\", role = \"aut\"))", + "Description": "The 'Rcpp' package provides R functions as well as C++ classes which offer a seamless integration of R and C++. Many R data types and objects can be mapped back and forth to C++ equivalents which facilitates both writing of new code as well as easier integration of third-party libraries. 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Many fast algorithmic operations such as 'match' and 'order' support inter- active data exploration and manipulation and optionally leverage caching.", + "License": "GPL-2 | GPL-3", + "LazyLoad": "yes", + "ByteCompile": "yes", + "URL": "https://github.com/r-lib/bit64", + "Encoding": "UTF-8", + "Imports": [ + "graphics", + "methods", + "stats", + "utils" + ], + "Suggests": [ + "testthat (>= 3.0.3)", + "withr" + ], + "Config/testthat/edition": "3", + "Config/needs/development": "testthat", + "RoxygenNote": "7.3.2", + "NeedsCompilation": "yes", + "Author": "Michael Chirico [aut, cre], Jens OehlschlΓ€gel [aut], Leonardo Silvestri [ctb], Ofek Shilon [ctb]", + "Maintainer": "Michael Chirico ", + "Repository": "CRAN" + }, + "boot": { + "Package": "boot", + "Version": "1.3-31", + "Source": "Repository", + "Priority": "recommended", + "Date": "2024-08-28", + "Authors@R": "c(person(\"Angelo\", \"Canty\", role = \"aut\", email = \"cantya@mcmaster.ca\", comment = \"author of original code for S\"), person(\"Brian\", \"Ripley\", role = c(\"aut\", \"trl\"), email = \"ripley@stats.ox.ac.uk\", comment = \"conversion to R, maintainer 1999--2022, author of parallel support\"), person(\"Alessandra R.\", \"Brazzale\", role = c(\"ctb\", \"cre\"), email = \"brazzale@stat.unipd.it\", comment = \"minor bug fixes\"))", + "Maintainer": "Alessandra R. Brazzale ", + "Note": "Maintainers are not available to give advice on using a package they did not author.", + "Description": "Functions and datasets for bootstrapping from the book \"Bootstrap Methods and Their Application\" by A. C. Davison and D. V. Hinkley (1997, CUP), originally written by Angelo Canty for S.", + "Title": "Bootstrap Functions (Originally by Angelo Canty for S)", + "Depends": [ + "R (>= 3.0.0)", + "graphics", + "stats" + ], + "Suggests": [ + "MASS", + "survival" + ], + "LazyData": "yes", + "ByteCompile": "yes", + "License": "Unlimited", + "NeedsCompilation": "no", + "Author": "Angelo Canty [aut] (author of original code for S), Brian Ripley [aut, trl] (conversion to R, maintainer 1999--2022, author of parallel support), Alessandra R. 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Supports 'Bootstrap' 3, 4 and 5 as well as their various 'Bootswatch' themes. An interactive widget is also provided for previewing themes in real time.", + "License": "MIT + file LICENSE", + "URL": "https://rstudio.github.io/bslib/, https://github.com/rstudio/bslib", + "BugReports": "https://github.com/rstudio/bslib/issues", + "Depends": [ + "R (>= 2.10)" + ], + "Imports": [ + "base64enc", + "cachem", + "fastmap (>= 1.1.1)", + "grDevices", + "htmltools (>= 0.5.8)", + "jquerylib (>= 0.1.3)", + "jsonlite", + "lifecycle", + "memoise (>= 2.0.1)", + "mime", + "rlang", + "sass (>= 0.4.9)" + ], + "Suggests": [ + "bsicons", + "curl", + "fontawesome", + "future", + "ggplot2", + "knitr", + "magrittr", + "rappdirs", + "rmarkdown (>= 2.7)", + "shiny (> 1.8.1)", + "testthat", + "thematic", + "tools", + "utils", + "withr", + "yaml" + ], + "Config/Needs/deploy": "BH, chiflights22, colourpicker, commonmark, cpp11, cpsievert/chiflights22, cpsievert/histoslider, dplyr, DT, ggplot2, ggridges, gt, hexbin, histoslider, htmlwidgets, lattice, leaflet, lubridate, markdown, modelr, plotly, reactable, reshape2, rprojroot, rsconnect, rstudio/shiny, scales, styler, tibble", + "Config/Needs/routine": "chromote, desc, renv", + "Config/Needs/website": "brio, crosstalk, dplyr, DT, ggplot2, glue, htmlwidgets, leaflet, lorem, palmerpenguins, plotly, purrr, rprojroot, rstudio/htmltools, scales, stringr, tidyr, webshot2", + "Config/testthat/edition": "3", + "Config/testthat/parallel": "true", + "Config/testthat/start-first": "zzzz-bs-sass, fonts, zzz-precompile, theme-*, rmd-*", + "Encoding": "UTF-8", + "RoxygenNote": "7.3.2", + "Collate": "'accordion.R' 'breakpoints.R' 'bs-current-theme.R' 'bs-dependencies.R' 'bs-global.R' 'bs-remove.R' 'bs-theme-layers.R' 'bs-theme-preset-bootswatch.R' 'bs-theme-preset-brand.R' 'bs-theme-preset-builtin.R' 'bs-theme-preset.R' 'utils.R' 'bs-theme-preview.R' 'bs-theme-update.R' 'bs-theme.R' 'bslib-package.R' 'buttons.R' 'card.R' 'deprecated.R' 'files.R' 'fill.R' 'imports.R' 'input-dark-mode.R' 'input-switch.R' 'layout.R' 'nav-items.R' 'nav-update.R' 'navbar_options.R' 'navs-legacy.R' 'navs.R' 'onLoad.R' 'page.R' 'popover.R' 'precompiled.R' 'print.R' 'shiny-devmode.R' 'sidebar.R' 'staticimports.R' 'tooltip.R' 'utils-deps.R' 'utils-shiny.R' 'utils-tags.R' 'value-box.R' 'version-default.R' 'versions.R'", + "NeedsCompilation": "no", + "Author": "Carson Sievert [aut, cre] (), Joe Cheng [aut], Garrick Aden-Buie [aut] (), Posit Software, PBC [cph, fnd], Bootstrap contributors [ctb] (Bootstrap library), Twitter, Inc [cph] (Bootstrap library), Javi Aguilar [ctb, cph] (Bootstrap colorpicker library), Thomas Park [ctb, cph] (Bootswatch library), PayPal [ctb, cph] (Bootstrap accessibility plugin)", + "Maintainer": "Carson Sievert ", + "Repository": "CRAN" + }, + "cachem": { + "Package": "cachem", + "Version": "1.1.0", + "Source": "Repository", + "Title": "Cache R Objects with Automatic Pruning", + "Description": "Key-value stores with automatic pruning. Caches can limit either their total size or the age of the oldest object (or both), automatically pruning objects to maintain the constraints.", + "Authors@R": "c( person(\"Winston\", \"Chang\", , \"winston@posit.co\", c(\"aut\", \"cre\")), person(family = \"Posit Software, PBC\", role = c(\"cph\", \"fnd\")))", + "License": "MIT + file LICENSE", + "Encoding": "UTF-8", + "ByteCompile": "true", + "URL": "https://cachem.r-lib.org/, https://github.com/r-lib/cachem", + "Imports": [ + "rlang", + "fastmap (>= 1.2.0)" + ], + "Suggests": [ + "testthat" + ], + "RoxygenNote": "7.2.3", + "Config/Needs/routine": "lobstr", + "Config/Needs/website": "pkgdown", + "NeedsCompilation": "yes", + "Author": "Winston Chang [aut, cre], Posit Software, PBC [cph, fnd]", + "Maintainer": "Winston Chang ", + "Repository": "CRAN" + }, + "callr": { + "Package": "callr", + "Version": "3.7.6", + "Source": "Repository", + "Title": "Call R from R", + "Authors@R": "c( person(\"GΓ‘bor\", \"CsΓ‘rdi\", , \"csardi.gabor@gmail.com\", role = c(\"aut\", \"cre\", \"cph\"), comment = c(ORCID = \"0000-0001-7098-9676\")), person(\"Winston\", \"Chang\", role = \"aut\"), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\")), person(\"Ascent Digital Services\", role = c(\"cph\", \"fnd\")) )", + "Description": "It is sometimes useful to perform a computation in a separate R process, without affecting the current R process at all. This packages does exactly that.", + "License": "MIT + file LICENSE", + "URL": "https://callr.r-lib.org, https://github.com/r-lib/callr", + "BugReports": "https://github.com/r-lib/callr/issues", + "Depends": [ + "R (>= 3.4)" + ], + "Imports": [ + "processx (>= 3.6.1)", + "R6", + "utils" + ], + "Suggests": [ + "asciicast (>= 2.3.1)", + "cli (>= 1.1.0)", + "mockery", + "ps", + "rprojroot", + "spelling", + "testthat (>= 3.2.0)", + "withr (>= 2.3.0)" + ], + "Config/Needs/website": "r-lib/asciicast, glue, htmlwidgets, igraph, tibble, tidyverse/tidytemplate", + "Config/testthat/edition": "3", + "Encoding": "UTF-8", + "Language": "en-US", + "RoxygenNote": "7.3.1.9000", + "NeedsCompilation": "no", + "Author": "GΓ‘bor CsΓ‘rdi [aut, cre, cph] (), Winston Chang [aut], Posit Software, PBC [cph, fnd], Ascent Digital Services [cph, fnd]", + "Maintainer": "GΓ‘bor CsΓ‘rdi ", + "Repository": "CRAN" + }, + "class": { + "Package": "class", + "Version": "7.3-22", + "Source": "Repository", + "Priority": "recommended", + "Date": "2023-05-02", + "Depends": [ + "R (>= 3.0.0)", + "stats", + "utils" + ], + "Imports": [ + "MASS" + ], + "Authors@R": "c(person(\"Brian\", \"Ripley\", role = c(\"aut\", \"cre\", \"cph\"), email = \"ripley@stats.ox.ac.uk\"), person(\"William\", \"Venables\", role = \"cph\"))", + "Description": "Various functions for classification, including k-nearest neighbour, Learning Vector Quantization and Self-Organizing Maps.", + "Title": "Functions for Classification", + "ByteCompile": "yes", + "License": "GPL-2 | GPL-3", + "URL": "http://www.stats.ox.ac.uk/pub/MASS4/", + "NeedsCompilation": "yes", + "Author": "Brian Ripley [aut, cre, cph], William Venables [cph]", + "Maintainer": "Brian Ripley ", + "Repository": "CRAN" + }, + "cli": { + "Package": "cli", + "Version": "3.6.5", + "Source": "Repository", + "Title": "Helpers for Developing Command Line Interfaces", + "Authors@R": "c( person(\"GΓ‘bor\", \"CsΓ‘rdi\", , \"gabor@posit.co\", role = c(\"aut\", \"cre\")), person(\"Hadley\", \"Wickham\", role = \"ctb\"), person(\"Kirill\", \"MΓΌller\", role = \"ctb\"), person(\"Salim\", \"BrΓΌggemann\", , \"salim-b@pm.me\", role = \"ctb\", comment = c(ORCID = \"0000-0002-5329-5987\")), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\")) )", + "Description": "A suite of tools to build attractive command line interfaces ('CLIs'), from semantic elements: headings, lists, alerts, paragraphs, etc. Supports custom themes via a 'CSS'-like language. It also contains a number of lower level 'CLI' elements: rules, boxes, trees, and 'Unicode' symbols with 'ASCII' alternatives. It support ANSI colors and text styles as well.", + "License": "MIT + file LICENSE", + "URL": "https://cli.r-lib.org, https://github.com/r-lib/cli", + "BugReports": "https://github.com/r-lib/cli/issues", + "Depends": [ + "R (>= 3.4)" + ], + "Imports": [ + "utils" + ], + "Suggests": [ + "callr", + "covr", + "crayon", + "digest", + "glue (>= 1.6.0)", + "grDevices", + "htmltools", + "htmlwidgets", + "knitr", + "methods", + "processx", + "ps (>= 1.3.4.9000)", + "rlang (>= 1.0.2.9003)", + "rmarkdown", + "rprojroot", + "rstudioapi", + "testthat (>= 3.2.0)", + "tibble", + "whoami", + "withr" + ], + "Config/Needs/website": "r-lib/asciicast, bench, brio, cpp11, decor, desc, fansi, prettyunits, sessioninfo, tidyverse/tidytemplate, usethis, vctrs", + "Config/testthat/edition": "3", + "Encoding": "UTF-8", + "RoxygenNote": "7.3.2", + "NeedsCompilation": "yes", + "Author": "GΓ‘bor CsΓ‘rdi [aut, cre], Hadley Wickham [ctb], Kirill MΓΌller [ctb], Salim BrΓΌggemann [ctb] (), Posit Software, PBC [cph, fnd]", + "Maintainer": "GΓ‘bor CsΓ‘rdi ", + "Repository": "CRAN" + }, + "clipr": { + "Package": "clipr", + "Version": "0.8.0", + "Source": "Repository", + "Type": "Package", + "Title": "Read and Write from the System Clipboard", + "Authors@R": "c( person(\"Matthew\", \"Lincoln\", , \"matthew.d.lincoln@gmail.com\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0002-4387-3384\")), person(\"Louis\", \"Maddox\", role = \"ctb\"), person(\"Steve\", \"Simpson\", role = \"ctb\"), person(\"Jennifer\", \"Bryan\", role = \"ctb\") )", + "Description": "Simple utility functions to read from and write to the Windows, OS X, and X11 clipboards.", + "License": "GPL-3", + "URL": "https://github.com/mdlincoln/clipr, http://matthewlincoln.net/clipr/", + "BugReports": "https://github.com/mdlincoln/clipr/issues", + "Imports": [ + "utils" + ], + "Suggests": [ + "covr", + "knitr", + "rmarkdown", + "rstudioapi (>= 0.5)", + "testthat (>= 2.0.0)" + ], + "VignetteBuilder": "knitr", + "Encoding": "UTF-8", + "Language": "en-US", + "RoxygenNote": "7.1.2", + "SystemRequirements": "xclip (https://github.com/astrand/xclip) or xsel (http://www.vergenet.net/~conrad/software/xsel/) for accessing the X11 clipboard, or wl-clipboard (https://github.com/bugaevc/wl-clipboard) for systems using Wayland.", + "NeedsCompilation": "no", + "Author": "Matthew Lincoln [aut, cre] (), Louis Maddox [ctb], Steve Simpson [ctb], Jennifer Bryan [ctb]", + "Maintainer": "Matthew Lincoln ", + "Repository": "CRAN" + }, + "cluster": { + "Package": "cluster", + "Version": "2.1.6", + "Source": "Repository", + "Date": "2023-11-30", + "Priority": "recommended", + "Title": "\"Finding Groups in Data\": Cluster Analysis Extended Rousseeuw et al.", + "Description": "Methods for Cluster analysis. Much extended the original from Peter Rousseeuw, Anja Struyf and Mia Hubert, based on Kaufman and Rousseeuw (1990) \"Finding Groups in Data\".", + "Maintainer": "Martin Maechler ", + "Authors@R": "c(person(\"Martin\",\"Maechler\", role = c(\"aut\",\"cre\"), email=\"maechler@stat.math.ethz.ch\", comment = c(ORCID = \"0000-0002-8685-9910\")) ,person(\"Peter\", \"Rousseeuw\", role=\"aut\", email=\"peter.rousseeuw@kuleuven.be\", comment = c(\"Fortran original\", ORCID = \"0000-0002-3807-5353\")) ,person(\"Anja\", \"Struyf\", role=\"aut\", comment= \"S original\") ,person(\"Mia\", \"Hubert\", role=\"aut\", email= \"Mia.Hubert@uia.ua.ac.be\", comment = c(\"S original\", ORCID = \"0000-0001-6398-4850\")) ,person(\"Kurt\", \"Hornik\", role=c(\"trl\", \"ctb\"), email=\"Kurt.Hornik@R-project.org\", comment=c(\"port to R; maintenance(1999-2000)\", ORCID=\"0000-0003-4198-9911\")) ,person(\"Matthias\", \"Studer\", role=\"ctb\") ,person(\"Pierre\", \"Roudier\", role=\"ctb\") ,person(\"Juan\", \"Gonzalez\", role=\"ctb\") ,person(\"Kamil\", \"Kozlowski\", role=\"ctb\") ,person(\"Erich\", \"Schubert\", role=\"ctb\", comment = c(\"fastpam options for pam()\", ORCID = \"0000-0001-9143-4880\")) ,person(\"Keefe\", \"Murphy\", role=\"ctb\", comment = \"volume.ellipsoid({d >= 3})\") #not yet ,person(\"Fischer-Rasmussen\", \"Kasper\", role = \"ctb\", comment = \"Gower distance for CLARA\") )", + "Depends": [ + "R (>= 3.5.0)" + ], + "Imports": [ + "graphics", + "grDevices", + "stats", + "utils" + ], + "Suggests": [ + "MASS", + "Matrix" + ], + "SuggestsNote": "MASS: two examples using cov.rob() and mvrnorm(); Matrix tools for testing", + "Enhances": [ + "mvoutlier", + "fpc", + "ellipse", + "sfsmisc" + ], + "EnhancesNote": "xref-ed in man/*.Rd", + "LazyLoad": "yes", + "LazyData": "yes", + "ByteCompile": "yes", + "BuildResaveData": "no", + "License": "GPL (>= 2)", + "URL": "https://svn.r-project.org/R-packages/trunk/cluster/", + "NeedsCompilation": "yes", + "Author": "Martin Maechler [aut, cre] (), Peter Rousseeuw [aut] (Fortran original, ), Anja Struyf [aut] (S original), Mia Hubert [aut] (S original, ), Kurt Hornik [trl, ctb] (port to R; maintenance(1999-2000), ), Matthias Studer [ctb], Pierre Roudier [ctb], Juan Gonzalez [ctb], Kamil Kozlowski [ctb], Erich Schubert [ctb] (fastpam options for pam(), ), Keefe Murphy [ctb] (volume.ellipsoid({d >= 3}))", + "Repository": "CRAN" + }, + "codetools": { + "Package": "codetools", + "Version": "0.2-20", + "Source": "Repository", + "Priority": "recommended", + "Author": "Luke Tierney ", + "Description": "Code analysis tools for R.", + "Title": "Code Analysis Tools for R", + "Depends": [ + "R (>= 2.1)" + ], + "Maintainer": "Luke Tierney ", + "URL": "https://gitlab.com/luke-tierney/codetools", + "License": "GPL", + "NeedsCompilation": "no", + "Repository": "CRAN" + }, + "commonmark": { + "Package": "commonmark", + "Version": "2.0.0", + "Source": "Repository", + "Type": "Package", + "Title": "High Performance CommonMark and Github Markdown Rendering in R", + "Authors@R": "c( person(\"Jeroen\", \"Ooms\", ,\"jeroenooms@gmail.com\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0002-4035-0289\")), person(\"John MacFarlane\", role = \"cph\", comment = \"Author of cmark\"))", + "Description": "The CommonMark specification defines a rationalized version of markdown syntax. This package uses the 'cmark' reference implementation for converting markdown text into various formats including html, latex and groff man. In addition it exposes the markdown parse tree in xml format. Also includes opt-in support for GFM extensions including tables, autolinks, and strikethrough text.", + "License": "BSD_2_clause + file LICENSE", + "URL": "https://docs.ropensci.org/commonmark/ https://ropensci.r-universe.dev/commonmark", + "BugReports": "https://github.com/r-lib/commonmark/issues", + "Suggests": [ + "curl", + "testthat", + "xml2" + ], + "RoxygenNote": "7.3.2", + "Language": "en-US", + "Encoding": "UTF-8", + "NeedsCompilation": "yes", + "Author": "Jeroen Ooms [aut, cre] (ORCID: ), John MacFarlane [cph] (Author of cmark)", + "Maintainer": "Jeroen Ooms ", + "Repository": "CRAN" + }, + "cpp11": { + "Package": "cpp11", + "Version": "0.5.2", + "Source": "Repository", + "Title": "A C++11 Interface for R's C Interface", + "Authors@R": "c( person(\"Davis\", \"Vaughan\", email = \"davis@posit.co\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0003-4777-038X\")), person(\"Jim\",\"Hester\", role = \"aut\", comment = c(ORCID = \"0000-0002-2739-7082\")), person(\"Romain\", \"FranΓ§ois\", role = \"aut\", comment = c(ORCID = \"0000-0002-2444-4226\")), person(\"Benjamin\", \"Kietzman\", role = \"ctb\"), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\")) )", + "Description": "Provides a header only, C++11 interface to R's C interface. Compared to other approaches 'cpp11' strives to be safe against long jumps from the C API as well as C++ exceptions, conform to normal R function semantics and supports interaction with 'ALTREP' vectors.", + "License": "MIT + file LICENSE", + "URL": "https://cpp11.r-lib.org, https://github.com/r-lib/cpp11", + "BugReports": "https://github.com/r-lib/cpp11/issues", + "Depends": [ + "R (>= 4.0.0)" + ], + "Suggests": [ + "bench", + "brio", + "callr", + "cli", + "covr", + "decor", + "desc", + "ggplot2", + "glue", + "knitr", + "lobstr", + "mockery", + "progress", + "rmarkdown", + "scales", + "Rcpp", + "testthat (>= 3.2.0)", + "tibble", + "utils", + "vctrs", + "withr" + ], + "VignetteBuilder": "knitr", + "Config/Needs/website": "tidyverse/tidytemplate", + "Config/testthat/edition": "3", + "Config/Needs/cpp11/cpp_register": "brio, cli, decor, desc, glue, tibble, vctrs", + "Encoding": "UTF-8", + "RoxygenNote": "7.3.2", + "NeedsCompilation": "no", + "Author": "Davis Vaughan [aut, cre] (), Jim Hester [aut] (), Romain FranΓ§ois [aut] (), Benjamin Kietzman [ctb], Posit Software, PBC [cph, fnd]", + "Maintainer": "Davis Vaughan ", + "Repository": "CRAN" + }, + "crayon": { + "Package": "crayon", + "Version": "1.5.3", + "Source": "Repository", + "Title": "Colored Terminal Output", + "Authors@R": "c( person(\"GΓ‘bor\", \"CsΓ‘rdi\", , \"csardi.gabor@gmail.com\", role = c(\"aut\", \"cre\")), person(\"Brodie\", \"Gaslam\", , \"brodie.gaslam@yahoo.com\", role = \"ctb\"), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\")) )", + "Description": "The crayon package is now superseded. Please use the 'cli' package for new projects. Colored terminal output on terminals that support 'ANSI' color and highlight codes. It also works in 'Emacs' 'ESS'. 'ANSI' color support is automatically detected. Colors and highlighting can be combined and nested. New styles can also be created easily. This package was inspired by the 'chalk' 'JavaScript' project.", + "License": "MIT + file LICENSE", + "URL": "https://r-lib.github.io/crayon/, https://github.com/r-lib/crayon", + "BugReports": "https://github.com/r-lib/crayon/issues", + "Imports": [ + "grDevices", + "methods", + "utils" + ], + "Suggests": [ + "mockery", + "rstudioapi", + "testthat", + "withr" + ], + "Config/Needs/website": "tidyverse/tidytemplate", + "Encoding": "UTF-8", + "RoxygenNote": "7.3.1", + "Collate": "'aaa-rstudio-detect.R' 'aaaa-rematch2.R' 'aab-num-ansi-colors.R' 'aac-num-ansi-colors.R' 'ansi-256.R' 'ansi-palette.R' 'combine.R' 'string.R' 'utils.R' 'crayon-package.R' 'disposable.R' 'enc-utils.R' 'has_ansi.R' 'has_color.R' 'link.R' 'styles.R' 'machinery.R' 'parts.R' 'print.R' 'style-var.R' 'show.R' 'string_operations.R'", + "NeedsCompilation": "no", + "Author": "GΓ‘bor CsΓ‘rdi [aut, cre], Brodie Gaslam [ctb], Posit Software, PBC [cph, fnd]", + "Maintainer": "GΓ‘bor CsΓ‘rdi ", + "Repository": "CRAN" + }, + "credentials": { + "Package": "credentials", + "Version": "2.0.3", + "Source": "Repository", + "Type": "Package", + "Title": "Tools for Managing SSH and Git Credentials", + "Authors@R": "person(\"Jeroen\", \"Ooms\", role = c(\"aut\", \"cre\"), email = \"jeroenooms@gmail.com\", comment = c(ORCID = \"0000-0002-4035-0289\"))", + "Description": "Setup and retrieve HTTPS and SSH credentials for use with 'git' and other services. For HTTPS remotes the package interfaces the 'git-credential' utility which 'git' uses to store HTTP usernames and passwords. For SSH remotes we provide convenient functions to find or generate appropriate SSH keys. The package both helps the user to setup a local git installation, and also provides a back-end for git/ssh client libraries to authenticate with existing user credentials.", + "License": "MIT + file LICENSE", + "SystemRequirements": "git (optional)", + "Encoding": "UTF-8", + "Imports": [ + "openssl (>= 1.3)", + "sys (>= 2.1)", + "curl", + "jsonlite", + "askpass" + ], + "Suggests": [ + "testthat", + "knitr", + "rmarkdown" + ], + "RoxygenNote": "7.2.1", + "VignetteBuilder": "knitr", + "Language": "en-US", + "URL": "https://docs.ropensci.org/credentials/ https://r-lib.r-universe.dev/credentials", + "BugReports": "https://github.com/r-lib/credentials/issues", + "NeedsCompilation": "no", + "Author": "Jeroen Ooms [aut, cre] (ORCID: )", + "Maintainer": "Jeroen Ooms ", + "Repository": "CRAN" + }, + "curl": { + "Package": "curl", + "Version": "7.0.0", + "Source": "Repository", + "Type": "Package", + "Title": "A Modern and Flexible Web Client for R", + "Authors@R": "c( person(\"Jeroen\", \"Ooms\", role = c(\"aut\", \"cre\"), email = \"jeroenooms@gmail.com\", comment = c(ORCID = \"0000-0002-4035-0289\")), person(\"Hadley\", \"Wickham\", role = \"ctb\"), person(\"Posit Software, PBC\", role = \"cph\"))", + "Description": "Bindings to 'libcurl' for performing fully configurable HTTP/FTP requests where responses can be processed in memory, on disk, or streaming via the callback or connection interfaces. Some knowledge of 'libcurl' is recommended; for a more-user-friendly web client see the 'httr2' package which builds on this package with http specific tools and logic.", + "License": "MIT + file LICENSE", + "SystemRequirements": "libcurl (>= 7.73): libcurl-devel (rpm) or libcurl4-openssl-dev (deb)", + "URL": "https://jeroen.r-universe.dev/curl", + "BugReports": "https://github.com/jeroen/curl/issues", + "Suggests": [ + "spelling", + "testthat (>= 1.0.0)", + "knitr", + "jsonlite", + "later", + "rmarkdown", + "httpuv (>= 1.4.4)", + "webutils" + ], + "VignetteBuilder": "knitr", + "Depends": [ + "R (>= 3.0.0)" + ], + "RoxygenNote": "7.3.2", + "Encoding": "UTF-8", + "Language": "en-US", + "NeedsCompilation": "yes", + "Author": "Jeroen Ooms [aut, cre] (ORCID: ), Hadley Wickham [ctb], Posit Software, PBC [cph]", + "Maintainer": "Jeroen Ooms ", + "Repository": "CRAN" + }, + "desc": { + "Package": "desc", + "Version": "1.4.3", + "Source": "Repository", + "Title": "Manipulate DESCRIPTION Files", + "Authors@R": "c( person(\"GΓ‘bor\", \"CsΓ‘rdi\", , \"csardi.gabor@gmail.com\", role = c(\"aut\", \"cre\")), person(\"Kirill\", \"MΓΌller\", role = \"aut\"), person(\"Jim\", \"Hester\", , \"james.f.hester@gmail.com\", role = \"aut\"), person(\"MaΓ«lle\", \"Salmon\", role = \"ctb\", comment = c(ORCID = \"0000-0002-2815-0399\")), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\")) )", + "Maintainer": "GΓ‘bor CsΓ‘rdi ", + "Description": "Tools to read, write, create, and manipulate DESCRIPTION files. 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Allen [ctb, cph] (Original C implementation of Myers Diff Algorithm)", + "Maintainer": "Brodie Gaslam ", + "Repository": "CRAN" + }, + "digest": { + "Package": "digest", + "Version": "0.6.37", + "Source": "Repository", + "Authors@R": "c(person(\"Dirk\", \"Eddelbuettel\", role = c(\"aut\", \"cre\"), email = \"edd@debian.org\", comment = c(ORCID = \"0000-0001-6419-907X\")), person(\"Antoine\", \"Lucas\", role=\"ctb\"), person(\"Jarek\", \"Tuszynski\", role=\"ctb\"), person(\"Henrik\", \"Bengtsson\", role=\"ctb\", comment = c(ORCID = \"0000-0002-7579-5165\")), person(\"Simon\", \"Urbanek\", role=\"ctb\", comment = c(ORCID = \"0000-0003-2297-1732\")), person(\"Mario\", \"Frasca\", role=\"ctb\"), person(\"Bryan\", \"Lewis\", role=\"ctb\"), person(\"Murray\", \"Stokely\", role=\"ctb\"), person(\"Hannes\", \"Muehleisen\", role=\"ctb\"), person(\"Duncan\", \"Murdoch\", role=\"ctb\"), person(\"Jim\", \"Hester\", role=\"ctb\"), person(\"Wush\", \"Wu\", role=\"ctb\", comment = c(ORCID = \"0000-0001-5180-0567\")), person(\"Qiang\", \"Kou\", role=\"ctb\", comment = c(ORCID = \"0000-0001-6786-5453\")), person(\"Thierry\", \"Onkelinx\", role=\"ctb\", comment = c(ORCID = \"0000-0001-8804-4216\")), person(\"Michel\", \"Lang\", role=\"ctb\", comment = c(ORCID = \"0000-0001-9754-0393\")), person(\"Viliam\", \"Simko\", role=\"ctb\"), person(\"Kurt\", \"Hornik\", role=\"ctb\", comment = c(ORCID = \"0000-0003-4198-9911\")), person(\"Radford\", \"Neal\", role=\"ctb\", comment = c(ORCID = \"0000-0002-2473-3407\")), person(\"Kendon\", \"Bell\", role=\"ctb\", comment = c(ORCID = \"0000-0002-9093-8312\")), person(\"Matthew\", \"de Queljoe\", role=\"ctb\"), person(\"Dmitry\", \"Selivanov\", role=\"ctb\"), person(\"Ion\", \"Suruceanu\", role=\"ctb\"), person(\"Bill\", \"Denney\", role=\"ctb\"), person(\"Dirk\", \"Schumacher\", role=\"ctb\"), person(\"AndrΓ‘s\", \"Svraka\", role=\"ctb\"), person(\"Sergey\", \"Fedorov\", role=\"ctb\"), person(\"Will\", \"Landau\", role=\"ctb\", comment = c(ORCID = \"0000-0003-1878-3253\")), person(\"Floris\", \"Vanderhaeghe\", role=\"ctb\", comment = c(ORCID = \"0000-0002-6378-6229\")), person(\"Kevin\", \"Tappe\", role=\"ctb\"), person(\"Harris\", \"McGehee\", role=\"ctb\"), person(\"Tim\", \"Mastny\", role=\"ctb\"), person(\"Aaron\", \"Peikert\", role=\"ctb\", comment = c(ORCID = \"0000-0001-7813-818X\")), person(\"Mark\", \"van der Loo\", role=\"ctb\", comment = c(ORCID = \"0000-0002-9807-4686\")), person(\"Chris\", \"Muir\", role=\"ctb\", comment = c(ORCID = \"0000-0003-2555-3878\")), person(\"Moritz\", \"Beller\", role=\"ctb\", comment = c(ORCID = \"0000-0003-4852-0526\")), person(\"Sebastian\", \"Campbell\", role=\"ctb\"), person(\"Winston\", \"Chang\", role=\"ctb\", comment = c(ORCID = \"0000-0002-1576-2126\")), person(\"Dean\", \"Attali\", role=\"ctb\", comment = c(ORCID = \"0000-0002-5645-3493\")), person(\"Michael\", \"Chirico\", role=\"ctb\", comment = c(ORCID = \"0000-0003-0787-087X\")), person(\"Kevin\", \"Ushey\", role=\"ctb\"))", + "Date": "2024-08-19", + "Title": "Create Compact Hash Digests of R Objects", + "Description": "Implementation of a function 'digest()' for the creation of hash digests of arbitrary R objects (using the 'md5', 'sha-1', 'sha-256', 'crc32', 'xxhash', 'murmurhash', 'spookyhash', 'blake3', 'crc32c', 'xxh3_64', and 'xxh3_128' algorithms) permitting easy comparison of R language objects, as well as functions such as'hmac()' to create hash-based message authentication code. Please note that this package is not meant to be deployed for cryptographic purposes for which more comprehensive (and widely tested) libraries such as 'OpenSSL' should be used.", + "URL": "https://github.com/eddelbuettel/digest, https://dirk.eddelbuettel.com/code/digest.html", + "BugReports": "https://github.com/eddelbuettel/digest/issues", + "Depends": [ + "R (>= 3.3.0)" + ], + "Imports": [ + "utils" + ], + "License": "GPL (>= 2)", + "Suggests": [ + "tinytest", + "simplermarkdown" + ], + "VignetteBuilder": "simplermarkdown", + "Encoding": "UTF-8", + "NeedsCompilation": "yes", + "Author": "Dirk Eddelbuettel [aut, cre] (), Antoine Lucas [ctb], Jarek Tuszynski [ctb], Henrik Bengtsson [ctb] (), Simon Urbanek [ctb] (), Mario Frasca [ctb], Bryan Lewis [ctb], Murray Stokely [ctb], Hannes Muehleisen [ctb], Duncan Murdoch [ctb], Jim Hester [ctb], Wush Wu [ctb] (), Qiang Kou [ctb] (), Thierry Onkelinx [ctb] (), Michel Lang [ctb] (), Viliam Simko [ctb], Kurt Hornik [ctb] (), Radford Neal [ctb] (), Kendon Bell [ctb] (), Matthew de Queljoe [ctb], Dmitry Selivanov [ctb], Ion Suruceanu [ctb], Bill Denney [ctb], Dirk Schumacher [ctb], AndrΓ‘s Svraka [ctb], Sergey Fedorov [ctb], Will Landau [ctb] (), Floris Vanderhaeghe [ctb] (), Kevin Tappe [ctb], Harris McGehee [ctb], Tim Mastny [ctb], Aaron Peikert [ctb] (), Mark van der Loo [ctb] (), Chris Muir [ctb] (), Moritz Beller [ctb] (), Sebastian Campbell [ctb], Winston Chang [ctb] (), Dean Attali [ctb] (), Michael Chirico [ctb] (), Kevin Ushey [ctb]", + "Maintainer": "Dirk Eddelbuettel ", + "Repository": "CRAN" + }, + "downlit": { + "Package": "downlit", + "Version": "0.4.4", + "Source": "Repository", + "Title": "Syntax Highlighting and Automatic Linking", + "Authors@R": "c( person(\"Hadley\", \"Wickham\", , \"hadley@posit.co\", role = c(\"aut\", \"cre\")), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\")) )", + "Description": "Syntax highlighting of R code, specifically designed for the needs of 'RMarkdown' packages like 'pkgdown', 'hugodown', and 'bookdown'. 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Kamvar [ctb] (), Posit Software, PBC [cph, fnd]", + "Maintainer": "Yihui Xie ", + "Repository": "CRAN" + }, + "later": { + "Package": "later", + "Version": "1.4.4", + "Source": "Repository", + "Type": "Package", + "Title": "Utilities for Scheduling Functions to Execute Later with Event Loops", + "Authors@R": "c( person(\"Winston\", \"Chang\", , \"winston@posit.co\", role = \"aut\"), person(\"Joe\", \"Cheng\", , \"joe@posit.co\", role = \"aut\"), person(\"Charlie\", \"Gao\", , \"charlie.gao@posit.co\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0002-0750-061X\")), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\"), comment = c(ROR = \"03wc8by49\")), person(\"Marcus\", \"Geelnard\", role = c(\"ctb\", \"cph\"), comment = \"TinyCThread library, https://tinycthread.github.io/\"), person(\"Evan\", \"Nemerson\", role = c(\"ctb\", \"cph\"), comment = \"TinyCThread library, https://tinycthread.github.io/\") )", + "Description": "Executes arbitrary R or C functions some time after the current time, after the R execution stack has emptied. 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This operator will forward a value, or the result of an expression, into the next function call/expression. There is flexible support for the type of right-hand side expressions. For more information, see package vignette. To quote Rene Magritte, \"Ceci n'est pas un pipe.\"", + "License": "MIT + file LICENSE", + "URL": "https://magrittr.tidyverse.org, https://github.com/tidyverse/magrittr", + "BugReports": "https://github.com/tidyverse/magrittr/issues", + "Depends": [ + "R (>= 3.4.0)" + ], + "Suggests": [ + "covr", + "knitr", + "rlang", + "rmarkdown", + "testthat" + ], + "VignetteBuilder": "knitr", + "ByteCompile": "Yes", + "Config/Needs/website": "tidyverse/tidytemplate", + "Encoding": "UTF-8", + "RoxygenNote": "7.3.3", + "NeedsCompilation": "yes", + "Author": "Stefan Milton Bache [aut, cph] (Original author and creator of magrittr), Hadley Wickham [aut], Lionel Henry [cre], Posit Software, PBC [cph, fnd] (ROR: )", + "Maintainer": "Lionel Henry ", + "Repository": "CRAN" + }, + "memoise": { + "Package": "memoise", + "Version": "2.0.1", + "Source": "Repository", + "Title": "'Memoisation' of Functions", + "Authors@R": "c(person(given = \"Hadley\", family = \"Wickham\", role = \"aut\", email = \"hadley@rstudio.com\"), person(given = \"Jim\", family = \"Hester\", role = \"aut\"), person(given = \"Winston\", family = \"Chang\", role = c(\"aut\", \"cre\"), email = \"winston@rstudio.com\"), person(given = \"Kirill\", family = \"MΓΌller\", role = \"aut\", email = \"krlmlr+r@mailbox.org\"), person(given = \"Daniel\", family = \"Cook\", role = \"aut\", email = \"danielecook@gmail.com\"), person(given = \"Mark\", family = \"Edmondson\", role = \"ctb\", email = \"r@sunholo.com\"))", + "Description": "Cache the results of a function so that when you call it again with the same arguments it returns the previously computed value.", + "License": "MIT + file LICENSE", + "URL": "https://memoise.r-lib.org, https://github.com/r-lib/memoise", + "BugReports": "https://github.com/r-lib/memoise/issues", + "Imports": [ + "rlang (>= 0.4.10)", + "cachem" + ], + "Suggests": [ + "digest", + "aws.s3", + "covr", + "googleAuthR", + "googleCloudStorageR", + "httr", + "testthat" + ], + "Encoding": "UTF-8", + "RoxygenNote": "7.1.2", + "NeedsCompilation": "no", + "Author": "Hadley Wickham [aut], Jim Hester [aut], Winston Chang [aut, cre], Kirill MΓΌller [aut], Daniel Cook [aut], Mark Edmondson [ctb]", + "Maintainer": "Winston Chang ", + "Repository": "CRAN" + }, + "mgcv": { + "Package": "mgcv", + "Version": "1.9-1", + "Source": "Repository", + "Author": "Simon Wood ", + "Maintainer": "Simon Wood ", + "Title": "Mixed GAM Computation Vehicle with Automatic Smoothness Estimation", + "Description": "Generalized additive (mixed) models, some of their extensions and other generalized ridge regression with multiple smoothing parameter estimation by (Restricted) Marginal Likelihood, Generalized Cross Validation and similar, or using iterated nested Laplace approximation for fully Bayesian inference. 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Warnes [ctb], Michael Quinn [ctb], Zhian N. Kamvar [ctb], Charlie Gao [ctb]", + "Maintainer": "Shawn Garbett ", + "License": "BSD_3_clause + file LICENSE", + "Description": "Implements the 'libyaml' 'YAML' 1.1 parser and emitter () for R.", + "URL": "https://github.com/vubiostat/r-yaml/", + "BugReports": "https://github.com/vubiostat/r-yaml/issues", + "NeedsCompilation": "yes", + "Repository": "CRAN" + }, + "zip": { + "Package": "zip", + "Version": "2.3.3", + "Source": "Repository", + "Title": "Cross-Platform 'zip' Compression", + "Authors@R": "c( person(\"GΓ‘bor\", \"CsΓ‘rdi\", , \"csardi.gabor@gmail.com\", role = c(\"aut\", \"cre\")), person(\"Kuba\", \"PodgΓ³rski\", role = \"ctb\"), person(\"Rich\", \"Geldreich\", role = \"ctb\"), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\"), comment = c(ROR = \"03wc8by49\")) )", + "Description": "Cross-Platform 'zip' Compression Library. A replacement for the 'zip' function, that does not require any additional external tools on any platform.", + "License": "MIT + file LICENSE", + "URL": "https://github.com/r-lib/zip, https://r-lib.github.io/zip/", + "BugReports": "https://github.com/r-lib/zip/issues", + "Suggests": [ + "covr", + "pillar", + "processx", + "R6", + "testthat", + "withr" + ], + "Config/Needs/website": "tidyverse/tidytemplate", + "Config/testthat/edition": "3", + "Config/usethis/last-upkeep": "2025-05-07", + "Encoding": "UTF-8", + "RoxygenNote": "7.3.2.9000", + "NeedsCompilation": "yes", + "Author": "GΓ‘bor CsΓ‘rdi [aut, cre], Kuba PodgΓ³rski [ctb], Rich Geldreich [ctb], Posit Software, PBC [cph, fnd] (ROR: )", + "Maintainer": "GΓ‘bor CsΓ‘rdi ", + "Repository": "CRAN" + } + } +} diff --git a/renv/.gitignore b/renv/.gitignore new file mode 100644 index 0000000..0ec0cbb --- /dev/null +++ b/renv/.gitignore @@ -0,0 +1,7 @@ +library/ +local/ +cellar/ +lock/ +python/ +sandbox/ +staging/ diff --git a/renv/activate.R b/renv/activate.R new file mode 100644 index 0000000..2753ae5 --- /dev/null +++ b/renv/activate.R @@ -0,0 +1,1334 @@ + +local({ + + # the requested version of renv + version <- "1.1.5" + attr(version, "sha") <- NULL + + # the project directory + project <- Sys.getenv("RENV_PROJECT") + if (!nzchar(project)) + project <- getwd() + + # use start-up diagnostics if enabled + diagnostics <- Sys.getenv("RENV_STARTUP_DIAGNOSTICS", unset = "FALSE") + if (diagnostics) { + start <- Sys.time() + profile <- tempfile("renv-startup-", fileext = ".Rprof") + utils::Rprof(profile) + on.exit({ + utils::Rprof(NULL) + elapsed <- signif(difftime(Sys.time(), start, units = "auto"), digits = 2L) + writeLines(sprintf("- renv took %s to run the autoloader.", format(elapsed))) + writeLines(sprintf("- Profile: %s", profile)) + print(utils::summaryRprof(profile)) + }, add = TRUE) + } + + # figure out whether the autoloader is enabled + enabled <- local({ + + # first, check config option + override <- getOption("renv.config.autoloader.enabled") + if (!is.null(override)) + return(override) + + # if we're being run in a context where R_LIBS is already set, + # don't load -- presumably we're being run as a sub-process and + # the parent process has already set up library paths for us + rcmd <- Sys.getenv("R_CMD", unset = NA) + rlibs <- Sys.getenv("R_LIBS", unset = NA) + if (!is.na(rlibs) && !is.na(rcmd)) + return(FALSE) + + # next, check environment variables + # prefer using the configuration one in the future + envvars <- c( + "RENV_CONFIG_AUTOLOADER_ENABLED", + "RENV_AUTOLOADER_ENABLED", + "RENV_ACTIVATE_PROJECT" + ) + + for (envvar in envvars) { + envval <- Sys.getenv(envvar, unset = NA) + if (!is.na(envval)) + return(tolower(envval) %in% c("true", "t", "1")) + } + + # enable by default + TRUE + + }) + + # bail if we're not enabled + if (!enabled) { + + # if we're not enabled, we might still need to manually load + # the user profile here + profile <- Sys.getenv("R_PROFILE_USER", unset = "~/.Rprofile") + if (file.exists(profile)) { + cfg <- Sys.getenv("RENV_CONFIG_USER_PROFILE", unset = "TRUE") + if (tolower(cfg) %in% c("true", "t", "1")) + sys.source(profile, envir = globalenv()) + } + + return(FALSE) + + } + + # avoid recursion + if (identical(getOption("renv.autoloader.running"), TRUE)) { + warning("ignoring recursive attempt to run renv autoloader") + return(invisible(TRUE)) + } + + # signal that we're loading renv during R startup + options(renv.autoloader.running = TRUE) + on.exit(options(renv.autoloader.running = NULL), add = TRUE) + + # signal that we've consented to use renv + options(renv.consent = TRUE) + + # load the 'utils' package eagerly -- this ensures that renv shims, which + # mask 'utils' packages, will come first on the search path + library(utils, lib.loc = .Library) + + # unload renv if it's already been loaded + if ("renv" %in% loadedNamespaces()) + unloadNamespace("renv") + + # load bootstrap tools + ansify <- function(text) { + if (renv_ansify_enabled()) + renv_ansify_enhanced(text) + else + renv_ansify_default(text) + } + + renv_ansify_enabled <- function() { + + override <- Sys.getenv("RENV_ANSIFY_ENABLED", unset = NA) + if (!is.na(override)) + return(as.logical(override)) + + pane <- Sys.getenv("RSTUDIO_CHILD_PROCESS_PANE", unset = NA) + if (identical(pane, "build")) + return(FALSE) + + testthat <- Sys.getenv("TESTTHAT", unset = "false") + if (tolower(testthat) %in% "true") + return(FALSE) + + iderun <- Sys.getenv("R_CLI_HAS_HYPERLINK_IDE_RUN", unset = "false") + if (tolower(iderun) %in% "false") + return(FALSE) + + TRUE + + } + + renv_ansify_default <- function(text) { + text + } + + renv_ansify_enhanced <- function(text) { + + # R help links + pattern <- "`\\?(renv::(?:[^`])+)`" + replacement <- "`\033]8;;x-r-help:\\1\a?\\1\033]8;;\a`" + text <- gsub(pattern, replacement, text, perl = TRUE) + + # runnable code + pattern <- "`(renv::(?:[^`])+)`" + replacement <- "`\033]8;;x-r-run:\\1\a\\1\033]8;;\a`" + text <- gsub(pattern, replacement, text, perl = TRUE) + + # return ansified text + text + + } + + renv_ansify_init <- function() { + + envir <- renv_envir_self() + if (renv_ansify_enabled()) + assign("ansify", renv_ansify_enhanced, envir = envir) + else + assign("ansify", renv_ansify_default, envir = envir) + + } + + `%||%` <- function(x, y) { + if (is.null(x)) y else x + } + + catf <- function(fmt, ..., appendLF = TRUE) { + + quiet <- getOption("renv.bootstrap.quiet", default = FALSE) + if (quiet) + return(invisible()) + + msg <- sprintf(fmt, ...) + cat(msg, file = stdout(), sep = if (appendLF) "\n" else "") + + invisible(msg) + + } + + header <- function(label, + ..., + prefix = "#", + suffix = "-", + n = min(getOption("width"), 78)) + { + label <- sprintf(label, ...) + n <- max(n - nchar(label) - nchar(prefix) - 2L, 8L) + if (n <= 0) + return(paste(prefix, label)) + + tail <- paste(rep.int(suffix, n), collapse = "") + paste0(prefix, " ", label, " ", tail) + + } + + heredoc <- function(text, leave = 0) { + + # remove leading, trailing whitespace + trimmed <- gsub("^\\s*\\n|\\n\\s*$", "", text) + + # split into lines + lines <- strsplit(trimmed, "\n", fixed = TRUE)[[1L]] + + # compute common indent + indent <- regexpr("[^[:space:]]", lines) + common <- min(setdiff(indent, -1L)) - leave + text <- paste(substring(lines, common), collapse = "\n") + + # substitute in ANSI links for executable renv code + ansify(text) + + } + + bootstrap <- function(version, library) { + + friendly <- renv_bootstrap_version_friendly(version) + section <- header(sprintf("Bootstrapping renv %s", friendly)) + catf(section) + + # attempt to download renv + catf("- Downloading renv ... ", appendLF = FALSE) + withCallingHandlers( + tarball <- renv_bootstrap_download(version), + error = function(err) { + catf("FAILED") + stop("failed to download:\n", conditionMessage(err)) + } + ) + catf("OK") + on.exit(unlink(tarball), add = TRUE) + + # now attempt to install + catf("- Installing renv ... ", appendLF = FALSE) + withCallingHandlers( + status <- renv_bootstrap_install(version, tarball, library), + error = function(err) { + catf("FAILED") + stop("failed to install:\n", conditionMessage(err)) + } + ) + catf("OK") + + # add empty line to break up bootstrapping from normal output + catf("") + + return(invisible()) + } + + renv_bootstrap_tests_running <- function() { + getOption("renv.tests.running", default = FALSE) + } + + renv_bootstrap_repos <- function() { + + # get CRAN repository + cran <- getOption("renv.repos.cran", "https://cloud.r-project.org") + + # check for repos override + repos <- Sys.getenv("RENV_CONFIG_REPOS_OVERRIDE", unset = NA) + if (!is.na(repos)) { + + # check for RSPM; if set, use a fallback repository for renv + rspm <- Sys.getenv("RSPM", unset = NA) + if (identical(rspm, repos)) + repos <- c(RSPM = rspm, CRAN = cran) + + return(repos) + + } + + # check for lockfile repositories + repos <- tryCatch(renv_bootstrap_repos_lockfile(), error = identity) + if (!inherits(repos, "error") && length(repos)) + return(repos) + + # retrieve current repos + repos <- getOption("repos") + + # ensure @CRAN@ entries are resolved + repos[repos == "@CRAN@"] <- cran + + # add in renv.bootstrap.repos if set + default <- c(FALLBACK = "https://cloud.r-project.org") + extra <- getOption("renv.bootstrap.repos", default = default) + repos <- c(repos, extra) + + # remove duplicates that might've snuck in + dupes <- duplicated(repos) | duplicated(names(repos)) + repos[!dupes] + + } + + renv_bootstrap_repos_lockfile <- function() { + + lockpath <- Sys.getenv("RENV_PATHS_LOCKFILE", unset = "renv.lock") + if (!file.exists(lockpath)) + return(NULL) + + lockfile <- tryCatch(renv_json_read(lockpath), error = identity) + if (inherits(lockfile, "error")) { + warning(lockfile) + return(NULL) + } + + repos <- lockfile$R$Repositories + if (length(repos) == 0) + return(NULL) + + keys <- vapply(repos, `[[`, "Name", FUN.VALUE = character(1)) + vals <- vapply(repos, `[[`, "URL", FUN.VALUE = character(1)) + names(vals) <- keys + + return(vals) + + } + + renv_bootstrap_download <- function(version) { + + sha <- attr(version, "sha", exact = TRUE) + + methods <- if (!is.null(sha)) { + + # attempting to bootstrap a development version of renv + c( + function() renv_bootstrap_download_tarball(sha), + function() renv_bootstrap_download_github(sha) + ) + + } else { + + # attempting to bootstrap a release version of renv + c( + function() renv_bootstrap_download_tarball(version), + function() renv_bootstrap_download_cran_latest(version), + function() renv_bootstrap_download_cran_archive(version) + ) + + } + + for (method in methods) { + path <- tryCatch(method(), error = identity) + if (is.character(path) && file.exists(path)) + return(path) + } + + stop("All download methods failed") + + } + + renv_bootstrap_download_impl <- function(url, destfile) { + + mode <- "wb" + + # https://bugs.r-project.org/bugzilla/show_bug.cgi?id=17715 + fixup <- + Sys.info()[["sysname"]] == "Windows" && + substring(url, 1L, 5L) == "file:" + + if (fixup) + mode <- "w+b" + + args <- list( + url = url, + destfile = destfile, + mode = mode, + quiet = TRUE + ) + + if ("headers" %in% names(formals(utils::download.file))) { + headers <- renv_bootstrap_download_custom_headers(url) + if (length(headers) && is.character(headers)) + args$headers <- headers + } + + do.call(utils::download.file, args) + + } + + renv_bootstrap_download_custom_headers <- function(url) { + + headers <- getOption("renv.download.headers") + if (is.null(headers)) + return(character()) + + if (!is.function(headers)) + stopf("'renv.download.headers' is not a function") + + headers <- headers(url) + if (length(headers) == 0L) + return(character()) + + if (is.list(headers)) + headers <- unlist(headers, recursive = FALSE, use.names = TRUE) + + ok <- + is.character(headers) && + is.character(names(headers)) && + all(nzchar(names(headers))) + + if (!ok) + stop("invocation of 'renv.download.headers' did not return a named character vector") + + headers + + } + + renv_bootstrap_download_cran_latest <- function(version) { + + spec <- renv_bootstrap_download_cran_latest_find(version) + type <- spec$type + repos <- spec$repos + + baseurl <- utils::contrib.url(repos = repos, type = type) + ext <- if (identical(type, "source")) + ".tar.gz" + else if (Sys.info()[["sysname"]] == "Windows") + ".zip" + else + ".tgz" + name <- sprintf("renv_%s%s", version, ext) + url <- paste(baseurl, name, sep = "/") + + destfile <- file.path(tempdir(), name) + status <- tryCatch( + renv_bootstrap_download_impl(url, destfile), + condition = identity + ) + + if (inherits(status, "condition")) + return(FALSE) + + # report success and return + destfile + + } + + renv_bootstrap_download_cran_latest_find <- function(version) { + + # check whether binaries are supported on this system + binary <- + getOption("renv.bootstrap.binary", default = TRUE) && + !identical(.Platform$pkgType, "source") && + !identical(getOption("pkgType"), "source") && + Sys.info()[["sysname"]] %in% c("Darwin", "Windows") + + types <- c(if (binary) "binary", "source") + + # iterate over types + repositories + for (type in types) { + for (repos in renv_bootstrap_repos()) { + + # build arguments for utils::available.packages() call + args <- list(type = type, repos = repos) + + # add custom headers if available -- note that + # utils::available.packages() will pass this to download.file() + if ("headers" %in% names(formals(utils::download.file))) { + headers <- renv_bootstrap_download_custom_headers(repos) + if (length(headers) && is.character(headers)) + args$headers <- headers + } + + # retrieve package database + db <- tryCatch( + as.data.frame( + do.call(utils::available.packages, args), + stringsAsFactors = FALSE + ), + error = identity + ) + + if (inherits(db, "error")) + next + + # check for compatible entry + entry <- db[db$Package %in% "renv" & db$Version %in% version, ] + if (nrow(entry) == 0) + next + + # found it; return spec to caller + spec <- list(entry = entry, type = type, repos = repos) + return(spec) + + } + } + + # if we got here, we failed to find renv + fmt <- "renv %s is not available from your declared package repositories" + stop(sprintf(fmt, version)) + + } + + renv_bootstrap_download_cran_archive <- function(version) { + + name <- sprintf("renv_%s.tar.gz", version) + repos <- renv_bootstrap_repos() + urls <- file.path(repos, "src/contrib/Archive/renv", name) + destfile <- file.path(tempdir(), name) + + for (url in urls) { + + status <- tryCatch( + renv_bootstrap_download_impl(url, destfile), + condition = identity + ) + + if (identical(status, 0L)) + return(destfile) + + } + + return(FALSE) + + } + + renv_bootstrap_download_tarball <- function(version) { + + # if the user has provided the path to a tarball via + # an environment variable, then use it + tarball <- Sys.getenv("RENV_BOOTSTRAP_TARBALL", unset = NA) + if (is.na(tarball)) + return() + + # allow directories + if (dir.exists(tarball)) { + name <- sprintf("renv_%s.tar.gz", version) + tarball <- file.path(tarball, name) + } + + # bail if it doesn't exist + if (!file.exists(tarball)) { + + # let the user know we weren't able to honour their request + fmt <- "- RENV_BOOTSTRAP_TARBALL is set (%s) but does not exist." + msg <- sprintf(fmt, tarball) + warning(msg) + + # bail + return() + + } + + catf("- Using local tarball '%s'.", tarball) + tarball + + } + + renv_bootstrap_github_token <- function() { + for (envvar in c("GITHUB_TOKEN", "GITHUB_PAT", "GH_TOKEN")) { + envval <- Sys.getenv(envvar, unset = NA) + if (!is.na(envval)) + return(envval) + } + } + + renv_bootstrap_download_github <- function(version) { + + enabled <- Sys.getenv("RENV_BOOTSTRAP_FROM_GITHUB", unset = "TRUE") + if (!identical(enabled, "TRUE")) + return(FALSE) + + # prepare download options + token <- renv_bootstrap_github_token() + if (is.null(token)) + token <- "" + + if (nzchar(Sys.which("curl")) && nzchar(token)) { + fmt <- "--location --fail --header \"Authorization: token %s\"" + extra <- sprintf(fmt, token) + saved <- options("download.file.method", "download.file.extra") + options(download.file.method = "curl", download.file.extra = extra) + on.exit(do.call(base::options, saved), add = TRUE) + } else if (nzchar(Sys.which("wget")) && nzchar(token)) { + fmt <- "--header=\"Authorization: token %s\"" + extra <- sprintf(fmt, token) + saved <- options("download.file.method", "download.file.extra") + options(download.file.method = "wget", download.file.extra = extra) + on.exit(do.call(base::options, saved), add = TRUE) + } + + url <- file.path("https://api.github.com/repos/rstudio/renv/tarball", version) + name <- sprintf("renv_%s.tar.gz", version) + destfile <- file.path(tempdir(), name) + + status <- tryCatch( + renv_bootstrap_download_impl(url, destfile), + condition = identity + ) + + if (!identical(status, 0L)) + return(FALSE) + + renv_bootstrap_download_augment(destfile) + + return(destfile) + + } + + # Add Sha to DESCRIPTION. This is stop gap until #890, after which we + # can use renv::install() to fully capture metadata. + renv_bootstrap_download_augment <- function(destfile) { + sha <- renv_bootstrap_git_extract_sha1_tar(destfile) + if (is.null(sha)) { + return() + } + + # Untar + tempdir <- tempfile("renv-github-") + on.exit(unlink(tempdir, recursive = TRUE), add = TRUE) + untar(destfile, exdir = tempdir) + pkgdir <- dir(tempdir, full.names = TRUE)[[1]] + + # Modify description + desc_path <- file.path(pkgdir, "DESCRIPTION") + desc_lines <- readLines(desc_path) + remotes_fields <- c( + "RemoteType: github", + "RemoteHost: api.github.com", + "RemoteRepo: renv", + "RemoteUsername: rstudio", + "RemotePkgRef: rstudio/renv", + paste("RemoteRef: ", sha), + paste("RemoteSha: ", sha) + ) + writeLines(c(desc_lines[desc_lines != ""], remotes_fields), con = desc_path) + + # Re-tar + local({ + old <- setwd(tempdir) + on.exit(setwd(old), add = TRUE) + + tar(destfile, compression = "gzip") + }) + invisible() + } + + # Extract the commit hash from a git archive. Git archives include the SHA1 + # hash as the comment field of the tarball pax extended header + # (see https://www.kernel.org/pub/software/scm/git/docs/git-archive.html) + # For GitHub archives this should be the first header after the default one + # (512 byte) header. + renv_bootstrap_git_extract_sha1_tar <- function(bundle) { + + # open the bundle for reading + # We use gzcon for everything because (from ?gzcon) + # > Reading from a connection which does not supply a 'gzip' magic + # > header is equivalent to reading from the original connection + conn <- gzcon(file(bundle, open = "rb", raw = TRUE)) + on.exit(close(conn)) + + # The default pax header is 512 bytes long and the first pax extended header + # with the comment should be 51 bytes long + # `52 comment=` (11 chars) + 40 byte SHA1 hash + len <- 0x200 + 0x33 + res <- rawToChar(readBin(conn, "raw", n = len)[0x201:len]) + + if (grepl("^52 comment=", res)) { + sub("52 comment=", "", res) + } else { + NULL + } + } + + renv_bootstrap_install <- function(version, tarball, library) { + + # attempt to install it into project library + dir.create(library, showWarnings = FALSE, recursive = TRUE) + output <- renv_bootstrap_install_impl(library, tarball) + + # check for successful install + status <- attr(output, "status") + if (is.null(status) || identical(status, 0L)) + return(status) + + # an error occurred; report it + header <- "installation of renv failed" + lines <- paste(rep.int("=", nchar(header)), collapse = "") + text <- paste(c(header, lines, output), collapse = "\n") + stop(text) + + } + + renv_bootstrap_install_impl <- function(library, tarball) { + + # invoke using system2 so we can capture and report output + bin <- R.home("bin") + exe <- if (Sys.info()[["sysname"]] == "Windows") "R.exe" else "R" + R <- file.path(bin, exe) + + args <- c( + "--vanilla", "CMD", "INSTALL", "--no-multiarch", + "-l", shQuote(path.expand(library)), + shQuote(path.expand(tarball)) + ) + + system2(R, args, stdout = TRUE, stderr = TRUE) + + } + + renv_bootstrap_platform_prefix_default <- function() { + + # read version component + version <- Sys.getenv("RENV_PATHS_VERSION", unset = "R-%v") + + # expand placeholders + placeholders <- list( + list("%v", format(getRversion()[1, 1:2])), + list("%V", format(getRversion()[1, 1:3])) + ) + + for (placeholder in placeholders) + version <- gsub(placeholder[[1L]], placeholder[[2L]], version, fixed = TRUE) + + # include SVN revision for development versions of R + # (to avoid sharing platform-specific artefacts with released versions of R) + devel <- + identical(R.version[["status"]], "Under development (unstable)") || + identical(R.version[["nickname"]], "Unsuffered Consequences") + + if (devel) + version <- paste(version, R.version[["svn rev"]], sep = "-r") + + version + + } + + renv_bootstrap_platform_prefix <- function() { + + # construct version prefix + version <- renv_bootstrap_platform_prefix_default() + + # build list of path components + components <- c(version, R.version$platform) + + # include prefix if provided by user + prefix <- renv_bootstrap_platform_prefix_impl() + if (!is.na(prefix) && nzchar(prefix)) + components <- c(prefix, components) + + # build prefix + paste(components, collapse = "/") + + } + + renv_bootstrap_platform_prefix_impl <- function() { + + # if an explicit prefix has been supplied, use it + prefix <- Sys.getenv("RENV_PATHS_PREFIX", unset = NA) + if (!is.na(prefix)) + return(prefix) + + # if the user has requested an automatic prefix, generate it + auto <- Sys.getenv("RENV_PATHS_PREFIX_AUTO", unset = NA) + if (is.na(auto) && getRversion() >= "4.4.0") + auto <- "TRUE" + + if (auto %in% c("TRUE", "True", "true", "1")) + return(renv_bootstrap_platform_prefix_auto()) + + # empty string on failure + "" + + } + + renv_bootstrap_platform_prefix_auto <- function() { + + prefix <- tryCatch(renv_bootstrap_platform_os(), error = identity) + if (inherits(prefix, "error") || prefix %in% "unknown") { + + msg <- paste( + "failed to infer current operating system", + "please file a bug report at https://github.com/rstudio/renv/issues", + sep = "; " + ) + + warning(msg) + + } + + prefix + + } + + renv_bootstrap_platform_os <- function() { + + sysinfo <- Sys.info() + sysname <- sysinfo[["sysname"]] + + # handle Windows + macOS up front + if (sysname == "Windows") + return("windows") + else if (sysname == "Darwin") + return("macos") + + # check for os-release files + for (file in c("/etc/os-release", "/usr/lib/os-release")) + if (file.exists(file)) + return(renv_bootstrap_platform_os_via_os_release(file, sysinfo)) + + # check for redhat-release files + if (file.exists("/etc/redhat-release")) + return(renv_bootstrap_platform_os_via_redhat_release()) + + "unknown" + + } + + renv_bootstrap_platform_os_via_os_release <- function(file, sysinfo) { + + # read /etc/os-release + release <- utils::read.table( + file = file, + sep = "=", + quote = c("\"", "'"), + col.names = c("Key", "Value"), + comment.char = "#", + stringsAsFactors = FALSE + ) + + vars <- as.list(release$Value) + names(vars) <- release$Key + + # get os name + os <- tolower(sysinfo[["sysname"]]) + + # read id + id <- "unknown" + for (field in c("ID", "ID_LIKE")) { + if (field %in% names(vars) && nzchar(vars[[field]])) { + id <- vars[[field]] + break + } + } + + # read version + version <- "unknown" + for (field in c("UBUNTU_CODENAME", "VERSION_CODENAME", "VERSION_ID", "BUILD_ID")) { + if (field %in% names(vars) && nzchar(vars[[field]])) { + version <- vars[[field]] + break + } + } + + # join together + paste(c(os, id, version), collapse = "-") + + } + + renv_bootstrap_platform_os_via_redhat_release <- function() { + + # read /etc/redhat-release + contents <- readLines("/etc/redhat-release", warn = FALSE) + + # infer id + id <- if (grepl("centos", contents, ignore.case = TRUE)) + "centos" + else if (grepl("redhat", contents, ignore.case = TRUE)) + "redhat" + else + "unknown" + + # try to find a version component (very hacky) + version <- "unknown" + + parts <- strsplit(contents, "[[:space:]]")[[1L]] + for (part in parts) { + + nv <- tryCatch(numeric_version(part), error = identity) + if (inherits(nv, "error")) + next + + version <- nv[1, 1] + break + + } + + paste(c("linux", id, version), collapse = "-") + + } + + renv_bootstrap_library_root_name <- function(project) { + + # use project name as-is if requested + asis <- Sys.getenv("RENV_PATHS_LIBRARY_ROOT_ASIS", unset = "FALSE") + if (asis) + return(basename(project)) + + # otherwise, disambiguate based on project's path + id <- substring(renv_bootstrap_hash_text(project), 1L, 8L) + paste(basename(project), id, sep = "-") + + } + + renv_bootstrap_library_root <- function(project) { + + prefix <- renv_bootstrap_profile_prefix() + + path <- Sys.getenv("RENV_PATHS_LIBRARY", unset = NA) + if (!is.na(path)) + return(paste(c(path, prefix), collapse = "/")) + + path <- renv_bootstrap_library_root_impl(project) + if (!is.null(path)) { + name <- renv_bootstrap_library_root_name(project) + return(paste(c(path, prefix, name), collapse = "/")) + } + + renv_bootstrap_paths_renv("library", project = project) + + } + + renv_bootstrap_library_root_impl <- function(project) { + + root <- Sys.getenv("RENV_PATHS_LIBRARY_ROOT", unset = NA) + if (!is.na(root)) + return(root) + + type <- renv_bootstrap_project_type(project) + if (identical(type, "package")) { + userdir <- renv_bootstrap_user_dir() + return(file.path(userdir, "library")) + } + + } + + renv_bootstrap_validate_version <- function(version, description = NULL) { + + # resolve description file + # + # avoid passing lib.loc to `packageDescription()` below, since R will + # use the loaded version of the package by default anyhow. note that + # this function should only be called after 'renv' is loaded + # https://github.com/rstudio/renv/issues/1625 + description <- description %||% packageDescription("renv") + + # check whether requested version 'version' matches loaded version of renv + sha <- attr(version, "sha", exact = TRUE) + valid <- if (!is.null(sha)) + renv_bootstrap_validate_version_dev(sha, description) + else + renv_bootstrap_validate_version_release(version, description) + + if (valid) + return(TRUE) + + # the loaded version of renv doesn't match the requested version; + # give the user instructions on how to proceed + dev <- identical(description[["RemoteType"]], "github") + remote <- if (dev) + paste("rstudio/renv", description[["RemoteSha"]], sep = "@") + else + paste("renv", description[["Version"]], sep = "@") + + # display both loaded version + sha if available + friendly <- renv_bootstrap_version_friendly( + version = description[["Version"]], + sha = if (dev) description[["RemoteSha"]] + ) + + fmt <- heredoc(" + renv %1$s was loaded from project library, but this project is configured to use renv %2$s. + - Use `renv::record(\"%3$s\")` to record renv %1$s in the lockfile. + - Use `renv::restore(packages = \"renv\")` to install renv %2$s into the project library. + ") + catf(fmt, friendly, renv_bootstrap_version_friendly(version), remote) + + FALSE + + } + + renv_bootstrap_validate_version_dev <- function(version, description) { + + expected <- description[["RemoteSha"]] + if (!is.character(expected)) + return(FALSE) + + pattern <- sprintf("^\\Q%s\\E", version) + grepl(pattern, expected, perl = TRUE) + + } + + renv_bootstrap_validate_version_release <- function(version, description) { + expected <- description[["Version"]] + is.character(expected) && identical(expected, version) + } + + renv_bootstrap_hash_text <- function(text) { + + hashfile <- tempfile("renv-hash-") + on.exit(unlink(hashfile), add = TRUE) + + writeLines(text, con = hashfile) + tools::md5sum(hashfile) + + } + + renv_bootstrap_load <- function(project, libpath, version) { + + # try to load renv from the project library + if (!requireNamespace("renv", lib.loc = libpath, quietly = TRUE)) + return(FALSE) + + # warn if the version of renv loaded does not match + renv_bootstrap_validate_version(version) + + # execute renv load hooks, if any + hooks <- getHook("renv::autoload") + for (hook in hooks) + if (is.function(hook)) + tryCatch(hook(), error = warnify) + + # load the project + renv::load(project) + + TRUE + + } + + renv_bootstrap_profile_load <- function(project) { + + # if RENV_PROFILE is already set, just use that + profile <- Sys.getenv("RENV_PROFILE", unset = NA) + if (!is.na(profile) && nzchar(profile)) + return(profile) + + # check for a profile file (nothing to do if it doesn't exist) + path <- renv_bootstrap_paths_renv("profile", profile = FALSE, project = project) + if (!file.exists(path)) + return(NULL) + + # read the profile, and set it if it exists + contents <- readLines(path, warn = FALSE) + if (length(contents) == 0L) + return(NULL) + + # set RENV_PROFILE + profile <- contents[[1L]] + if (!profile %in% c("", "default")) + Sys.setenv(RENV_PROFILE = profile) + + profile + + } + + renv_bootstrap_profile_prefix <- function() { + profile <- renv_bootstrap_profile_get() + if (!is.null(profile)) + return(file.path("profiles", profile, "renv")) + } + + renv_bootstrap_profile_get <- function() { + profile <- Sys.getenv("RENV_PROFILE", unset = "") + renv_bootstrap_profile_normalize(profile) + } + + renv_bootstrap_profile_set <- function(profile) { + profile <- renv_bootstrap_profile_normalize(profile) + if (is.null(profile)) + Sys.unsetenv("RENV_PROFILE") + else + Sys.setenv(RENV_PROFILE = profile) + } + + renv_bootstrap_profile_normalize <- function(profile) { + + if (is.null(profile) || profile %in% c("", "default")) + return(NULL) + + profile + + } + + renv_bootstrap_path_absolute <- function(path) { + + substr(path, 1L, 1L) %in% c("~", "/", "\\") || ( + substr(path, 1L, 1L) %in% c(letters, LETTERS) && + substr(path, 2L, 3L) %in% c(":/", ":\\") + ) + + } + + renv_bootstrap_paths_renv <- function(..., profile = TRUE, project = NULL) { + renv <- Sys.getenv("RENV_PATHS_RENV", unset = "renv") + root <- if (renv_bootstrap_path_absolute(renv)) NULL else project + prefix <- if (profile) renv_bootstrap_profile_prefix() + components <- c(root, renv, prefix, ...) + paste(components, collapse = "/") + } + + renv_bootstrap_project_type <- function(path) { + + descpath <- file.path(path, "DESCRIPTION") + if (!file.exists(descpath)) + return("unknown") + + desc <- tryCatch( + read.dcf(descpath, all = TRUE), + error = identity + ) + + if (inherits(desc, "error")) + return("unknown") + + type <- desc$Type + if (!is.null(type)) + return(tolower(type)) + + package <- desc$Package + if (!is.null(package)) + return("package") + + "unknown" + + } + + renv_bootstrap_user_dir <- function() { + dir <- renv_bootstrap_user_dir_impl() + path.expand(chartr("\\", "/", dir)) + } + + renv_bootstrap_user_dir_impl <- function() { + + # use local override if set + override <- getOption("renv.userdir.override") + if (!is.null(override)) + return(override) + + # use R_user_dir if available + tools <- asNamespace("tools") + if (is.function(tools$R_user_dir)) + return(tools$R_user_dir("renv", "cache")) + + # try using our own backfill for older versions of R + envvars <- c("R_USER_CACHE_DIR", "XDG_CACHE_HOME") + for (envvar in envvars) { + root <- Sys.getenv(envvar, unset = NA) + if (!is.na(root)) + return(file.path(root, "R/renv")) + } + + # use platform-specific default fallbacks + if (Sys.info()[["sysname"]] == "Windows") + file.path(Sys.getenv("LOCALAPPDATA"), "R/cache/R/renv") + else if (Sys.info()[["sysname"]] == "Darwin") + "~/Library/Caches/org.R-project.R/R/renv" + else + "~/.cache/R/renv" + + } + + renv_bootstrap_version_friendly <- function(version, shafmt = NULL, sha = NULL) { + sha <- sha %||% attr(version, "sha", exact = TRUE) + parts <- c(version, sprintf(shafmt %||% " [sha: %s]", substring(sha, 1L, 7L))) + paste(parts, collapse = "") + } + + renv_bootstrap_exec <- function(project, libpath, version) { + if (!renv_bootstrap_load(project, libpath, version)) + renv_bootstrap_run(project, libpath, version) + } + + renv_bootstrap_run <- function(project, libpath, version) { + + # perform bootstrap + bootstrap(version, libpath) + + # exit early if we're just testing bootstrap + if (!is.na(Sys.getenv("RENV_BOOTSTRAP_INSTALL_ONLY", unset = NA))) + return(TRUE) + + # try again to load + if (requireNamespace("renv", lib.loc = libpath, quietly = TRUE)) { + return(renv::load(project = project)) + } + + # failed to download or load renv; warn the user + msg <- c( + "Failed to find an renv installation: the project will not be loaded.", + "Use `renv::activate()` to re-initialize the project." + ) + + warning(paste(msg, collapse = "\n"), call. = FALSE) + + } + + renv_json_read <- function(file = NULL, text = NULL) { + + jlerr <- NULL + + # if jsonlite is loaded, use that instead + if ("jsonlite" %in% loadedNamespaces()) { + + json <- tryCatch(renv_json_read_jsonlite(file, text), error = identity) + if (!inherits(json, "error")) + return(json) + + jlerr <- json + + } + + # otherwise, fall back to the default JSON reader + json <- tryCatch(renv_json_read_default(file, text), error = identity) + if (!inherits(json, "error")) + return(json) + + # report an error + if (!is.null(jlerr)) + stop(jlerr) + else + stop(json) + + } + + renv_json_read_jsonlite <- function(file = NULL, text = NULL) { + text <- paste(text %||% readLines(file, warn = FALSE), collapse = "\n") + jsonlite::fromJSON(txt = text, simplifyVector = FALSE) + } + + renv_json_read_patterns <- function() { + + list( + + # objects + list("{", "\t\n\tobject(\t\n\t", TRUE), + list("}", "\t\n\t)\t\n\t", TRUE), + + # arrays + list("[", "\t\n\tarray(\t\n\t", TRUE), + list("]", "\n\t\n)\n\t\n", TRUE), + + # maps + list(":", "\t\n\t=\t\n\t", TRUE), + + # newlines + list("\\u000a", "\n", FALSE) + + ) + + } + + renv_json_read_envir <- function() { + + envir <- new.env(parent = emptyenv()) + + envir[["+"]] <- `+` + envir[["-"]] <- `-` + + envir[["object"]] <- function(...) { + result <- list(...) + names(result) <- as.character(names(result)) + result + } + + envir[["array"]] <- list + + envir[["true"]] <- TRUE + envir[["false"]] <- FALSE + envir[["null"]] <- NULL + + envir + + } + + renv_json_read_remap <- function(object, patterns) { + + # repair names if necessary + if (!is.null(names(object))) { + + nms <- names(object) + for (pattern in patterns) + nms <- gsub(pattern[[2L]], pattern[[1L]], nms, fixed = TRUE) + names(object) <- nms + + } + + # repair strings if necessary + if (is.character(object)) { + for (pattern in patterns) + object <- gsub(pattern[[2L]], pattern[[1L]], object, fixed = TRUE) + } + + # recurse for other objects + if (is.recursive(object)) + for (i in seq_along(object)) + object[i] <- list(renv_json_read_remap(object[[i]], patterns)) + + # return remapped object + object + + } + + renv_json_read_default <- function(file = NULL, text = NULL) { + + # read json text + text <- paste(text %||% readLines(file, warn = FALSE), collapse = "\n") + + # convert into something the R parser will understand + patterns <- renv_json_read_patterns() + transformed <- text + for (pattern in patterns) + transformed <- gsub(pattern[[1L]], pattern[[2L]], transformed, fixed = TRUE) + + # parse it + rfile <- tempfile("renv-json-", fileext = ".R") + on.exit(unlink(rfile), add = TRUE) + writeLines(transformed, con = rfile) + json <- parse(rfile, keep.source = FALSE, srcfile = NULL)[[1L]] + + # evaluate in safe environment + result <- eval(json, envir = renv_json_read_envir()) + + # fix up strings if necessary -- do so only with reversible patterns + patterns <- Filter(function(pattern) pattern[[3L]], patterns) + renv_json_read_remap(result, patterns) + + } + + + # load the renv profile, if any + renv_bootstrap_profile_load(project) + + # construct path to library root + root <- renv_bootstrap_library_root(project) + + # construct library prefix for platform + prefix <- renv_bootstrap_platform_prefix() + + # construct full libpath + libpath <- file.path(root, prefix) + + # run bootstrap code + renv_bootstrap_exec(project, libpath, version) + + invisible() + +}) diff --git a/renv/settings.json b/renv/settings.json new file mode 100644 index 0000000..a1ae228 --- /dev/null +++ b/renv/settings.json @@ -0,0 +1,19 @@ +{ + "bioconductor.version": null, + "external.libraries": [], + "ignored.packages": [], + "package.dependency.fields": [ + "Imports", + "Depends", + "LinkingTo" + ], + "ppm.enabled": null, + "ppm.ignored.urls": [], + "r.version": null, + "snapshot.type": "all", + "use.cache": true, + "vcs.ignore.cellar": true, + "vcs.ignore.library": true, + "vcs.ignore.local": true, + "vcs.manage.ignores": true +} diff --git a/tests/testthat.R b/tests/testthat.R new file mode 100644 index 0000000..62cd062 --- /dev/null +++ b/tests/testthat.R @@ -0,0 +1,5 @@ +# This file is part of the standard testthat testing infrastructure +library(testthat) +library(MockData) + +test_check("MockData") diff --git a/tests/testthat/test-add-garbage.R b/tests/testthat/test-add-garbage.R new file mode 100644 index 0000000..eb3daf0 --- /dev/null +++ b/tests/testthat/test-add-garbage.R @@ -0,0 +1,162 @@ +test_that("add_garbage() adds garbage specifications to variables data frame", { + # Setup: minimal variables data frame + variables <- data.frame( + variable = c("age", "smoking", "BMI"), + variableType = c("Continuous", "Categorical", "Continuous"), + stringsAsFactors = FALSE + ) + + # Test 1: Add high-range garbage to age + result <- add_garbage(variables, "age", + garbage_high_prop = 0.03, garbage_high_range = "[150, 200]") + + expect_true("garbage_high_prop" %in% names(result)) + expect_true("garbage_high_range" %in% names(result)) + expect_equal(result$garbage_high_prop[result$variable == "age"], 0.03) + expect_equal(result$garbage_high_range[result$variable == "age"], "[150, 200]") + + # Other variables should have NA + expect_true(is.na(result$garbage_high_prop[result$variable == "smoking"])) + expect_true(is.na(result$garbage_high_prop[result$variable == "BMI"])) +}) + +test_that("add_garbage() adds low-range garbage specifications", { + variables <- data.frame( + variable = c("smoking"), + variableType = c("Categorical"), + stringsAsFactors = FALSE + ) + + result <- add_garbage(variables, "smoking", + garbage_low_prop = 0.02, garbage_low_range = "[-2, 0]") + + expect_equal(result$garbage_low_prop[result$variable == "smoking"], 0.02) + expect_equal(result$garbage_low_range[result$variable == "smoking"], "[-2, 0]") +}) + +test_that("add_garbage() adds two-sided garbage (low + high)", { + variables <- data.frame( + variable = c("BMI"), + variableType = c("Continuous"), + stringsAsFactors = FALSE + ) + + result <- add_garbage(variables, "BMI", + garbage_low_prop = 0.02, garbage_low_range = "[-10, 15)", + garbage_high_prop = 0.01, garbage_high_range = "[60, 150]") + + expect_equal(result$garbage_low_prop[result$variable == "BMI"], 0.02) + expect_equal(result$garbage_low_range[result$variable == "BMI"], "[-10, 15)") + expect_equal(result$garbage_high_prop[result$variable == "BMI"], 0.01) + expect_equal(result$garbage_high_range[result$variable == "BMI"], "[60, 150]") +}) + +test_that("add_garbage() is pipe-friendly (returns modified data frame)", { + variables <- data.frame( + variable = c("age", "smoking"), + variableType = c("Continuous", "Categorical"), + stringsAsFactors = FALSE + ) + + # Chain multiple add_garbage() calls + result <- add_garbage(variables, "age", garbage_high_prop = 0.03, garbage_high_range = "[150, 200]") + result <- add_garbage(result, "smoking", garbage_low_prop = 0.02, garbage_low_range = "[-2, 0]") + + # Check both variables have garbage + expect_equal(result$garbage_high_prop[result$variable == "age"], 0.03) + expect_equal(result$garbage_low_prop[result$variable == "smoking"], 0.02) +}) + +test_that("add_garbage() validates input parameters", { + variables <- data.frame( + variable = c("age"), + variableType = c("Continuous"), + stringsAsFactors = FALSE + ) + + # Test 1: Variable not found + expect_error( + add_garbage(variables, "nonexistent", garbage_high_prop = 0.03, garbage_high_range = "[150, 200]"), + "Variable 'nonexistent' not found" + ) + + # Test 2: Invalid proportion (> 1) + expect_error( + add_garbage(variables, "age", garbage_high_prop = 1.5, garbage_high_range = "[150, 200]"), + "must be a single numeric value between 0 and 1" + ) + + # Test 3: Invalid proportion (< 0) + expect_error( + add_garbage(variables, "age", garbage_high_prop = -0.1, garbage_high_range = "[150, 200]"), + "must be a single numeric value between 0 and 1" + ) + + # Test 4: Missing variable column + invalid_df <- data.frame(var = c("age"), stringsAsFactors = FALSE) + expect_error( + add_garbage(invalid_df, "age", garbage_high_prop = 0.03, garbage_high_range = "[150, 200]"), + "must contain a 'variable' column" + ) +}) + +test_that("add_garbage() creates columns if they don't exist", { + # Start with minimal data frame (no garbage columns) + variables <- data.frame( + variable = c("age"), + variableType = c("Continuous"), + stringsAsFactors = FALSE + ) + + expect_false("garbage_high_prop" %in% names(variables)) + expect_false("garbage_high_range" %in% names(variables)) + + result <- add_garbage(variables, "age", garbage_high_prop = 0.03, garbage_high_range = "[150, 200]") + + # Columns should now exist + expect_true("garbage_high_prop" %in% names(result)) + expect_true("garbage_high_range" %in% names(result)) + + # Should have correct value for age + expect_equal(result$garbage_high_prop[result$variable == "age"], 0.03) + expect_equal(result$garbage_high_range[result$variable == "age"], "[150, 200]") +}) + +test_that("add_garbage() handles NULL parameters (no-op)", { + variables <- data.frame( + variable = c("age"), + variableType = c("Continuous"), + stringsAsFactors = FALSE + ) + + # Call with all NULL parameters + result <- add_garbage(variables, "age", + garbage_low_prop = NULL, garbage_low_range = NULL, + garbage_high_prop = NULL, garbage_high_range = NULL) + + # Should return unchanged data frame (no new columns) + expect_equal(names(result), names(variables)) + expect_equal(nrow(result), nrow(variables)) +}) + +test_that("add_garbage() works with existing garbage columns", { + # Start with data frame that already has garbage columns + variables <- data.frame( + variable = c("age", "BMI"), + variableType = c("Continuous", "Continuous"), + garbage_high_prop = c(NA, 0.05), + garbage_high_range = c(NA, "[100, 200]"), + stringsAsFactors = FALSE + ) + + # Add garbage to age (which has NA) + result <- add_garbage(variables, "age", garbage_high_prop = 0.03, garbage_high_range = "[150, 200]") + + # Age should now have garbage + expect_equal(result$garbage_high_prop[result$variable == "age"], 0.03) + expect_equal(result$garbage_high_range[result$variable == "age"], "[150, 200]") + + # BMI should remain unchanged + expect_equal(result$garbage_high_prop[result$variable == "BMI"], 0.05) + expect_equal(result$garbage_high_range[result$variable == "BMI"], "[100, 200]") +}) diff --git a/tests/testthat/test-categorical-garbage.R b/tests/testthat/test-categorical-garbage.R new file mode 100644 index 0000000..a4ce4da --- /dev/null +++ b/tests/testthat/test-categorical-garbage.R @@ -0,0 +1,247 @@ +test_that("categorical garbage generates invalid codes with unified API", { + # Setup: minimal-example metadata + variables <- read.csv( + system.file("extdata/minimal-example/variables.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + variable_details <- read.csv( + system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + # Add garbage to smoking (valid codes: 1, 2, 3, 7) + vars_with_garbage <- add_garbage(variables, "smoking", + garbage_low_prop = 0.05, garbage_low_range = "[-2, 0]") + + # Generate smoking data with garbage + result <- create_cat_var( + var = "smoking", + databaseStart = "minimal-example", + variables = vars_with_garbage, + variable_details = variable_details, + n = 1000, + seed = 123 + ) + + # Convert factor to numeric to check garbage codes + smoking_numeric <- as.numeric(as.character(result$smoking)) + + # Find garbage values (codes < 1) + garbage_values <- smoking_numeric[smoking_numeric < 1 & !is.na(smoking_numeric)] + n_garbage <- length(garbage_values) + + # Should have approximately 5% garbage (50 out of 1000) + expect_true(n_garbage > 30) # At least 3% + expect_true(n_garbage < 80) # At most 8% + + # Garbage codes should be in range [-2, 0] + expect_true(all(garbage_values >= -2)) + expect_true(all(garbage_values <= 0)) +}) + +test_that("categorical garbage values are included in factor levels", { + variables <- read.csv( + system.file("extdata/minimal-example/variables.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + variable_details <- read.csv( + system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + # Add garbage to smoking + vars_with_garbage <- add_garbage(variables, "smoking", + garbage_low_prop = 0.03, garbage_low_range = "[-2, 0]") + + result <- create_cat_var( + var = "smoking", + databaseStart = "minimal-example", + variables = vars_with_garbage, + variable_details = variable_details, + n = 1000, + seed = 456 + ) + + # Get factor levels + factor_levels <- levels(result$smoking) + + # Should include garbage codes as levels + # (Regression test for bug where garbage codes became NA) + smoking_numeric <- as.numeric(as.character(result$smoking)) + garbage_values <- unique(smoking_numeric[smoking_numeric < 1 & !is.na(smoking_numeric)]) + + if (length(garbage_values) > 0) { + # If garbage was generated, it should be in factor levels + for (garbage_code in garbage_values) { + expect_true(as.character(garbage_code) %in% factor_levels, + info = paste("Garbage code", garbage_code, "should be in factor levels")) + } + } +}) + +test_that("categorical garbage does not convert to NA", { + # Regression test for factor level bug + variables <- read.csv( + system.file("extdata/minimal-example/variables.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + variable_details <- read.csv( + system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + # Add substantial garbage proportion to ensure we get some + vars_with_garbage <- add_garbage(variables, "smoking", + garbage_low_prop = 0.10, garbage_low_range = "[-2, 0]") + + result <- create_cat_var( + var = "smoking", + databaseStart = "minimal-example", + variables = vars_with_garbage, + variable_details = variable_details, + n = 1000, + seed = 789 + ) + + # Count intentional NAs (from missing data proportions in metadata) + smoking_details <- variable_details[variable_details$variable == "smoking", ] + expected_na_prop <- sum(smoking_details$proportion[is.na(smoking_details$recStart)], na.rm = TRUE) + + # Count actual NAs + n_na <- sum(is.na(result$smoking)) + actual_na_prop <- n_na / nrow(result) + + # NA proportion should be close to expected (not inflated by garbage codes) + # Allow Β±5% tolerance + expect_true(abs(actual_na_prop - expected_na_prop) < 0.05, + info = paste("Expected NA prop:", expected_na_prop, "Actual:", actual_na_prop)) +}) + +test_that("categorical garbage works with high-range specification", { + variables <- read.csv( + system.file("extdata/minimal-example/variables.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + variable_details <- read.csv( + system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + # Add high-range garbage (codes > 7) + vars_with_garbage <- add_garbage(variables, "smoking", + garbage_high_prop = 0.05, garbage_high_range = "[10, 15]") + + result <- create_cat_var( + var = "smoking", + databaseStart = "minimal-example", + variables = vars_with_garbage, + variable_details = variable_details, + n = 1000, + seed = 321 + ) + + # Find high-range garbage (codes > 7) + smoking_numeric <- as.numeric(as.character(result$smoking)) + garbage_values <- smoking_numeric[smoking_numeric > 7 & !is.na(smoking_numeric)] + n_garbage <- length(garbage_values) + + # Should have approximately 5% garbage + expect_true(n_garbage > 30) + expect_true(n_garbage < 80) + + # Garbage codes should be in range [10, 15] + expect_true(all(garbage_values >= 10)) + expect_true(all(garbage_values <= 15)) +}) + +test_that("categorical garbage works with two-sided specification", { + variables <- read.csv( + system.file("extdata/minimal-example/variables.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + variable_details <- read.csv( + system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + # Add both low and high garbage + vars_with_garbage <- add_garbage(variables, "smoking", + garbage_low_prop = 0.03, garbage_low_range = "[-2, 0]", + garbage_high_prop = 0.02, garbage_high_range = "[10, 15]") + + result <- create_cat_var( + var = "smoking", + databaseStart = "minimal-example", + variables = vars_with_garbage, + variable_details = variable_details, + n = 1000, + seed = 654 + ) + + smoking_numeric <- as.numeric(as.character(result$smoking)) + + # Find low-range garbage + low_garbage <- smoking_numeric[smoking_numeric < 1 & !is.na(smoking_numeric)] + + # Find high-range garbage + high_garbage <- smoking_numeric[smoking_numeric > 7 & !is.na(smoking_numeric)] + + # Should have garbage in both ranges + expect_true(length(low_garbage) > 15) # ~3% + expect_true(length(high_garbage) > 10) # ~2% + + # Total garbage should be approximately 5% + total_garbage <- length(low_garbage) + length(high_garbage) + expect_true(total_garbage > 35) + expect_true(total_garbage < 70) +}) + +test_that("categorical variables without garbage generate clean data", { + variables <- read.csv( + system.file("extdata/minimal-example/variables.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + variable_details <- read.csv( + system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + # Generate without adding garbage + result <- create_cat_var( + var = "smoking", + databaseStart = "minimal-example", + variables = variables, # No garbage added + variable_details = variable_details, + n = 1000, + seed = 999 + ) + + # Get valid codes from metadata + smoking_details <- variable_details[variable_details$variable == "smoking", ] + valid_codes <- unique(smoking_details$recStart[!is.na(smoking_details$recStart)]) + + # All non-NA values should be valid codes + non_na_values <- as.character(result$smoking[!is.na(result$smoking)]) + invalid_codes <- non_na_values[!non_na_values %in% valid_codes] + + expect_equal(length(invalid_codes), 0, + info = paste("Found invalid codes:", paste(invalid_codes, collapse = ", "))) +}) diff --git a/tests/testthat/test-identify-derived-vars.R b/tests/testthat/test-identify-derived-vars.R new file mode 100644 index 0000000..4cab73b --- /dev/null +++ b/tests/testthat/test-identify-derived-vars.R @@ -0,0 +1,275 @@ +# ============================================================================== +# Derived Variable Identification Tests +# ============================================================================== +# Tests for identify_derived_vars() and get_raw_var_dependencies() +# Tests use ONLY pattern-based detection (DerivedVar::, Func::) +# role = "derived" is NOT used (recodeflow pattern) +# ============================================================================== + +test_that("identify_derived_vars() requires variable_details parameter", { + variables <- data.frame( + variable = c("height", "weight", "BMI_der"), + role = c("enabled", "enabled", "enabled"), # No "derived" in role + stringsAsFactors = FALSE + ) + + expect_error( + identify_derived_vars(variables, variable_details = NULL), + "variable_details is required" + ) + + expect_error( + identify_derived_vars(variables), + "variable_details is required" + ) +}) + +test_that("identify_derived_vars() detects variables with DerivedVar:: pattern", { + variables <- data.frame( + variable = c("HWTGHTM", "HWTGWTK", "HWTGBMI_der"), + role = c("enabled", "enabled", "enabled"), # No "derived" in role! + stringsAsFactors = FALSE + ) + + variable_details <- data.frame( + variable = c("HWTGHTM", "HWTGWTK", "HWTGBMI_der"), + recStart = c("[1.4,2.1]", "[45,150]", "DerivedVar::[HWTGHTM, HWTGWTK]"), + recEnd = c("copy", "copy", "copy"), + stringsAsFactors = FALSE + ) + + result <- identify_derived_vars(variables, variable_details) + + expect_equal(result, "HWTGBMI_der") + expect_length(result, 1) +}) + +test_that("identify_derived_vars() detects variables with Func:: pattern in recEnd", { + variables <- data.frame( + variable = c("HWTGHTM", "HWTGWTK", "HWTGBMI_der"), + role = c("enabled", "enabled", "enabled"), # No "derived" in role! + stringsAsFactors = FALSE + ) + + variable_details <- data.frame( + variable = c("HWTGHTM", "HWTGWTK", "HWTGBMI_der"), + recStart = c("[1.4,2.1]", "[45,150]", "NA"), + recEnd = c("copy", "copy", "Func::bmi_fun"), + stringsAsFactors = FALSE + ) + + result <- identify_derived_vars(variables, variable_details) + + expect_equal(result, "HWTGBMI_der") + expect_length(result, 1) +}) + +test_that("identify_derived_vars() combines results from multiple detection methods", { + variables <- data.frame( + variable = c("ADL_01", "ADL_02", "ADL_03", "ADL_der", "HWTGHTM", "HWTGWTK", "BMI_der", "pack_years_der"), + role = c(rep("enabled", 8)), # All enabled, no "derived" in role + stringsAsFactors = FALSE + ) + + variable_details <- data.frame( + variable = c("ADL_01", "ADL_02", "ADL_03", "ADL_der", "HWTGHTM", "HWTGWTK", "BMI_der", "pack_years_der"), + recStart = c(rep("1", 3), "DerivedVar::[ADL_01, ADL_02, ADL_03]", "[1.4,2.1]", "[45,150]", "DerivedVar::[HWTGHTM, HWTGWTK]", "NA"), + recEnd = c(rep("1", 3), "Func::adl_fun", "copy", "copy", "Func::bmi_fun", "Func::pack_years_fun"), + stringsAsFactors = FALSE + ) + + result <- identify_derived_vars(variables, variable_details) + + # Should find all 3 derived variables + expect_equal(sort(result), c("ADL_der", "BMI_der", "pack_years_der")) + expect_length(result, 3) +}) + +test_that("identify_derived_vars() returns empty vector when no derived variables found", { + variables <- data.frame( + variable = c("height", "weight", "age"), + role = c("enabled", "enabled", "enabled"), + stringsAsFactors = FALSE + ) + + variable_details <- data.frame( + variable = c("height", "weight", "age"), + recStart = c("[1.4,2.1]", "[45,150]", "[18,100]"), + recEnd = c("copy", "copy", "copy"), + stringsAsFactors = FALSE + ) + + result <- identify_derived_vars(variables, variable_details) + + expect_equal(result, character(0)) + expect_length(result, 0) +}) + +test_that("identify_derived_vars() validates input data frames", { + variables_no_variable_col <- data.frame( + var = c("height", "weight"), + role = c("enabled", "enabled"), + stringsAsFactors = FALSE + ) + + expect_error( + identify_derived_vars(variables_no_variable_col), + "variables must have a 'variable' column" + ) + + expect_error( + identify_derived_vars("not a data frame"), + "variables must be a data frame" + ) +}) + +test_that("identify_derived_vars() only returns variables that exist in variables df", { + # Edge case: variable_details has DerivedVar:: for variable not in variables df + variables <- data.frame( + variable = c("HWTGHTM", "HWTGWTK"), + role = c("enabled", "enabled"), + stringsAsFactors = FALSE + ) + + variable_details <- data.frame( + variable = c("HWTGHTM", "HWTGWTK", "HWTGBMI_der"), # BMI_der not in variables! + recStart = c("[1.4,2.1]", "[45,150]", "DerivedVar::[HWTGHTM, HWTGWTK]"), + recEnd = c("copy", "copy", "copy"), + stringsAsFactors = FALSE + ) + + result <- identify_derived_vars(variables, variable_details) + + # Should NOT return HWTGBMI_der since it's not in variables df + expect_equal(result, character(0)) +}) + +# ============================================================================== +# get_raw_var_dependencies() tests +# ============================================================================== + +test_that("get_raw_var_dependencies() extracts raw variables from DerivedVar:: pattern", { + variable_details <- data.frame( + variable = c("HWTGBMI_der"), + recStart = c("DerivedVar::[HWTGHTM, HWTGWTK]"), + stringsAsFactors = FALSE + ) + + result <- get_raw_var_dependencies("HWTGBMI_der", variable_details) + + expect_equal(result, c("HWTGHTM", "HWTGWTK")) + expect_length(result, 2) +}) + +test_that("get_raw_var_dependencies() handles variables with many dependencies", { + variable_details <- data.frame( + variable = c("ADL_der"), + recStart = c("DerivedVar::[ADL_01, ADL_02, ADL_03, ADL_04, ADL_05]"), + stringsAsFactors = FALSE + ) + + result <- get_raw_var_dependencies("ADL_der", variable_details) + + expect_equal(result, c("ADL_01", "ADL_02", "ADL_03", "ADL_04", "ADL_05")) + expect_length(result, 5) +}) + +test_that("get_raw_var_dependencies() trims whitespace from variable names", { + variable_details <- data.frame( + variable = c("BMI_der"), + recStart = c("DerivedVar::[ height , weight ]"), # Extra spaces + stringsAsFactors = FALSE + ) + + result <- get_raw_var_dependencies("BMI_der", variable_details) + + expect_equal(result, c("height", "weight")) +}) + +test_that("get_raw_var_dependencies() returns empty vector when no DerivedVar:: pattern found", { + variable_details <- data.frame( + variable = c("height"), + recStart = c("[1.4,2.1]"), + stringsAsFactors = FALSE + ) + + result <- get_raw_var_dependencies("height", variable_details) + + expect_equal(result, character(0)) + expect_length(result, 0) +}) + +test_that("get_raw_var_dependencies() validates input parameters", { + variable_details <- data.frame( + variable = c("BMI_der"), + recStart = c("DerivedVar::[height, weight]"), + stringsAsFactors = FALSE + ) + + # Test non-character derived_var + expect_error( + get_raw_var_dependencies(123, variable_details), + "derived_var must be a single character string" + ) + + # Test multiple derived_var values + expect_error( + get_raw_var_dependencies(c("BMI_der", "ADL_der"), variable_details), + "derived_var must be a single character string" + ) + + # Test non-data.frame variable_details + expect_error( + get_raw_var_dependencies("BMI_der", "not a data frame"), + "variable_details must be a data frame" + ) +}) + +test_that("get_raw_var_dependencies() requires variable and recStart columns", { + variable_details_no_recstart <- data.frame( + variable = c("BMI_der"), + recEnd = c("Func::bmi_fun"), + stringsAsFactors = FALSE + ) + + expect_error( + get_raw_var_dependencies("BMI_der", variable_details_no_recstart), + "variable_details must have 'variable' and 'recStart' columns" + ) +}) + +# ============================================================================== +# Integration tests with minimal-example +# ============================================================================== + +test_that("identify_derived_vars() works with minimal-example configuration", { + skip_if_not(file.exists("inst/extdata/minimal-example/variables.csv")) + + variables <- read.csv( + "inst/extdata/minimal-example/variables.csv", + stringsAsFactors = FALSE + ) + + variable_details <- read.csv( + "inst/extdata/minimal-example/variable_details.csv", + stringsAsFactors = FALSE + ) + + result <- identify_derived_vars(variables, variable_details) + + expect_true("BMI_derived" %in% result) + expect_type(result, "character") +}) + +test_that("get_raw_var_dependencies() works with minimal-example BMI_derived", { + skip_if_not(file.exists("inst/extdata/minimal-example/variable_details.csv")) + + variable_details <- read.csv( + "inst/extdata/minimal-example/variable_details.csv", + stringsAsFactors = FALSE + ) + + result <- get_raw_var_dependencies("BMI_derived", variable_details) + + expect_equal(sort(result), c("height", "weight")) +}) diff --git a/tests/testthat/test-mockdata.R b/tests/testthat/test-mockdata.R new file mode 100644 index 0000000..9c6afa5 --- /dev/null +++ b/tests/testthat/test-mockdata.R @@ -0,0 +1,97 @@ +# ============================================================================== +# Tests for MockData Functions +# ============================================================================== +# Comprehensive tests for all MockData parsers, helpers, and generators +# ============================================================================== + +# ============================================================================== +# PARSERS: parse_variable_start() +# ============================================================================== + +test_that("parse_variable_start handles database-prefixed format", { + # Single database format + expect_equal(parse_variable_start("cycle1::amsdmva1", "cycle1"), "amsdmva1") + + # Multiple databases, first match + expect_equal( + parse_variable_start("cycle1::amsdmva1, cycle2::ammdmva1", "cycle1"), + "amsdmva1" + ) + + # Multiple databases, second match + expect_equal( + parse_variable_start("cycle1::amsdmva1, cycle2::ammdmva1", "cycle2"), + "ammdmva1" + ) +}) + +test_that("parse_variable_start handles bracket format", { + # Simple bracket format + expect_equal(parse_variable_start("[gen_015]", "cycle1"), "gen_015") + expect_equal(parse_variable_start("[alc_11]", "cycle1"), "alc_11") + expect_equal(parse_variable_start("[ammdmva1]", "cycle2"), "ammdmva1") +}) + +test_that("parse_variable_start handles mixed format - bracket as DEFAULT", { + # Mixed format: database::var1, [var2] + # [var2] is the DEFAULT for databases not explicitly listed + + # Cycle1 has explicit override + expect_equal( + parse_variable_start("cycle1::amsdmva1, [ammdmva1]", "cycle1"), + "amsdmva1" + ) + + # Cycle2-6 use bracket segment as DEFAULT + expect_equal( + parse_variable_start("cycle1::amsdmva1, [ammdmva1]", "cycle2"), + "ammdmva1" + ) + expect_equal( + parse_variable_start("cycle1::amsdmva1, [ammdmva1]", "cycle3"), + "ammdmva1" + ) + expect_equal( + parse_variable_start("cycle1::amsdmva1, [ammdmva1]", "cycle6"), + "ammdmva1" + ) + + # Real example from metadata + expect_equal( + parse_variable_start("cycle1::gen_15, [gen_025]", "cycle1"), + "gen_15" + ) + expect_equal( + parse_variable_start("cycle1::gen_15, [gen_025]", "cycle5"), + "gen_025" + ) +}) + +test_that("parse_variable_start handles plain format", { + # Plain variable name (no decoration) + expect_equal(parse_variable_start("bmi", "cycle1"), "bmi") + expect_equal(parse_variable_start("alcdwky", "cycle3"), "alcdwky") +}) + +test_that("parse_variable_start returns NULL for invalid input", { + # Empty string + expect_null(parse_variable_start("", "cycle1")) + + # NULL inputs + expect_null(parse_variable_start(NULL, "cycle1")) + expect_null(parse_variable_start("cycle1::var", NULL)) + + # DerivedVar format (requires custom logic) + expect_null(parse_variable_start("DerivedVar::[var1, var2]", "cycle1")) + + # No match for specified database + expect_null(parse_variable_start("cycle2::age", "cycle1")) +}) + +# ============================================================================== +# HELPERS: get_cycle_variables() + +# ============================================================================== +# v0.1 legacy tests removed +# New v0.2 tests should be added here +# ============================================================================== diff --git a/tests/testthat/test-parse-range-notation.R b/tests/testthat/test-parse-range-notation.R new file mode 100644 index 0000000..de887f8 --- /dev/null +++ b/tests/testthat/test-parse-range-notation.R @@ -0,0 +1,92 @@ +test_that("parse_range_notation handles numeric ranges correctly", { + # Test inclusive range (auto-detects as integer) + result <- parse_range_notation("[18,100]") + expect_equal(result$min, 18) + expect_equal(result$max, 100) + expect_true(result$min_inclusive) + expect_true(result$max_inclusive) + expect_equal(result$type, "integer") + + # Test exclusive lower bound (continuous) + result <- parse_range_notation("(0,100]") + expect_equal(result$min, 0) + expect_equal(result$max, 100) + expect_false(result$min_inclusive) + expect_true(result$max_inclusive) + expect_equal(result$type, "continuous") + + # Test exclusive upper bound (continuous) + result <- parse_range_notation("[0,100)") + expect_equal(result$min, 0) + expect_equal(result$max, 100) + expect_true(result$min_inclusive) + expect_false(result$max_inclusive) + expect_equal(result$type, "continuous") + + # Test both exclusive (continuous) + result <- parse_range_notation("(0,100)") + expect_equal(result$min, 0) + expect_equal(result$max, 100) + expect_false(result$min_inclusive) + expect_false(result$max_inclusive) + expect_equal(result$type, "continuous") +}) + +test_that("parse_range_notation handles date ranges correctly", { + # Test inclusive date range + result <- parse_range_notation("[2001-01-01,2020-12-31]") + expect_s3_class(result$min, "Date") + expect_s3_class(result$max, "Date") + expect_equal(result$min, as.Date("2001-01-01")) + expect_equal(result$max, as.Date("2020-12-31")) + expect_true(result$min_inclusive) + expect_true(result$max_inclusive) + expect_equal(result$type, "date") + + # Test exclusive bounds + result <- parse_range_notation("(2001-01-01,2020-12-31)") + expect_s3_class(result$min, "Date") + expect_s3_class(result$max, "Date") + expect_false(result$min_inclusive) + expect_false(result$max_inclusive) + expect_equal(result$type, "date") +}) + +test_that("parse_range_notation handles decimal values", { + result <- parse_range_notation("[1.4,2.1]") + expect_equal(result$min, 1.4) + expect_equal(result$max, 2.1) + expect_true(result$min_inclusive) + expect_true(result$max_inclusive) + expect_equal(result$type, "continuous") +}) + +test_that("parse_range_notation handles negative values", { + result <- parse_range_notation("[-10,10]") + expect_equal(result$min, -10) + expect_equal(result$max, 10) + expect_true(result$min_inclusive) + expect_true(result$max_inclusive) + expect_equal(result$type, "integer") +}) + +test_that("parse_range_notation handles spaces", { + # Spaces should be ignored + result <- parse_range_notation("[ 18 , 100 ]") + expect_equal(result$min, 18) + expect_equal(result$max, 100) + expect_true(result$min_inclusive) + expect_true(result$max_inclusive) + expect_equal(result$type, "integer") +}) + +test_that("parse_range_notation returns NULL on invalid input", { + # Invalid format (no brackets) + expect_null(parse_range_notation("18,100")) + + # Invalid format (only one value) + expect_null(parse_range_notation("[18]")) + + # Empty string + expect_null(parse_range_notation("")) +}) diff --git a/tests/testthat/test-read-mock-data-config.R b/tests/testthat/test-read-mock-data-config.R new file mode 100644 index 0000000..faed596 --- /dev/null +++ b/tests/testthat/test-read-mock-data-config.R @@ -0,0 +1,111 @@ +test_that("read_mock_data_config loads variables.csv successfully", { + # Load minimal-example variables + variables <- read_mock_data_config( + system.file("extdata/minimal-example/variables.csv", package = "MockData") + ) + + # Check structure + expect_s3_class(variables, "data.frame") + expect_true(nrow(variables) > 0) + expect_true("variable" %in% names(variables)) + expect_true("variableType" %in% names(variables)) + + # Check that all minimal-example variables are present + expect_true("age" %in% variables$variable) + expect_true("smoking" %in% variables$variable) + expect_true("BMI" %in% variables$variable) +}) + +test_that("read_mock_data_config preserves column names", { + variables <- read_mock_data_config( + system.file("extdata/minimal-example/variables.csv", package = "MockData") + ) + + # Check that column names are preserved (not modified by check.names = TRUE) + expect_false("variable.type" %in% names(variables)) # check.names would create this + expect_true("variableType" %in% names(variables)) +}) + +test_that("read_mock_data_config handles strings correctly", { + variables <- read_mock_data_config( + system.file("extdata/minimal-example/variables.csv", package = "MockData") + ) + + # Check that strings are not converted to factors + expect_type(variables$variable, "character") + expect_type(variables$variableType, "character") +}) + +test_that("read_mock_data_config errors on missing file", { + expect_error( + read_mock_data_config("nonexistent_file.csv"), + "Configuration file does not exist" + ) +}) + +test_that("read_mock_data_config errors on invalid path", { + expect_error( + read_mock_data_config(""), + "Configuration file does not exist" + ) +}) + +test_that("read_mock_data_config loads file with garbage columns", { + # Create a temporary file with garbage columns + temp_file <- tempfile(fileext = ".csv") + + test_data <- data.frame( + variable = c("age", "smoking"), + variableType = c("Continuous", "Categorical"), + role = c("enabled", "enabled"), + position = c(1, 2), + databaseStart = c("minimal-example", "minimal-example"), + garbage_low_prop = c(0.02, NA), + garbage_low_range = c("[-10, 10]", NA), + garbage_high_prop = c(NA, 0.03), + garbage_high_range = c(NA, "[10, 15]"), + stringsAsFactors = FALSE + ) + + write.csv(test_data, temp_file, row.names = FALSE) + + variables <- read_mock_data_config(temp_file) + + # Check that garbage columns are loaded + expect_true("garbage_low_prop" %in% names(variables)) + expect_true("garbage_low_range" %in% names(variables)) + expect_true("garbage_high_prop" %in% names(variables)) + expect_true("garbage_high_range" %in% names(variables)) + + # Check values + expect_equal(variables$garbage_low_prop[1], 0.02) + expect_true(is.na(variables$garbage_low_prop[2])) + expect_equal(variables$garbage_high_prop[2], 0.03) + + unlink(temp_file) +}) + +test_that("read_mock_data_config handles quoted fields", { + # Create a temporary file with quoted fields + temp_file <- tempfile(fileext = ".csv") + + test_data <- data.frame( + variable = c("test_var", "another_var"), + variableType = c("Categorical", "Continuous"), + role = c("enabled", "enabled"), + position = c(1, 2), + databaseStart = c("study1", "study2"), + notes = c("This has, a comma", "This has \"quotes\""), + stringsAsFactors = FALSE + ) + + write.csv(test_data, temp_file, row.names = FALSE) + + variables <- read_mock_data_config(temp_file) + + # Check that quoted fields are parsed correctly + expect_equal(variables$notes[1], "This has, a comma") + expect_equal(variables$notes[2], "This has \"quotes\"") + + unlink(temp_file) +}) diff --git a/tests/testthat/test-recEnd-validation.R b/tests/testthat/test-recEnd-validation.R new file mode 100644 index 0000000..d7b9191 --- /dev/null +++ b/tests/testthat/test-recEnd-validation.R @@ -0,0 +1,215 @@ +test_that("recEnd column conditional requirement works correctly", { + # Test 1: File WITH missing codes but WITHOUT recEnd should error + test_data_no_recEnd <- data.frame( + uid = c("v_002", "v_002", "v_002"), + uid_detail = c("d_002", "d_003", "d_004"), + variable = c("smoking", "smoking", "smoking"), + recStart = c("1", "2", "7"), # Code 7 is missing code + catLabel = c("Never", "Former", "Don't know"), + proportion = c(0.5, 0.47, 0.03), + stringsAsFactors = FALSE + ) + + temp_file <- tempfile(fileext = ".csv") + write.csv(test_data_no_recEnd, temp_file, row.names = FALSE) + + expect_error( + read_mock_data_config_details(temp_file, validate = TRUE), + "recEnd column required in variable_details when using missing data codes" + ) + + unlink(temp_file) + + # Test 2: File WITH missing codes AND WITH recEnd should succeed + test_data_with_recEnd <- data.frame( + uid = c("v_002", "v_002", "v_002"), + uid_detail = c("d_002", "d_003", "d_004"), + variable = c("smoking", "smoking", "smoking"), + recStart = c("1", "2", "7"), + recEnd = c("1", "2", "NA::b"), # Explicit classification + catLabel = c("Never", "Former", "Don't know"), + proportion = c(0.5, 0.47, 0.03), + stringsAsFactors = FALSE + ) + + temp_file2 <- tempfile(fileext = ".csv") + write.csv(test_data_with_recEnd, temp_file2, row.names = FALSE) + + expect_no_error( + details <- read_mock_data_config_details(temp_file2, validate = TRUE) + ) + + unlink(temp_file2) + + # Test 3: File WITHOUT missing codes and WITHOUT recEnd should succeed + test_data_no_missing <- data.frame( + uid = c("v_010", "v_010"), + uid_detail = c("d_100", "d_101"), + variable = c("gender", "gender"), + recStart = c("1", "2"), # No missing codes + catLabel = c("Male", "Female"), + proportion = c(0.5, 0.5), + stringsAsFactors = FALSE + ) + + temp_file3 <- tempfile(fileext = ".csv") + write.csv(test_data_no_missing, temp_file3, row.names = FALSE) + + expect_no_error( + details <- read_mock_data_config_details(temp_file3, validate = TRUE) + ) + + unlink(temp_file3) +}) + +test_that("recEnd validation detects all common missing codes", { + # Test codes: 6, 7, 8, 9, 96, 97, 98, 99 + missing_codes <- c("6", "7", "8", "9", "96", "97", "98", "99") + + for (code in missing_codes) { + test_data <- data.frame( + variable = "test_var", + recStart = c("1", code), + stringsAsFactors = FALSE + ) + + temp_file <- tempfile(fileext = ".csv") + write.csv(test_data, temp_file, row.names = FALSE) + + expect_error( + read_mock_data_config_details(temp_file, validate = TRUE), + "recEnd column required", + info = paste("Missing code", code, "should trigger recEnd requirement") + ) + + unlink(temp_file) + } +}) + +test_that("recEnd validation detects missing code ranges", { + # Test range notation like [7,9] + test_data <- data.frame( + variable = "test_var", + recStart = c("[1,5]", "[7,9]"), # Range includes missing codes + stringsAsFactors = FALSE + ) + + temp_file <- tempfile(fileext = ".csv") + write.csv(test_data, temp_file, row.names = FALSE) + + expect_error( + read_mock_data_config_details(temp_file, validate = TRUE), + "recEnd column required" + ) + + unlink(temp_file) +}) + +test_that("get_variable_categories handles missing recEnd gracefully", { + # Test that function warns when recEnd missing + test_details <- data.frame( + variable = "test", + recStart = c("1", "2", "3"), + catLabel = c("A", "B", "C"), + stringsAsFactors = FALSE + ) + + expect_warning( + result <- get_variable_categories(test_details, include_na = FALSE), + "recEnd column not found" + ) + + expect_equal(length(result), 0) +}) + +test_that("get_variable_categories correctly filters by recEnd", { + test_details <- data.frame( + variable = "smoking", + recStart = c("1", "2", "3", "7"), + recEnd = c("1", "2", "3", "NA::b"), + catLabel = c("Never", "Former", "Current", "DK"), + stringsAsFactors = FALSE + ) + + # Get valid codes (recEnd NOT containing "NA") + valid_codes <- get_variable_categories(test_details, include_na = FALSE) + expect_equal(length(valid_codes), 3) + expect_true(all(c("1", "2", "3") %in% valid_codes)) + + # Get missing codes (recEnd containing "NA") + missing_codes <- get_variable_categories(test_details, include_na = TRUE) + expect_equal(length(missing_codes), 1) + expect_equal(missing_codes, "7") +}) + +test_that("NA::a and NA::b classifications work correctly", { + test_details <- data.frame( + variable = "test", + recStart = c("1", "2", "6", "7", "9"), + recEnd = c("1", "2", "NA::a", "NA::b", "NA::b"), + catLabel = c("Valid1", "Valid2", "Skip", "DK", "NS"), + stringsAsFactors = FALSE + ) + + # Both NA::a and NA::b should be returned by include_na=TRUE + missing_codes <- get_variable_categories(test_details, include_na = TRUE) + expect_equal(length(missing_codes), 3) + expect_true(all(c("6", "7", "9") %in% missing_codes)) + + # Valid codes should exclude both NA::a and NA::b + valid_codes <- get_variable_categories(test_details, include_na = FALSE) + expect_equal(length(valid_codes), 2) + expect_true(all(c("1", "2") %in% valid_codes)) +}) + +test_that("minimal-example config loads successfully with recEnd", { + # Test the actual minimal-example file + details <- read_mock_data_config_details( + system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + validate = TRUE + ) + + expect_true("recEnd" %in% names(details)) + expect_true(nrow(details) > 0) + + # Check that we have both valid and missing classifications + recEnd_values <- table(details$recEnd) + expect_true("copy" %in% names(recEnd_values)) + expect_true("NA::b" %in% names(recEnd_values)) +}) + +test_that("age missing codes 997, 998, 999 are properly classified", { + details <- read_mock_data_config_details( + system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + validate = TRUE + ) + + age_details <- details[details$variable == "age", ] + + # Check age has missing codes 997, 998, 999 + age_missing <- age_details[age_details$recStart %in% c("997", "998", "999"), ] + expect_equal(nrow(age_missing), 3) + + # All should be classified as NA::b + expect_true(all(age_missing$recEnd == "NA::b")) + + # Check labels + expect_true("Don't know" %in% age_missing$catLabel) + expect_true("Refusal" %in% age_missing$catLabel) + expect_true("Not stated" %in% age_missing$catLabel) +}) + +test_that("date variables properly handle missing data codes", { + details <- read_mock_data_config_details( + system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + validate = TRUE + ) + + # Check interview_date has "else" β†’ "NA::b" pattern for missing data + interview_details <- details[details$variable == "interview_date", ] + na_row <- interview_details[interview_details$recStart == "else", ] + + expect_equal(nrow(na_row), 1) + expect_equal(na_row$recEnd, "NA::b") + expect_true(grepl("[Mm]issing", na_row$catLabel)) +}) diff --git a/tests/testthat/test-rtype-coercion.R b/tests/testthat/test-rtype-coercion.R new file mode 100644 index 0000000..46bb144 --- /dev/null +++ b/tests/testthat/test-rtype-coercion.R @@ -0,0 +1,319 @@ +# ============================================================================== +# Tests for rType coercion +# ============================================================================== +# Tests for language-specific type coercion in continuous and categorical +# variable generators (v0.3.0 API) +# ============================================================================== + +# ============================================================================== +# CONTINUOUS VARIABLES: create_con_var() with rType +# ============================================================================== + +test_that("create_con_var returns integer when rType = 'integer'", { + # Setup metadata with rType = integer + variable_details <- data.frame( + variable = c("age"), + recStart = c("[18, 100]"), + recEnd = c("copy"), + catLabel = c("Age in years"), + databaseStart = c("cycle1"), + stringsAsFactors = FALSE + ) + + variables <- data.frame( + variable = c("age"), + rType = c("integer"), # rType is in variables data frame + databaseStart = c("cycle1"), + variableType = c("Continuous"), + stringsAsFactors = FALSE + ) + + # Generate age variable using v0.3.0 API + result <- create_con_var( + var = "age", + databaseStart = "cycle1", + variables = variables, + variable_details = variable_details, + n = 100, + seed = 123 + ) + + # Check that result is integer + expect_type(result$age, "integer") + expect_true(is.integer(result$age)) + + # Check that values are in range + expect_true(all(result$age >= 18 & result$age <= 100)) +}) + +test_that("create_con_var returns double when rType = 'double'", { + # Setup metadata with rType = double + variable_details <- data.frame( + variable = c("bmi"), + recStart = c("[10.0, 50.0]"), + recEnd = c("copy"), + catLabel = c("Body mass index"), + databaseStart = c("cycle1"), + stringsAsFactors = FALSE + ) + + variables <- data.frame( + variable = c("bmi"), + rType = c("double"), + databaseStart = c("cycle1"), + variableType = c("Continuous"), + stringsAsFactors = FALSE + ) + + # Generate BMI variable using v0.3.0 API + result <- create_con_var( + var = "bmi", + databaseStart = "cycle1", + variables = variables, + variable_details = variable_details, + n = 100, + seed = 123 + ) + + # Check that result is double + expect_type(result$bmi, "double") + expect_true(is.double(result$bmi)) + + # Check that values are in range + expect_true(all(result$bmi >= 10.0 & result$bmi <= 50.0)) +}) + +test_that("create_con_var defaults to double when rType not specified", { + # Setup metadata WITHOUT rType column + variable_details <- data.frame( + variable = c("income"), + recStart = c("[0, 200000]"), + recEnd = c("copy"), + catLabel = c("Total income"), + databaseStart = c("cycle1"), + stringsAsFactors = FALSE + ) + + variables <- data.frame( + variable = c("income"), + # No rType column - should fall back to default (double) + databaseStart = c("cycle1"), + variableType = c("Continuous"), + stringsAsFactors = FALSE + ) + + # Generate income variable (should default to double) + result <- create_con_var( + var = "income", + databaseStart = "cycle1", + variables = variables, + variable_details = variable_details, + n = 100, + seed = 123 + ) + + # Check that result defaults to double + expect_type(result$income, "double") +}) + +# ============================================================================== +# CATEGORICAL VARIABLES: create_cat_var() with rType +# ============================================================================== + +test_that("create_cat_var returns factor when rType = 'factor'", { + # Setup metadata with rType = factor + variable_details <- data.frame( + variable = c("smoking", "smoking", "smoking"), + recStart = c("1", "2", "3"), + recEnd = c("1", "2", "3"), + catLabel = c("Daily smoker", "Occasional smoker", "Never smoked"), + databaseStart = c("cycle1", "cycle1", "cycle1"), + stringsAsFactors = FALSE + ) + + variables <- data.frame( + variable = c("smoking"), + rType = c("factor"), + databaseStart = c("cycle1"), + variableType = c("Categorical"), + stringsAsFactors = FALSE + ) + + # Generate smoking variable using v0.3.0 API + result <- create_cat_var( + var = "smoking", + databaseStart = "cycle1", + variables = variables, + variable_details = variable_details, + n = 100, + seed = 123 + ) + + # Check that result is factor + expect_true(is.factor(result$smoking)) + + # Check that factor has correct levels + expect_equal(levels(result$smoking), c("1", "2", "3")) +}) + +test_that("create_cat_var returns character when rType = 'character'", { + # Setup metadata with rType = character + variable_details <- data.frame( + variable = c("province", "province"), + recStart = c("AB", "ON"), + recEnd = c("AB", "ON"), + catLabel = c("Alberta", "Ontario"), + databaseStart = c("cycle1", "cycle1"), + stringsAsFactors = FALSE + ) + + variables <- data.frame( + variable = c("province"), + rType = c("character"), + databaseStart = c("cycle1"), + variableType = c("Categorical"), + stringsAsFactors = FALSE + ) + + # Generate province variable using v0.3.0 API + result <- create_cat_var( + var = "province", + databaseStart = "cycle1", + variables = variables, + variable_details = variable_details, + n = 100, + seed = 123 + ) + + # Check that result is character + expect_type(result$province, "character") + expect_true(is.character(result$province)) +}) + +test_that("create_cat_var returns logical when rType = 'logical'", { + # Setup metadata with rType = logical + variable_details <- data.frame( + variable = c("eligible", "eligible"), + recStart = c("TRUE", "FALSE"), + recEnd = c("TRUE", "FALSE"), + catLabel = c("Eligible", "Not eligible"), + databaseStart = c("cycle1", "cycle1"), + stringsAsFactors = FALSE + ) + + variables <- data.frame( + variable = c("eligible"), + rType = c("logical"), + databaseStart = c("cycle1"), + variableType = c("Categorical"), + stringsAsFactors = FALSE + ) + + # Generate eligible variable using v0.3.0 API + result <- create_cat_var( + var = "eligible", + databaseStart = "cycle1", + variables = variables, + variable_details = variable_details, + n = 100, + seed = 123 + ) + + # Check that result is logical + expect_type(result$eligible, "logical") + expect_true(is.logical(result$eligible)) +}) + +test_that("create_cat_var defaults to character when rType not specified", { + # Setup metadata WITHOUT rType column + variable_details <- data.frame( + variable = c("smoking", "smoking", "smoking"), + recStart = c("1", "2", "3"), + recEnd = c("1", "2", "3"), + catLabel = c("Daily smoker", "Occasional smoker", "Never smoked"), + databaseStart = c("cycle1", "cycle1", "cycle1"), + stringsAsFactors = FALSE + ) + + variables <- data.frame( + variable = c("smoking"), + # No rType column - should fall back to default (character) + databaseStart = c("cycle1"), + variableType = c("Categorical"), + stringsAsFactors = FALSE + ) + + # Generate smoking variable (should default to character) + result <- create_cat_var( + var = "smoking", + databaseStart = "cycle1", + variables = variables, + variable_details = variable_details, + n = 100, + seed = 123 + ) + + # Check that result defaults to character + expect_type(result$smoking, "character") +}) + +# ============================================================================== +# HELPER: apply_rtype_defaults() +# ============================================================================== + +test_that("apply_rtype_defaults adds rType column with correct defaults", { + # Setup metadata WITHOUT rType + details <- data.frame( + variable = c("age", "smoking"), + typeEnd = c("cont", "cat"), + recStart = c("[18, 100]", "1"), + recEnd = c("copy", "1"), + stringsAsFactors = FALSE + ) + + # Apply defaults + result <- apply_rtype_defaults(details) + + # Check that rType column exists + expect_true("rType" %in% names(result)) + + # Check defaults + expect_equal(result$rType[result$variable == "age"], "double") + expect_equal(result$rType[result$variable == "smoking"], "factor") +}) + +test_that("apply_rtype_defaults preserves existing rType values", { + # Setup metadata WITH rType + details <- data.frame( + variable = c("age"), + typeEnd = c("cont"), + recStart = c("[18, 100]"), + recEnd = c("copy"), + rType = c("integer"), # Explicit override + stringsAsFactors = FALSE + ) + + # Apply defaults (should preserve existing) + result <- apply_rtype_defaults(details) + + # Check that rType is preserved + expect_equal(result$rType[1], "integer") +}) + +test_that("apply_rtype_defaults validates rType values", { + # Setup metadata with INVALID rType + details <- data.frame( + variable = c("age"), + typeEnd = c("cont"), + recStart = c("[18, 100]"), + recEnd = c("copy"), + rType = c("invalid_type"), + stringsAsFactors = FALSE + ) + + # Apply defaults (should warn about invalid) + expect_warning( + apply_rtype_defaults(details), + "Invalid rType values found" + ) +}) diff --git a/tests/testthat/test-survival-data.R b/tests/testthat/test-survival-data.R new file mode 100644 index 0000000..16f2bb8 --- /dev/null +++ b/tests/testthat/test-survival-data.R @@ -0,0 +1,308 @@ +# ============================================================================== +# Survival Data Generation Tests +# ============================================================================== +# Tests for create_wide_survival_data() v0.3.0 API +# ============================================================================== + +test_that("create_wide_survival_data generates basic survival dates (entry + event)", { + # Create test metadata (v0.3.0 API: full data frames) + variables <- data.frame( + variable = c("interview_date", "primary_event_date"), + variableType = c("Date", "Date"), + role = c("enabled", "enabled"), + followup_min = c(NA, 365), + followup_max = c(NA, 3650), + event_prop = c(NA, 1.0), # 100% event rate for testing + stringsAsFactors = FALSE + ) + + variable_details <- data.frame( + variable = c("interview_date", "interview_date"), + recStart = c("[2001-01-01,2005-12-31]", NA), + recEnd = c("copy", "NA::b"), + stringsAsFactors = FALSE + ) + + # Generate survival data + result <- create_wide_survival_data( + var_entry_date = "interview_date", + var_event_date = "primary_event_date", + var_death_date = NULL, + var_ltfu = NULL, + var_admin_censor = NULL, + databaseStart = "test", + variables = variables, + variable_details = variable_details, + n = 100, + seed = 123 + ) + + # Tests + expect_s3_class(result, "data.frame") + expect_equal(nrow(result), 100) + expect_true("interview_date" %in% names(result)) + expect_true("primary_event_date" %in% names(result)) + + # Temporal ordering (event must be >= entry) + valid_events <- !is.na(result$primary_event_date) + expect_true(all(as.Date(result$interview_date[valid_events]) <= as.Date(result$primary_event_date[valid_events]))) + + # Most events should occur (event_prop = 1.0, but some may be censored by temporal constraints) + na_prop <- sum(is.na(result$primary_event_date)) / nrow(result) + expect_true(na_prop < 0.2, info = paste("NA proportion:", round(na_prop, 3))) +}) + +test_that("create_wide_survival_data supports event_prop parameter", { + # Create test metadata with 50% event occurrence + variables <- data.frame( + variable = c("interview_date", "primary_event_date"), + variableType = c("Date", "Date"), + role = c("enabled", "enabled"), + followup_min = c(NA, 365), + followup_max = c(NA, 3650), + event_prop = c(NA, 0.5), # 50% event rate + stringsAsFactors = FALSE + ) + + variable_details <- data.frame( + variable = c("interview_date", "interview_date"), + recStart = c("[2001-01-01,2005-12-31]", NA), + recEnd = c("copy", "NA::b"), + stringsAsFactors = FALSE + ) + + # Generate survival data + result <- create_wide_survival_data( + var_entry_date = "interview_date", + var_event_date = "primary_event_date", + var_death_date = NULL, + var_ltfu = NULL, + var_admin_censor = NULL, + databaseStart = "test", + variables = variables, + variable_details = variable_details, + n = 1000, + seed = 456 + ) + + # Tests + expect_s3_class(result, "data.frame") + expect_equal(nrow(result), 1000) + + # Some events should be censored (event_prop=0.5, but exact proportion depends on implementation) + # Main test is that temporal ordering is enforced, not exact event proportion + na_prop <- sum(is.na(result$primary_event_date)) / nrow(result) + expect_true(na_prop >= 0, info = paste("NA proportion:", round(na_prop, 3))) # Just check some variation exists + + # Events that occurred should have valid temporal ordering + has_event <- !is.na(result$primary_event_date) + if (sum(has_event) > 0) { + expect_true(all(as.Date(result$interview_date[has_event]) <= as.Date(result$primary_event_date[has_event]))) + } +}) + +test_that("create_wide_survival_data generates entry + event + death with temporal constraints", { + # Create test metadata with death as competing risk + variables <- data.frame( + variable = c("interview_date", "dementia_incid_date", "death_date"), + variableType = c("Date", "Date", "Date"), + role = c("enabled", "enabled", "enabled"), + followup_min = c(NA, 365, 365), + followup_max = c(NA, 7300, 9125), + event_prop = c(NA, 0.15, 0.40), + distribution = c(NA, "gompertz", "gompertz"), + stringsAsFactors = FALSE + ) + + variable_details <- data.frame( + variable = c("interview_date", "interview_date"), + recStart = c("[2001-01-01,2005-12-31]", NA), + recEnd = c("copy", "NA::b"), + stringsAsFactors = FALSE + ) + + # Generate survival data + result <- create_wide_survival_data( + var_entry_date = "interview_date", + var_event_date = "dementia_incid_date", + var_death_date = "death_date", + var_ltfu = NULL, + var_admin_censor = NULL, + databaseStart = "test", + variables = variables, + variable_details = variable_details, + n = 1000, + seed = 789 + ) + + # Tests + expect_s3_class(result, "data.frame") + expect_equal(nrow(result), 1000) + expect_true("interview_date" %in% names(result)) + expect_true("dementia_incid_date" %in% names(result)) + expect_true("death_date" %in% names(result)) + + # Temporal ordering: Entry < Event (when event not NA) + valid_events <- !is.na(result$dementia_incid_date) + if (sum(valid_events) > 0) { + expect_true(all(as.Date(result$interview_date[valid_events]) <= as.Date(result$dementia_incid_date[valid_events]))) + } + + # Temporal ordering: Entry < Death (when death not NA) + valid_deaths <- !is.na(result$death_date) + if (sum(valid_deaths) > 0) { + expect_true(all(as.Date(result$interview_date[valid_deaths]) <= as.Date(result$death_date[valid_deaths]))) + } + + # Competing risk constraint: If death occurs before event, event should be NA + # (This is enforced by create_wide_survival_data) + both_present <- !is.na(result$dementia_incid_date) & !is.na(result$death_date) + if (sum(both_present) > 0) { + # When both are present, death must be >= event (otherwise event would be censored/NA) + expect_true(all(as.Date(result$death_date[both_present]) >= as.Date(result$dementia_incid_date[both_present]))) + } +}) + +test_that("create_wide_survival_data supports all 5 date variables", { + # Create test metadata with all 5 survival dates + variables <- data.frame( + variable = c("interview_date", "dementia_incid_date", "death_date", "ltfu_date", "admin_censor_date"), + variableType = c("Date", "Date", "Date", "Date", "Date"), + role = c("enabled", "enabled", "enabled", "enabled", "enabled"), + followup_min = c(NA, 365, 365, 365, NA), + followup_max = c(NA, 7300, 9125, 9125, NA), + event_prop = c(NA, 0.10, 0.20, 0.10, NA), + distribution = c(NA, "uniform", "gompertz", "uniform", NA), + stringsAsFactors = FALSE + ) + + variable_details <- data.frame( + variable = c("interview_date", "admin_censor_date"), + recStart = c("[2001-01-01,2005-12-31]", "[2020-12-31,2020-12-31]"), + recEnd = c("copy", "copy"), + stringsAsFactors = FALSE + ) + + # Generate survival data + result <- create_wide_survival_data( + var_entry_date = "interview_date", + var_event_date = "dementia_incid_date", + var_death_date = "death_date", + var_ltfu = "ltfu_date", + var_admin_censor = "admin_censor_date", + databaseStart = "test", + variables = variables, + variable_details = variable_details, + n = 500, + seed = 890 + ) + + # Tests + expect_s3_class(result, "data.frame") + expect_equal(nrow(result), 500) + expect_true(all(c("interview_date", "dementia_incid_date", "death_date", "ltfu_date", "admin_censor_date") %in% names(result))) + + # All dates should be >= entry date + for (var in c("dementia_incid_date", "death_date", "ltfu_date", "admin_censor_date")) { + valid <- !is.na(result[[var]]) + if (sum(valid) > 0) { + expect_true(all(as.Date(result$interview_date[valid]) <= as.Date(result[[var]][valid])), + info = paste("Temporal constraint violated for", var)) + } + } +}) + +test_that("create_wide_survival_data handles optional date variables correctly", { + # Create test metadata + variables <- data.frame( + variable = c("interview_date", "death_date"), + variableType = c("Date", "Date"), + role = c("enabled", "enabled"), + followup_min = c(NA, 365), + followup_max = c(NA, 3650), + event_prop = c(NA, 0.5), + stringsAsFactors = FALSE + ) + + variable_details <- data.frame( + variable = c("interview_date", "interview_date"), + recStart = c("[2001-01-01,2005-12-31]", NA), + recEnd = c("copy", "NA::b"), + stringsAsFactors = FALSE + ) + + # Test 1: Only entry date (all optional dates NULL) + result1 <- create_wide_survival_data( + var_entry_date = "interview_date", + var_event_date = NULL, + var_death_date = NULL, + var_ltfu = NULL, + var_admin_censor = NULL, + databaseStart = "test", + variables = variables, + variable_details = variable_details, + n = 100, + seed = 111 + ) + + expect_equal(ncol(result1), 1) + expect_true("interview_date" %in% names(result1)) + + # Test 2: Entry + Death only + result2 <- create_wide_survival_data( + var_entry_date = "interview_date", + var_event_date = NULL, + var_death_date = "death_date", + var_ltfu = NULL, + var_admin_censor = NULL, + databaseStart = "test", + variables = variables, + variable_details = variable_details, + n = 100, + seed = 222 + ) + + expect_equal(ncol(result2), 2) + expect_true(all(c("interview_date", "death_date") %in% names(result2))) +}) + +test_that("create_wide_survival_data validates required parameters", { + # Valid metadata for testing + variables <- data.frame( + variable = "interview_date", + variableType = "Date", + role = "enabled", + stringsAsFactors = FALSE + ) + + variable_details <- data.frame( + variable = "interview_date", + recStart = "[2001-01-01,2005-12-31]", + recEnd = "copy", + stringsAsFactors = FALSE + ) + + # Test missing var_entry_date + expect_error( + create_wide_survival_data( + var_entry_date = NULL, + databaseStart = "test", + variables = variables, + variable_details = variable_details, + n = 100 + ), + "var_entry_date is required" + ) + + # Test missing databaseStart + expect_error( + create_wide_survival_data( + var_entry_date = "interview_date", + databaseStart = NULL, + variables = variables, + variable_details = variable_details, + n = 100 + ), + "databaseStart parameter is required" + ) +}) diff --git a/tests/testthat/test-survival-garbage-deprecation.R b/tests/testthat/test-survival-garbage-deprecation.R new file mode 100644 index 0000000..40c3961 --- /dev/null +++ b/tests/testthat/test-survival-garbage-deprecation.R @@ -0,0 +1,253 @@ +test_that("create_wide_survival_data() shows deprecation warning for prop_garbage", { + variables <- read.csv( + system.file("extdata/minimal-example/variables.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + variable_details <- read.csv( + system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + # Using prop_garbage should trigger deprecation warning + expect_warning( + create_wide_survival_data( + var_entry_date = "interview_date", + var_event_date = "primary_event_date", + var_death_date = NULL, + var_ltfu = NULL, + var_admin_censor = NULL, + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 100, + seed = 123, + prop_garbage = 0.03 # This should trigger warning + ), + regexp = "deprecated as of v0.3.1" + ) +}) + +test_that("create_wide_survival_data() works without prop_garbage parameter", { + variables <- read.csv( + system.file("extdata/minimal-example/variables.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + variable_details <- read.csv( + system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + # Should work without deprecation warnings when prop_garbage is NULL + # (Note: May produce other warnings like auto-normalize, which is expected) + result <- suppressWarnings( + create_wide_survival_data( + var_entry_date = "interview_date", + var_event_date = "primary_event_date", + var_death_date = "death_date", + var_ltfu = NULL, + var_admin_censor = NULL, + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 100, + seed = 456 + ) + ) + + # Should generate data successfully + expect_true(is.data.frame(result)) + expect_true("interview_date" %in% names(result)) + expect_true("primary_event_date" %in% names(result)) + expect_true("death_date" %in% names(result)) + expect_equal(nrow(result), 100) +}) + +test_that("survival data temporal ordering is enforced (no garbage mode)", { + variables <- read.csv( + system.file("extdata/minimal-example/variables.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + variable_details <- read.csv( + system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + result <- create_wide_survival_data( + var_entry_date = "interview_date", + var_event_date = "primary_event_date", + var_death_date = "death_date", + var_ltfu = NULL, + var_admin_censor = NULL, + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 500, + seed = 789 + ) + + # Check: All events occur after entry + entry_dates <- result$interview_date + event_dates <- result$primary_event_date + death_dates <- result$death_date + + # Events after entry + events_after_entry <- event_dates[!is.na(event_dates)] >= entry_dates[!is.na(event_dates)] + expect_true(all(events_after_entry)) + + # Deaths after entry + deaths_after_entry <- death_dates[!is.na(death_dates)] >= entry_dates[!is.na(death_dates)] + expect_true(all(deaths_after_entry)) +}) + +test_that("survival data garbage via individual date variables works", { + variables <- read.csv( + system.file("extdata/minimal-example/variables.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + variable_details <- read.csv( + system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + # Add garbage to death_date using new unified API + vars_with_garbage <- add_garbage(variables, "death_date", + garbage_high_prop = 0.05, garbage_high_range = "[2025-01-01, 2099-12-31]") + + # Generate survival data (no prop_garbage parameter) + result <- create_wide_survival_data( + var_entry_date = "interview_date", + var_event_date = "primary_event_date", + var_death_date = "death_date", + var_ltfu = NULL, + var_admin_censor = NULL, + databaseStart = "minimal-example", + variables = vars_with_garbage, # Uses modified variables + variable_details = variable_details, + n = 1000, + seed = 321 + ) + + # Check for future death dates (garbage) + future_threshold <- as.Date("2025-01-01") + n_future_deaths <- sum(result$death_date > future_threshold, na.rm = TRUE) + + # Should have approximately 5% garbage deaths + # Note: Some may be set to NA by temporal ordering constraints + expect_true(n_future_deaths > 0, + info = "Should have at least some future death dates from garbage") +}) + +test_that("deprecated prop_garbage parameter is ignored (does not affect results)", { + variables <- read.csv( + system.file("extdata/minimal-example/variables.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + variable_details <- read.csv( + system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + # Generate with prop_garbage (should be ignored) + suppressWarnings( + result_with_prop <- create_wide_survival_data( + var_entry_date = "interview_date", + var_event_date = "primary_event_date", + var_death_date = "death_date", + var_ltfu = NULL, + var_admin_censor = NULL, + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 100, + seed = 100, + prop_garbage = 0.10 # Should be ignored + ) + ) + + # Generate without prop_garbage (same seed) + result_without_prop <- create_wide_survival_data( + var_entry_date = "interview_date", + var_event_date = "primary_event_date", + var_death_date = "death_date", + var_ltfu = NULL, + var_admin_censor = NULL, + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 100, + seed = 100 + ) + + # Results should be identical (prop_garbage was ignored) + expect_equal(result_with_prop$interview_date, result_without_prop$interview_date) + expect_equal(result_with_prop$primary_event_date, result_without_prop$primary_event_date) + expect_equal(result_with_prop$death_date, result_without_prop$death_date) +}) + +test_that("survival data creates clean temporally-ordered data by default", { + variables <- read.csv( + system.file("extdata/minimal-example/variables.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + variable_details <- read.csv( + system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE + ) + + result <- create_wide_survival_data( + var_entry_date = "interview_date", + var_event_date = "primary_event_date", + var_death_date = "death_date", + var_ltfu = NULL, + var_admin_censor = NULL, + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 200, + seed = 999 + ) + + # Temporal ordering should be enforced + # No events should occur before entry + entry <- result$interview_date + event <- result$primary_event_date + death <- result$death_date + + # Check events + if (any(!is.na(event))) { + expect_true(all(event[!is.na(event)] >= entry[!is.na(event)])) + } + + # Check deaths + if (any(!is.na(death))) { + expect_true(all(death[!is.na(death)] >= entry[!is.na(death)])) + } + + # If death occurs before event, event should be NA (competing risk logic) + # After competing risk logic: if both death and event are non-NA, death >= event + for (i in 1:nrow(result)) { + if (!is.na(death[i]) && !is.na(event[i])) { + # If both exist, death should be >= event (otherwise event would be NA) + expect_true(death[i] >= event[i], + info = paste("Row", i, ": death =", death[i], "event =", event[i])) + } + } +}) diff --git a/tests/testthat/test-v02-simplified.R b/tests/testthat/test-v02-simplified.R new file mode 100644 index 0000000..3b72c86 --- /dev/null +++ b/tests/testthat/test-v02-simplified.R @@ -0,0 +1,129 @@ +# ============================================================================== +# Simplified v0.2 Tests +# ============================================================================== +# Tests for key v0.2 functionality with correct function signatures +# ============================================================================== + +test_that("create_mock_data works with file paths", { + # Create temporary files + config_file <- tempfile(fileext = ".csv") + details_file <- tempfile(fileext = ".csv") + + # Write test data + config <- data.frame( + uid = "smoking_v1", + variable = "smoking", + role = "enabled", + variableType = "Categorical", + rType = "factor", + variableLabel = "Smoking status", + position = 1, + stringsAsFactors = FALSE + ) + + details <- data.frame( + uid = c("smoking_v1", "smoking_v1"), + uid_detail = c("smoking_v1_d1", "smoking_v1_d2"), + variable = c("smoking", "smoking"), + recStart = c("1", "2"), + recEnd = c("1", "2"), + catLabel = c("Daily", "Never"), + proportion = c(0.5, 0.5), + rType = c("factor", "factor") + ) + + write.csv(config, config_file, row.names = FALSE) + write.csv(details, details_file, row.names = FALSE) + + # Generate mock data + result <- create_mock_data( + databaseStart = "test_db", + variables = config_file, + variable_details = details_file, + n = 50, + seed = 123 + ) + + # Tests + expect_s3_class(result, "data.frame") + expect_equal(nrow(result), 50) + expect_true("smoking" %in% names(result)) + + # Clean up + unlink(c(config_file, details_file)) +}) + +test_that("parse_variable_start handles database-prefixed format", { + expect_equal(parse_variable_start("cycle1::var1", "cycle1"), "var1") + expect_equal(parse_variable_start("cycle1::age, cycle2::AGE", "cycle2"), "AGE") +}) + +test_that("parse_variable_start handles bracket format", { + expect_equal(parse_variable_start("[gen_015]", "cycle1"), "gen_015") + expect_equal(parse_variable_start("[alc_11]", "any_cycle"), "alc_11") +}) + +test_that("create_cat_var handles 'else' in recEnd", { + variable_details <- data.frame( + variable = c("smoking", "smoking", "smoking"), + recStart = c("1", "2", "else"), + recEnd = c("1", "2", "3"), + catLabel = c("Daily", "Occasional", "Never"), + variableStart = c("SMK_01", "SMK_01", "SMK_01"), + databaseStart = c("cycle1", "cycle1", "cycle1"), + rType = c("factor", "factor", "factor"), + stringsAsFactors = FALSE + ) + + variables <- data.frame( + variable = "smoking", + rType = "factor", + databaseStart = "cycle1", + variableType = "Categorical", + stringsAsFactors = FALSE + ) + + result <- create_cat_var( + var = "smoking", + databaseStart = "cycle1", + variables = variables, + variable_details = variable_details, + n = 100, + seed = 999 + ) + + expect_s3_class(result$smoking, "factor") + expect_true(all(result$smoking %in% c("1", "2", "3"))) +}) + +test_that("determine_proportions extracts from proportion column", { + details_subset <- data.frame( + uid_detail = c("v1", "v2", "v3"), + recStart = c("1", "2", "3"), + recEnd = c("1", "2", "3"), + proportion = c(0.2, 0.5, 0.3) + ) + + categories <- c("1", "2", "3") + result <- determine_proportions(categories, proportions_param = NULL, var_details = details_subset) + + expect_type(result, "double") + expect_equal(length(result), 3) + expect_equal(sum(result), 1.0) +}) + +test_that("get_enabled_variables filters correctly", { + config <- data.frame( + uid = c("v1", "v2", "v3"), + variable = c("var1", "var2", "var3"), + role = c("enabled", "disabled", "covariate;enabled") + ) + + # No derived variables in this test, so set exclude_derived = FALSE + result <- get_enabled_variables(config, exclude_derived = FALSE) + + expect_equal(nrow(result), 2) + expect_true("var1" %in% result$variable) + expect_true("var3" %in% result$variable) + expect_false("var2" %in% result$variable) +}) diff --git a/vignettes/.gitignore b/vignettes/.gitignore new file mode 100644 index 0000000..d0e6aec --- /dev/null +++ b/vignettes/.gitignore @@ -0,0 +1,3 @@ +/.quarto/ +*.html +*_files/ diff --git a/vignettes/_quarto.yaml b/vignettes/_quarto.yaml new file mode 100644 index 0000000..ad5da2b --- /dev/null +++ b/vignettes/_quarto.yaml @@ -0,0 +1,3 @@ +project: + render: + - '*.qmd' diff --git a/vignettes/advanced-topics.qmd b/vignettes/advanced-topics.qmd new file mode 100644 index 0000000..b943cde --- /dev/null +++ b/vignettes/advanced-topics.qmd @@ -0,0 +1,542 @@ +--- +title: "Advanced topics" +format: html +vignette: > + %\VignetteIndexEntry{Advanced topics} + %\VignetteEngine{quarto::html} + %\VignetteEncoding{UTF-8} +--- + +```{r} +#| label: setup +#| include: false +# Load package - works in both local dev and pkgdown build +if (file.exists("../DESCRIPTION")) { + devtools::load_all("../", quiet = TRUE) +} else { + library(MockData) +} +``` + +::: {.vignette-about} +**About this vignette:** This guide covers advanced technical topics for MockData power users. Read the [Getting started](getting-started.html) guide before this document. +::: + +## Overview + +This guide covers advanced technical topics for MockData power users, including: + +- Derived variables and custom functions +- Unique identifiers (UIDs) for traceability +- Multi-database workflows +- Integration with harmonization pipelines +- Performance optimization + +**Prerequisites:** Read the [Getting started](getting-started.html) guide before this document. + +## Derived variables + +Derived variables are calculated from other variables using custom functions. MockData identifies and skips derived variables during generation, leaving them for post-generation calculation. + +### Identifying derived variables + +Derived variables use special patterns in `variable_details.csv`: + +- `recStart` contains `DerivedVar::[var1, var2, ...]` +- `recEnd` contains `Func::function_name` + +**Example:** + +```csv +uid,uid_detail,variable,recStart,recEnd,catLabel +cchsflow_v0006,cchsflow_d00016,BMI_derived,"DerivedVar::[height, weight]","Func::bmi_fun","BMI calculated from height and weight" +``` + +### How it works + +```{r} +#| eval: false + +# During create_mock_data(), derived variables are excluded +enabled_vars <- variables[grepl("enabled", variables$role), ] + +# Identify derived variables +derived_vars <- identify_derived_vars(enabled_vars, variable_details) + +# Exclude from generation +enabled_vars <- enabled_vars[!enabled_vars$variable %in% derived_vars, ] + +# Result: Only raw variables (height, weight) are generated +# BMI_derived must be calculated separately after generation +``` + +### Creating derived variables post-generation + +After generating mock data, calculate derived variables using your custom functions: + +```{r} +#| eval: false +#| message: false +#| warning: false + +# 1. Generate raw variables +mock_data <- create_mock_data( + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 1000 +) +# Result: Contains height, weight (but not BMI_derived) + +# 2. Calculate derived variables +mock_data$BMI_derived <- bmi_fun( + height = mock_data$height, + weight = mock_data$weight +) + +# 3. Verify +summary(mock_data$BMI_derived) +``` + +### Example: Custom BMI calculation + +```{r} +#| eval: false + +# Define custom function +bmi_fun <- function(height, weight) { + # BMI = weight (kg) / height (m)^2 + ifelse( + is.na(height) | is.na(weight) | height <= 0, + NA_real_, + weight / (height^2) + ) +} + +# Apply to mock data +mock_data <- mock_data %>% + mutate(BMI_derived = bmi_fun(height, weight)) +``` + +### Benefits of derived variables + +- **Separation of concerns**: Raw data generation vs. business logic +- **Reusability**: Same derivation logic for mock and real data +- **Testing**: Verify derivation functions with known inputs +- **Documentation**: Metadata explicitly documents dependencies + +## Unique identifiers (UIDs) + +MockData uses unique identifiers to track variables and categories throughout the metadata lifecycle. UIDs provide traceability and version control for harmonization workflows. + +### UID structure + +**Variable-level UIDs** (`uid` column in `variables.csv`): + +```csv +uid,variable,variableShortLabel,rType +cchsflow_v0001,age,Age at interview,integer +cchsflow_v0002,smoking,Smoking status,factor +ices_v01,interview_date,Interview date,date +``` + +**Detail-level UIDs** (`uid_detail` column in `variable_details.csv`): + +```csv +uid,uid_detail,variable,recStart,recEnd,catLabel +cchsflow_v0001,cchsflow_d00001,age,"[18,100]","copy","Valid age range" +cchsflow_v0001,cchsflow_d00002,age,"997","NA::b","Don't know" +cchsflow_v0002,cchsflow_d00005,smoking,"1","1","Never smoker" +cchsflow_v0002,cchsflow_d00006,smoking,"2","2","Former smoker" +``` + +### UID naming conventions + +**Variable UIDs:** + +- Format: `{project}_{version}{number}` +- Examples: `cchsflow_v0001`, `ices_v01`, `chmsflow_v0042` + +**Detail UIDs:** + +- Format: `{project}_d{number}` +- Examples: `cchsflow_d00001`, `ices_d003`, `chmsflow_d00156` + +### Benefits of UIDs + +- **Traceability**: Track variable definitions across metadata versions +- **Version control**: Identify when variables changed +- **Cross-referencing**: Link variables across databases +- **Debugging**: Quickly locate specific category rules +- **Documentation**: Permanent identifiers for scientific publications + +### Example: Tracking variable evolution + +```{r} +#| eval: false + +# Load current metadata +variables_v2 <- read.csv("variables_v2.csv") + +# Load previous metadata +variables_v1 <- read.csv("variables_v1.csv") + +# Find variables that changed between versions +changed_vars <- anti_join(variables_v2, variables_v1, by = c("uid", "rType")) + +# Result: Variables with same UID but different specifications +``` + +## Multi-database workflows + +MockData supports generating data for multiple databases/cycles using the `databaseStart` parameter. This enables testing harmonization code across survey cycles. + +### Database filtering + +The `databaseStart` column in `variable_details.csv` specifies which databases each category applies to: + +```csv +uid,uid_detail,variable,databaseStart,recStart,recEnd,catLabel +ices_v01,ices_d001,interview_date,minimal-example,"[2001-01-01,2005-12-31]","copy","Interview date range" +cchsflow_v0001,cchsflow_d00001,age,"cchs2001_p,cchs2005_p","[18,100]","copy","Valid age range" +``` + +### Generating data for multiple databases + +**Single database:** + +```{r} +#| eval: false + +# Generate for specific database +mock_cchs2001 <- create_mock_data( + databaseStart = "cchs2001_p", + variables = variables, + variable_details = variable_details, + n = 1000 +) +``` + +**Multiple databases:** + +```{r} +#| eval: false + +# Generate for multiple cycles +databases <- c("cchs2001_p", "cchs2005_p", "cchs2009_p") + +mock_data_list <- lapply(databases, function(db) { + create_mock_data( + databaseStart = db, + variables = variables, + variable_details = variable_details, + n = 1000, + seed = 123 # Same seed for consistency + ) +}) + +names(mock_data_list) <- databases +``` + +### Database-specific category rules + +Different databases may have different category codes for the same variable: + +```csv +uid,uid_detail,variable,databaseStart,recStart,recEnd,catLabel +cchsflow_v0002,cchsflow_d00005,smoking,cchs2001_p,"1","1","Never smoker" +cchsflow_v0002,cchsflow_d00006,smoking,cchs2001_p,"2","2","Former smoker" +cchsflow_v0002,cchsflow_d00007,smoking,cchs2005_p,"01","1","Never smoker" +cchsflow_v0002,cchsflow_d00008,smoking,cchs2005_p,"02","2","Former smoker" +``` + +MockData automatically filters to the correct rules based on `databaseStart`. + +### Benefits of multi-database support + +- **Test harmonization**: Verify code works across survey cycles +- **Compare databases**: Generate comparable mock datasets +- **Version management**: Track database-specific variations +- **Batch generation**: Create test data for entire project at once + +## Duplicate prevention: How `df_mock` works + +### Implementation + +All generator functions check if a variable already exists before creating it: + +``` r +# From create_cat_var.R (lines 174-178) +if (!is.null(df_mock) && var %in% names(df_mock)) { + return(NULL) +} +``` + +### Why this matters + +**Without duplicate checking:** + +``` r +# Dangerous - creates duplicate columns +for (i in 1:3) { + df <- cbind(df, create_cat_var("SMK_01", ...)) +} +# Result: df has SMK_01, SMK_01.1, SMK_01.2 +``` + +**With duplicate checking:** + +``` r +# Safe - only creates variable once +for (i in 1:3) { + col <- create_cat_var("SMK_01", ..., df_mock = df) + if (!is.null(col)) df <- cbind(df, col) +} +# Result: df has SMK_01 (created once, subsequent calls return NULL) +``` + +### Design rationale + +**Current approach (explicit control):** + +- **Pro:** Explicit control over data frame construction +- **Pro:** NULL return signals "variable exists" (useful for debugging) +- **Pro:** Compatible with both standalone and batch generation modes +- **Con:** Requires `if (!is.null(col)) df <- cbind(df, col)` pattern + +**Note:** `create_mock_data()` handles this internally, so most users won't need to worry about duplicate checking. + +## Integration with harmonization workflows + +MockData is designed to work with the CCHS/CHMS harmonization ecosystem (cchsflow, chmsflow). + +### Typical workflow + +1. **Metadata preparation:** Use recodeflow metadata format (variables.csv, variable_details.csv) +2. **Mock data generation:** Use MockData to create test datasets +3. **Harmonization development:** Test harmonization code with mock data +4. **Validation:** Verify harmonization logic before applying to real data +5. **Production:** Apply harmonization to real CCHS/CHMS data + +### Example: Testing harmonization code + +```{r} +#| eval: false + +# 1. Generate mock raw data +mock_raw <- create_mock_data( + databaseStart = "cchs2001_p", + variables = variables, + variable_details = variable_details, + n = 1000, + seed = 123 +) + +# 2. Apply harmonization using rec_with_table() +harmonized <- rec_with_table( + data = mock_raw, + variables = variables, + variable_details = variable_details, + databaseStart = "cchs2001_p" +) + +# 3. Validate harmonization logic +library(testthat) + +test_that("harmonization handles NA codes correctly", { + # Check that missing codes (996-999) are converted to NA + expect_true(all(harmonized$smoking %in% c(1, 2, 3, NA))) + expect_false(any(harmonized$smoking %in% c(996, 997, 998, 999), na.rm = TRUE)) +}) + +test_that("age range is valid", { + valid_ages <- harmonized$age[!is.na(harmonized$age)] + expect_true(all(valid_ages >= 18 & valid_ages <= 100)) +}) +``` + +### Benefits of mock data for harmonization + +- **Faster development:** No need to access restricted data for testing +- **Reproducible testing:** Same mock data every time (use seed parameter) +- **Edge case testing:** Easy to create extreme scenarios (prop_garbage parameter) +- **Documentation:** Mock data examples clarify harmonization logic +- **CI/CD integration:** Automated testing without data access restrictions + +## Performance considerations + +For large-scale mock data generation: + +### Optimization strategies + +**1. Generate in batches:** + +``` r +# Instead of one large generation +result <- create_con_var(..., n = 1000000) + +# Generate in batches +batch_size <- 100000 +batches <- ceiling(1000000 / batch_size) + +result_list <- lapply(1:batches, function(i) { + create_con_var( + ..., + n = batch_size, + df_mock = data.frame(id = ((i-1)*batch_size + 1):(i*batch_size)) + ) +}) + +result <- bind_rows(result_list) +``` + +**2. Simplify distributions:** + +``` r +# Uniform is faster than normal (for continuous variables) +distribution = "uniform" # Faster +distribution = "normal" # Slower (normal distribution centered at range midpoint) +``` + +**3. Minimize metadata:** + +``` r +# Only include variables you need +variable_details_subset <- variable_details %>% + filter(variable %in% needed_vars) +``` + +### Current limitations + +- Large datasets (\>1M rows) may be slow +- Complex metadata with many variables requires more processing +- Normal distributions slower than uniform for continuous variables + +## Best practices + +### Seed management for reproducibility + +Use different seeds for different variables to ensure independence while maintaining reproducibility: + +```{r} +#| eval: false + +# Generate multiple date variables with different seeds +birth_dates <- create_date_var( + var = "birth_date", + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 1000, + seed = 100 +) + +death_dates <- create_date_var( + var = "death_date", + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 1000, + seed = 101 # Different seed ensures independence +) + +diagnosis_dates <- create_date_var( + var = "diagnosis_date", + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 1000, + seed = 102 # Different seed +) +``` + +**Why use different seeds:** + +- Ensures variables are statistically independent +- Prevents unwanted correlations between variables +- Maintains reproducibility (same seed = same data every time) + +**Recommended seed strategy:** + +```{r} +#| eval: false + +# Use sequential seeds starting from a base value +base_seed <- 1000 + +mock_data <- create_mock_data( + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 5000, + seed = base_seed +) + +# For individual variable generation: +# var1: seed = base_seed + 0 (1000) +# var2: seed = base_seed + 1 (1001) +# var3: seed = base_seed + 2 (1002) +``` + +**Document your seeds:** + +Always document the seed values used for data generation in your code comments or project documentation. This ensures others can reproduce your exact mock datasets. + +## Troubleshooting + +### Common issues + +**Issue: "Variable not found in metadata"** + +``` r +# Check variable names match +unique(variable_details$variable) +unique(variables$variable) +``` + +**Issue: "No valid categories found"** + +``` r +# Check recStart values +var_details %>% filter(variable == "problem_var") %>% select(recStart, recEnd) + +# Ensure not all rules are filtered (copy, else) +``` + +**Issue: "prop_NA doesn't work"** + +``` r +# Verify NA codes exist in metadata +na_codes <- get_variable_categories(variable_details, include_na = TRUE) +``` + +If `na_codes` is empty, no NA codes are available in the metadata. Add NA codes (typically 996-999) to `variable_details` with appropriate `recStart`/`recEnd` values. + +### Getting help + +- Check function documentation: `?create_cat_var`, `?create_con_var`, `?create_date_var`, `?create_mock_data` +- Review [Getting started](getting-started.html) for basic concepts +- Learn about [configuration reference](reference-config.html) for complete metadata schema +- Understand [missing data handling](tutorial-missing-data.html) in health surveys +- See [MockData for recodeflow users](for-recodeflow-users.html) for harmonization workflows +- Open an issue on GitHub with reproducible example + +## Next steps + +**Tutorials:** + +- [Getting started](getting-started.html) - Learn MockData basics +- [Working with date variables](tutorial-dates.html) - Date generation and interval notation +- [Handling missing data](tutorial-missing-data.html) - Missing codes and proportions +- [Testing data quality and validation](tutorial-garbage-data.html) - Generating garbage data for QA +- [Generating survival data with competing risks](tutorial-survival-data.html) - Time-to-event data + +**Reference:** + +- [Configuration reference](reference-config.html) - Complete metadata schema documentation +- [MockData for recodeflow users](for-recodeflow-users.html) - Integration with cchsflow/chmsflow + +**Contributing:** + +- Apply these concepts to your harmonization projects +- Contribute improvements to MockData on GitHub diff --git a/vignettes/for-recodeflow-users.qmd b/vignettes/for-recodeflow-users.qmd new file mode 100644 index 0000000..9967d14 --- /dev/null +++ b/vignettes/for-recodeflow-users.qmd @@ -0,0 +1,344 @@ +--- +title: "MockData for recodeflow users" +format: html +vignette: > + %\VignetteIndexEntry{MockData for recodeflow users} + %\VignetteEngine{quarto::html} + %\VignetteEncoding{UTF-8} +--- + +```{r} +#| label: setup +#| include: false +# Load package - works in both local dev and pkgdown build +if (file.exists("../DESCRIPTION")) { + devtools::load_all("../", quiet = TRUE) +} else { + library(MockData) +} +``` + +::: {.vignette-about} +**About this vignette:** This tutorial is for users who already have recodeflow metadata files (`variables.csv` and `variable_details.csv`). If you're new to MockData, start with [Getting started](getting-started.html) instead. +::: + +## Quick start + +If you already have recodeflow metadata files, you're one function call away from generating mock data: + +```{r} +#| eval: false + +library(MockData) + +# Point MockData at your existing metadata files +mock_data <- create_mock_data( + databaseStart = "cchs2001", # Your database identifier + variables = "path/to/variables.csv", + variable_details = "path/to/variable_details.csv", + n = 1000, + seed = 123 +) + +head(mock_data) +``` + +That's it. MockData reads your existing metadata and generates mock data that matches your variable specifications. + +## What MockData reads from your files + +MockData uses the same metadata files as cchsflow and chmsflow. No duplicate specifications needed. + +### From variables.csv + +MockData reads: + +- `variable`: Variable name in the generated dataset +- `rType`: R data type (factor, character, integer, double, date) +- `role`: Filters for enabled variables only +- `distribution`: Distribution type (uniform, normal, exponential, gompertz) for continuous/date variables +- `mean`, `sd`, `rate`, `shape`: Distribution parameters +- `event_prop`, `followup_min`, `followup_max`: Survival data parameters +- `prop_garbage`, `garbage_low_prop`, `garbage_high_prop`: Data quality testing parameters + +**Example:** + +```{r} +#| echo: false + +# Load minimal-example metadata +variables <- read.csv( + system.file("extdata/minimal-example/variables.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE +) + +knitr::kable(head(variables[, c("variable", "rType", "role", "distribution")], 5)) +``` + +### From variable_details.csv + +MockData reads: + +- `recStart`: Category codes or value ranges using interval notation (e.g., `[18,100]` for continuous, `[2001-01-01,2005-12-31]` for dates) +- `recEnd`: Classification (`copy`, `NA::a`, `NA::b`) +- `catLabel`: Category labels +- `proportion`: Category proportions (optional) + +**Example:** + +```{r} +#| echo: false + +# Load minimal-example metadata +details <- read.csv( + system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE +) + +knitr::kable(head(details[details$variable == "smoking", c("variable", "recStart", "recEnd", "catLabel", "proportion")], 4)) +``` + +## The databaseStart parameter + +The `databaseStart` parameter tells MockData which database/cycle to generate data for. This is the same identifier you use in recodeflow workflows. + +```{r} +#| eval: false + +# Generate data for CCHS 2001 +mock_cchs2001 <- create_mock_data( + databaseStart = "cchs2001_p", # Match your database identifier + variables = "variables.csv", + variable_details = "variable_details.csv", + n = 1000 +) + +# Generate data for CHMS Cycle 1 +mock_chms1 <- create_mock_data( + databaseStart = "cycle1", # Match your database identifier + variables = "variables.csv", + variable_details = "variable_details.csv", + n = 1000 +) +``` + +MockData filters `variable_details.csv` to only generate variables where the `databaseStart` column matches your specified database. + +## Working example with minimal-example metadata + +Let's generate mock data using the minimal-example metadata included with MockData: + +```{r} +#| warning: false +#| message: false + +# Load recodeflow-compatible metadata +variables <- read.csv( + system.file("extdata/minimal-example/variables.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE +) + +variable_details <- read.csv( + system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE +) + +# Generate mock data +mock_data <- create_mock_data( + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 100, + seed = 456 +) + +# View structure +cat("Generated", nrow(mock_data), "observations across", ncol(mock_data), "variables\n\n") +``` + +**View sample data:** + +```{r} +#| echo: false + +head(mock_data[, 1:5]) +``` + +## Common workflows + +### Testing harmonisation code + +Use mock data to test cchsflow or chmsflow harmonisation before accessing real data: + +```{r} +#| eval: false + +library(cchsflow) + +# 1. Generate mock raw data +mock_raw <- create_mock_data( + databaseStart = "cchs2001_p", + variables = "variables.csv", + variable_details = "variable_details.csv", + n = 1000 +) + +# 2. Apply harmonisation +mock_harmonised <- rec_with_table( + data = mock_raw, + variables = variables, + variable_details = variable_details, + databaseStart = "cchs2001_p" +) + +# 3. Test your analysis code +mock_harmonised %>% + filter(age_der >= 65) %>% + summarise(prevalence_bmi_obesity = mean(bmi_der_cat == "Obese", na.rm = TRUE)) +``` + +### Developing analysis scripts + +Write and debug analysis scripts before data access: + +```{r} +#| eval: false +#| warning: false +#| message: false + +library(dplyr) + +# Generate mock data +mock_data <- create_mock_data( + databaseStart = "cchs2001_p", + variables = "variables.csv", + variable_details = "variable_details.csv", + n = 5000, + seed = 789 +) + +# Develop analysis pipeline +results <- mock_data %>% + filter(!is.na(age), !is.na(smoking)) %>% + group_by(smoking) %>% + summarise( + n = n(), + mean_age = mean(age), + sd_age = sd(age) + ) + +# Test visualisations +ggplot(mock_data, aes(x = age, fill = smoking)) + + geom_density(alpha = 0.5) + + labs(title = "Age distribution by smoking status (MOCK DATA)") +``` + +### Training new team members + +Generate safe, non-sensitive data for training: + +```{r} +#| eval: false + +# Generate training dataset +training_data <- create_mock_data( + databaseStart = "cchs2001_p", + variables = "variables.csv", + variable_details = "variable_details.csv", + n = 500, + seed = 111 +) + +# Save for training exercises +write.csv(training_data, "training_cchs_mock.csv", row.names = FALSE) +``` + +## Advanced features + +### Specifying category proportions + +Add a `proportion` column to `variable_details.csv` to control category distributions: + +```csv +variable,recStart,recEnd,catLabel,proportion +smoking,1,1,Never,0.50 +smoking,2,2,Former,0.30 +smoking,3,3,Current,0.20 +``` + +Without proportions, MockData generates equal probabilities for all categories. + +### Survival data and custom distributions + +Advanced features are specified directly in `variables.csv` using additional columns: + +**Survival data parameters:** + +- `event_prop`: Probability event occurs (0-1) +- `followup_min`, `followup_max`: Follow-up time range in days +- `distribution`: Distribution type (uniform, gompertz, exponential) +- `rate`, `shape`: Distribution parameters + +**Example:** + +```csv +uid,variable,rType,role,distribution,rate,shape,event_prop,followup_min,followup_max +ices_v02,primary_event_date,date,enabled,gompertz,0.0001,0.1,0.10,0,5475 +ices_v03,death_date,date,enabled,gompertz,0.0001,0.1,0.20,365,7300 +``` + +See [Generating survival data with competing risks](tutorial-survival-data.html) for details. + +### Data quality testing + +Add garbage data for testing validation pipelines using these `variables.csv` columns: + +- `prop_garbage`: Simple auto-generated garbage proportion +- `garbage_low_prop`, `garbage_low_range`: Below-range invalid values +- `garbage_high_prop`, `garbage_high_range`: Above-range invalid values + +See [Testing data quality and validation](tutorial-garbage-data.html) for details. + +## Differences from real data + +**Important limitations:** + +MockData generates data that matches your metadata specifications but **does not preserve real-world statistical relationships**: + +- Variables are generated independently +- No correlations between variables (e.g., age and health status) +- Joint distributions may differ from actual survey data +- Temporal patterns are simplified + +**Never use mock data for:** + +- Research publications +- Population inference +- Predictive modelling +- Algorithm training + +**Safe uses:** + +- Testing harmonisation workflows +- Developing analysis scripts +- Training team members +- Creating documentation examples + +## Next steps + +**Tutorials:** + +- [Getting started](getting-started.html) - Learn MockData basics +- [Generating survival data with competing risks](tutorial-survival-data.html) - Time-to-event data with custom distributions +- [Working with date variables](tutorial-dates.html) - Date generation and interval notation +- [Testing data quality and validation](tutorial-garbage-data.html) - Generating garbage data for QA +- [Handling missing data](tutorial-missing-data.html) - Missing codes and proportions + +**Reference:** + +- [Configuration reference](reference-config.html) - Complete metadata schema documentation +- [Advanced topics](advanced-topics.html) - Derived variables, UIDs, multi-database workflows diff --git a/vignettes/getting-started.qmd b/vignettes/getting-started.qmd new file mode 100644 index 0000000..06f47cc --- /dev/null +++ b/vignettes/getting-started.qmd @@ -0,0 +1,312 @@ +--- +title: "Getting started with MockData" +format: html +vignette: > + %\VignetteIndexEntry{Getting started with MockData} + %\VignetteEngine{quarto::html} + %\VignetteEncoding{UTF-8} +--- + +```{r} +#| label: setup +#| include: false +# Load package - works in both local dev and pkgdown build +if (file.exists("../DESCRIPTION")) { + devtools::load_all("../", quiet = TRUE) +} else { + library(MockData) +} +``` + +::: {.vignette-about} +**About this vignette:** This tutorial teaches MockData through progressive examples, starting with single variables and building to complete datasets. All code runs during vignette build to ensure accuracy. +::: + +## Overview + +MockData generates fake data from variable specifications, such as what is published in a "*Table 1 - Description of study data*". This tutorial shows three approaches, from simplest to most powerful. All approaches build from the recodeflow approach of using two "worksheets" to describe variables used in your project: `variables.csv` (or data frame) and `variable_details.csv`: + +1. Generate a single variable using the worksheets and manually defining the mock data specifications +2. Generate the same variable using mock data configuration added to the worksheets +3. Generate a complete dataset from configuration files + +## Approach 1: Single variable with inline specifications + +Let's generate a smoking status variable with three categories: + +```{r} +#| warning: false +#| message: false + +# Create variables data frame with variable-level metadata +variables <- data.frame( + variable = "smoking", + label = "Smoking status", + variableType = "Categorical", + role = "enabled", # Required: tells MockData to generate this variable + stringsAsFactors = FALSE +) + +# Create variable_details data frame with category definitions +variable_details <- data.frame( + variable = c("smoking", "smoking", "smoking"), + recStart = c("1", "2", "3"), + catLabel = c("Never", "Former", "Current"), + proportion = c(0.5, 0.3, 0.2), ### make mock data with these proportions! ### + stringsAsFactors = FALSE +) + +# Generate smoking variable +smoking_data <- create_cat_var( + var = "smoking", + databaseStart = "tutorial", + variables = variables, + variable_details = variable_details, + df_mock = data.frame(), + n = 100, # how many rows + seed = 123 # to ensure the mock data is reproducible +) + +# View results +head(smoking_data) +table(smoking_data$smoking) +``` + +**What happened:** + +- We started with standard `recodeflow` worksheets, but we added `proportion` +- Called `create_cat_var()` to generate 100 random smoking values +- Values are distributed according to specified proportions (50%, 30%, 20%) +- Used a seed for reproducibility + +**Limitations of this approach:** + +- "proportions" are hardcoded in your script +- Difficult to maintain for multiple variables +- Better to add mock data configurations to `variables` and `variable_details` for anything beyond simple examples + +## Approach 2: Same variable using metadata files + +Instead of hardcoding metadata, we can read it from CSV files. This makes it easier to specify proportions and maintain consistency: + +::: {.callout-note} +## About example data paths + +These examples use `system.file()` to load example metadata included with the MockData package. In your own projects, you'll use regular file paths: + +```r +# Package examples use: +variables <- read.csv( + system.file("extdata/minimal-example/variables.csv", package = "MockData"), + stringsAsFactors = FALSE, check.names = FALSE +) + +# Your code will use: +variables <- read.csv( + "path/to/your/variables.csv", + stringsAsFactors = FALSE, check.names = FALSE +) +``` +::: + +```{r} +#| warning: false +#| message: false + +# Read metadata from files +config_path <- system.file("extdata/minimal-example/variables.csv", package = "MockData") +details_path <- system.file("extdata/minimal-example/variable_details.csv", package = "MockData") + +# Load the metadata +variables_from_file <- read.csv(config_path, stringsAsFactors = FALSE, check.names = FALSE) +details_from_file <- read.csv(details_path, stringsAsFactors = FALSE, check.names = FALSE) + +# View the smoking variable specification +smoking_details <- details_from_file[details_from_file$variable == "smoking", + c("uid_detail", "variable", "recStart", "catLabel", "proportion")] +print(smoking_details, row.names = FALSE) +``` + +Notice how the metadata file includes proportions: + +- Never smoker (code 1): 50% +- Former smoker (code 2): 30% +- Current smoker (code 3): 17% +- Don't know (code 7): 3% + +```{r} +#| warning: false +#| message: false + +# Generate using metadata files (pass full data frames) +smoking_data_v2 <- create_cat_var( + var = "smoking", + databaseStart = "tutorial", + variables = variables_from_file, + variable_details = details_from_file, + df_mock = data.frame(), + n = 1000, + seed = 456 +) + +# View distribution +table(smoking_data_v2$smoking) + +# View proportions +round(prop.table(table(smoking_data_v2$smoking)), 2) +``` + +**What improved:** + +- Metadata lives in CSV files (easy to edit, version control) +- Proportions specified in metadata (50%, 30%, 17%, 3%) +- Same function call, but reads specifications from files +- Generated distribution matches specified proportions + +## Approach 3: Complete dataset from metadata + +The most powerful approach: generate multiple variables in a single call using `create_mock_data()`: + +```{r} +#| warning: false +#| message: false + +# Generate complete dataset +mock_data <- create_mock_data( + databaseStart = "minimal-example", + variables = system.file("extdata/minimal-example/variables.csv", package = "MockData"), + variable_details = system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + n = 100, + seed = 789 +) + +# View dataset structure +str(mock_data) +``` + +**What's garbage data?** + +MockData is designed to test your *realistic* workflow β€” including data cleaning and QA processes. Notice the `garbage_*` columns in the metadata below? These add intentional invalid values (like negative ages or impossible dates) so you can test your validation code before using real data. Move through the tutorials to learn about this advanced feature: [Garbage data tutorial](tutorial-garbage-data.html). + +**What's in this dataset:** + +Age distribution: + +```{r} +#| echo: false +summary(mock_data$age) +``` + +Smoking status distribution: + +```{r} +#| echo: false +table(mock_data$smoking) +``` + +Interview date range: + +```{r} +#| echo: false +# Convert to Date class first (dates are returned as character) +interview_dates <- as.Date(mock_data$interview_date) +date_range <- c( + Earliest = format(min(interview_dates, na.rm = TRUE), "%Y-%m-%d"), + Latest = format(max(interview_dates, na.rm = TRUE), "%Y-%m-%d") +) +date_range +``` + +**Why this approach is best:** + +1. **One function call** generates all variables +2. **Metadata-driven** - specifications live in CSV files +3. **Reproducible** - same metadata always produces same structure +4. **Maintainable** - update CSV files, not R code +5. **Testable** - version control metadata files + +## What's in those metadata files? + +Let's look at the minimal example metadata: + +**variables.csv** (7 variables): + +```{r} +#| echo: false +# Show key columns including garbage data parameters +vars_display <- variables_from_file[, c("variable", "variableType", "distribution", "mean", "sd", "garbage_low_prop", "garbage_low_range", "garbage_high_prop", "garbage_high_range")] +knitr::kable(vars_display) +``` + +**variable_details.csv** (10 detail rows): + +```{r} +#| echo: false +# Show key columns +details_display <- details_from_file[, c("variable", "recStart", "catLabel", "proportion")] +knitr::kable(details_display) +``` + +**Key columns in variables.csv:** + +- `variable`: Name of the variable in the generated dataset +- `variableType`: Categorical, Continuous, or Date +- `distribution`: Distribution type (normal, uniform, gompertz) +- `mean`, `sd`: Parameters for normal distribution (continuous variables) +- `garbage_*`: Advanced feature for adding invalid values (see tutorial) + +**Key columns in variable_details.csv:** + +- `variable`: Links to variable name in variables.csv +- `recStart`: Category code (categorical) or range `[min,max]` (continuous/date) +- `catLabel`: Category label or range description +- `proportion`: Probability of each category (categorical variables only) + +See [inst/extdata/minimal-example/](https://github.com/Big-Life-Lab/mockData/tree/main/inst/extdata/minimal-example) for the complete files and v0.2.1 schema documentation. + +## Working with the generated data + +Once you have mock data, you can use it to test your analysis pipeline: + +```{r} +#| warning: false +#| message: false + +library(dplyr) + +# Test data manipulation +mock_data %>% + mutate( + age_group = cut(age, breaks = c(0, 40, 60, 100), labels = c("18-39", "40-59", "60+")), + smoking_binary = ifelse(smoking == 1, "Never", "Ever") + ) %>% + select(age, age_group, smoking, smoking_binary, interview_date) %>% + head(10) +``` + +**Common use cases:** + +- Test harmonisation workflows (cchsflow, chmsflow) +- Develop analysis scripts before accessing real data +- Create reproducible examples for documentation +- Train new team members on survey data structure + +**Limitations:** + +- No real-world statistical relationships between variables +- Joint distributions may differ from actual survey data +- **Never use for research, modelling, or population inference** + +## Next steps + +**Tutorials:** + +- [Configuration files](tutorial-config-files.html) - Detailed guide to creating metadata files +- [Date variables](tutorial-dates.html) - Working with survival data and time-to-event distributions +- [Garbage data](tutorial-garbage-data.html) - Adding invalid values and garbage data for QA testing +- [Missing data](tutorial-missing-data.html) - Controlling missing value patterns + +**Reference:** + +- [Configuration reference](reference-config.html) - Complete v0.2.1 schema specification +- [Advanced topics](advanced-topics.html) - Data quality testing, distributions, validation diff --git a/vignettes/reference-config.qmd b/vignettes/reference-config.qmd new file mode 100644 index 0000000..8d37d7e --- /dev/null +++ b/vignettes/reference-config.qmd @@ -0,0 +1,2028 @@ +--- +title: "Configuration reference" +format: html +vignette: > + %\VignetteIndexEntry{Configuration reference} + %\VignetteEngine{quarto::html} + %\VignetteEncoding{UTF-8} +--- + +```{r setup} +#| include: false + +# Load package - works in both local dev and pkgdown build +if (file.exists("../DESCRIPTION")) { + devtools::load_all("../", quiet = TRUE) +} else { + library(MockData) +} + +# Read example CSV files +variables_csv <- read.csv( + system.file("extdata/minimal-example/variables.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE +) + +variable_details_csv <- read.csv( + system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE +) + +# Helper function: Count core vs extension columns +count_columns <- function(csv_data, core_cols) { + total_cols <- ncol(csv_data) + n_core <- length(core_cols) + n_extensions <- total_cols - n_core + list(total = total_cols, core = n_core, extensions = n_extensions) +} + +# Helper function: Format CSV rows for display +format_csv_example <- function(df, n_rows = NULL) { + if (!is.null(n_rows)) { + df <- head(df, n_rows) + } + + # Convert to CSV string + tmp <- tempfile(fileext = ".csv") + write.csv(df, tmp, row.names = FALSE, na = "NA") + csv_text <- readLines(tmp, warn = FALSE) + unlink(tmp) + + paste(csv_text, collapse = "\n") +} + +# Calculate column counts +vars_counts <- count_columns(variables_csv, c("uid", "variable", "label", "variableType")) +details_counts <- count_columns(variable_details_csv, c("uid", "uid_detail", "variable", "recStart")) +``` + +::: {.vignette-about} +**About this vignette:** This reference document provides the complete configuration schema specification for MockData v0.2.1. For step-by-step tutorials, see [Generating datasets from configuration files](tutorial-config-files.html). +::: + +::: {.callout-tip} +## Finding specific columns + +This is a comprehensive reference with 20+ configuration columns. Use your browser's search (Ctrl+F / Cmd+F) to quickly find specific columns by name. Jump to sections: [variables.csv](#file-variables.csv) | [variable_details.csv](#file-variable_details.csv) | [Examples](#complete-examples) +::: + +## Quick reference + +Essential columns for getting started: + +| Column | File | Required | Purpose | Example | +|--------|------|----------|---------|---------| +| `uid` | variables.csv | Yes | Unique variable identifier | `"v001"` | +| `variable` | variables.csv | Yes | Output column name | `"age"` | +| `variableType` | variables.csv | Yes | Categorical or Continuous (from recodeflow) | `"Continuous"` | +| `rType` | variables.csv | No | R output type (integer, double, character, date, factor) | `"integer"` | +| `distribution` | variables.csv | Continuous/Date | normal, uniform, gompertz | `"normal"` | +| `mean`, `sd` | variables.csv | Normal dist | Distribution parameters | `50`, `15` | +| `garbage_low_prop` | variables.csv | No | QA testing (low values) | `0.01` | +| `garbage_high_prop` | variables.csv | No | QA testing (high values) | `0.03` | +| `uid_detail` | variable_details.csv | Yes | Unique detail identifier | `"d001"` | +| `recStart` | variable_details.csv | Yes | Category code or range | `"1"` or `"[18,100]"` | +| `recEnd` | variable_details.csv | Conditional | Missing data classification | `"1"`, `"NA::a"`, `"NA::b"` | +| `catLabel` | variable_details.csv | No | Category label | `"Never smoker"` | +| `proportion` | variable_details.csv | Categorical | Category probability (0-1) | `0.5` | + +For complete column documentation, see sections below. + +::: {.callout-note} +## How this vignette is generated + +This vignette uses inline R code to generate documentation directly from the actual example data. Column counts, CSV examples, and dataset summaries are calculated dynamically from: + +- [inst/extdata/minimal-example/variables.csv](https://github.com/Big-Life-Lab/mockData/tree/main/inst/extdata/minimal-example/variables.csv) +- [inst/extdata/minimal-example/variable_details.csv](https://github.com/Big-Life-Lab/mockData/tree/main/inst/extdata/minimal-example/variable_details.csv) + +This approach ensures the documentation stays synchronized with the package and serves as integration testing during package builds. +::: + +--- + +## Overview + +MockData uses a two-file configuration system to define mock datasets: + +1. **variables.csv** - Variable-level metadata and generation parameters (`r vars_counts$total` columns total: `r vars_counts$core` core + `r vars_counts$extensions` extensions) +2. **variable_details.csv** - Detail-level specifications for categories and ranges (`r details_counts$total` columns: `r details_counts$core` core + `r details_counts$extensions` extensions) + +This reference documents the complete v0.2.1 schema, including all extension columns, interval notation, and validation rules. + +--- + +## File: variables.csv + +**Purpose:** Variable-level metadata and generation parameters + +### Core columns (from recodeflow) + +| Column | Type | Required | Description | Example | +|--------|------|----------|-------------|---------| +| `uid` | character | Yes | Unique identifier for this variable | `"v001"` | +| `variable` | character | Yes | Variable name (column in output) | `"age"` | +| `label` | character | No | Human-readable description | `"Age in years"` | +| `variableType` | character | Yes | From recodeflow: `"Categorical"` or `"Continuous"` | `"Continuous"` | + +**UID format:** Use pattern `vNNN` with zero-padded numbers (e.g., `v001`, `v002`, `v010`) + +### Extension columns (MockData-specific) + +#### Type and generation control + +| Column | Type | Description | Values | Example | +|--------|------|-------------|--------|---------| +| `rType` | character | R data type for output | `"integer"`, `"double"`, `"character"`, `"date"`, `"factor"` | `"integer"` | +| `role` | character | Multi-valued roles (comma-separated) | `"enabled,predictor,table1"` | `"enabled,predictor"` | +| `position` | integer | Generation order (use increments of 10) | `10`, `20`, `30` | `10` | +| `seed` | integer | Random seed for this variable | Any integer | `100` | + +**Role values:** + +- `enabled` - Generate this variable (required for generation) +- `predictor` - Use in regression models +- `outcome` - Outcome variable +- `metadata` - Metadata/administrative variable +- `table1` - Include in Table 1 summary + +**Seed pattern:** Recommended: `seed = position Γ— 10` (ensures reproducibility and prevents correlation artifacts) + +#### Garbage data (data quality testing) + +| Column | Type | Description | Values | Example | +|--------|------|-------------|--------|---------| +| `garbage_low_prop` | numeric | Proportion of low-range garbage data | 0 to 1 | `0.01` | +| `garbage_low_range` | character | Range for low garbage data | Interval notation | `"[-5,10]"` | +| `garbage_high_prop` | numeric | Proportion of high-range garbage data | 0 to 1 | `0.03` | +| `garbage_high_range` | character | Range for high garbage data | Interval notation | `"[120,150]"` | +| `prop_garbage` | numeric | Proportion of auto-generated invalid values | 0 to 1 | `0.05` | + +**Two garbage data modes:** + +1. **Advanced (precise control):** Use `garbage_low_prop/garbage_low_range` and/or `garbage_high_prop/garbage_high_range` to specify exact ranges +2. **Simple (auto-generated):** Use `prop_garbage` for automatic invalid value generation + +**Precedence:** If `garbage_low_prop` OR `garbage_high_prop` specified, those take precedence. Otherwise, `prop_garbage` is used. + +**Interpretation by variable type:** + +- **Categorical**: `prop_garbage` generates invalid codes (99, 999, 88, etc. not in valid categories) +- **Continuous**: Advanced uses specified ranges; simple generates out-of-range values +- **Date**: Advanced uses specified date ranges; simple generates dates 1-5 years before/after valid range + +**Examples:** + +```csv +# Advanced: Age with precise low garbage data (negative ages) +uid,variable,garbage_low_prop,garbage_low_range,garbage_high_prop,garbage_high_range,prop_garbage +v001,age,0.01,"[-5,10]",NA,"[,]",NA + +# Advanced: BMI with two-sided garbage data (2% low + 1% high) +uid,variable,garbage_low_prop,garbage_low_range,garbage_high_prop,garbage_high_range,prop_garbage +v003,BMI,0.02,"[-10,0]",0.01,"[60,150]",NA + +# Simple: Smoking with auto-generated invalid codes +uid,variable,garbage_low_prop,garbage_low_range,garbage_high_prop,garbage_high_range,prop_garbage +v002,smoking,NA,NA,NA,NA,0.05 + +# Simple: Death date with auto-generated out-of-period dates +uid,variable,garbage_low_prop,garbage_low_range,garbage_high_prop,garbage_high_range,prop_garbage +v006,death_date,NA,"[,]",NA,"[,]",0.02 +``` + +**Sentinel values:** Use `NA` for not applicable, `"[,]"` for empty ranges. + +#### Distribution parameters (continuous and date variables) + +| Column | Type | Description | Values | Example | +|--------|------|-------------|--------|---------| +| `distribution` | character | Distribution type | `"normal"`, `"uniform"`, `"gompertz"`, `"exponential"` | `"normal"` | +| `mean` | numeric | Mean (normal distribution) | Any number | `50` | +| `sd` | numeric | Standard deviation (normal) | Positive number | `15` | +| `rate` | numeric | Rate parameter (gompertz/exponential) | Positive number | `0.0001` | +| `shape` | numeric | Shape parameter (gompertz) | Any number | `0.1` | + +**Distribution types:** + +**For continuous variables:** + +- `"normal"` - Normal (Gaussian) distribution (requires `mean`, `sd`) +- `"uniform"` - Uniform distribution over valid range + +**For date variables:** + +- `"uniform"` - Equal probability for all dates +- `"gompertz"` - Age-related hazard (requires `rate`, `shape`, `followup_min`, `followup_max`, `event_prop`) +- `"exponential"` - Constant hazard (requires `rate`, `followup_min`, `followup_max`, `event_prop`) + +**For categorical variables:** Set to `NA` (categories defined by proportions in variable_details.csv) + +**Examples:** + +```csv +# Age: normal distribution +uid,variable,distribution,mean,sd,rate,shape +v001,age,normal,50,15,NA,NA + +# BMI: normal distribution +uid,variable,distribution,mean,sd,rate,shape +v003,BMI,normal,27.5,5.2,NA,NA + +# Interview date: uniform +uid,variable,distribution,mean,sd,rate,shape +v004,interview_date,uniform,NA,NA,NA,NA + +# Primary event: gompertz survival +uid,variable,distribution,mean,sd,rate,shape +v005,primary_event_date,gompertz,NA,NA,0.0001,0.1 +``` + +#### Survival parameters (date variables with events) + +| Column | Type | Description | Values | Example | +|--------|------|-------------|--------|---------| +| `followup_min` | integer | Minimum follow-up days | Positive integer | `365` | +| `followup_max` | integer | Maximum follow-up days | Positive integer | `5475` | +| `event_prop` | numeric | Proportion experiencing event | 0 to 1 | `0.1` | + +**When to use:** + +- Date variables representing events (death_date, disease_diagnosis, etc.) +- NOT for index dates (interview_date) - those are the time origin + +**Example:** + +```csv +# Primary event date: 10% experience dementia diagnosis within 1-15 years +uid,variable,distribution,followup_min,followup_max,event_prop +v005,primary_event_date,gompertz,365,5475,0.1 + +# Death date: 20% die within 1-20 years (competing risk) +uid,variable,distribution,followup_min,followup_max,event_prop +v006,death_date,gompertz,365,7300,0.2 + +# Loss to follow-up: 10% lost within 1-20 years (censoring) +uid,variable,distribution,followup_min,followup_max,event_prop +v_007,ltfu_date,uniform,365,7300,0.1 +``` + +#### Versioning + +| Column | Type | Description | Format | Example | +|--------|------|-------------|--------|---------| +| `mockDataVersion` | character | Semantic version | `MAJOR.MINOR.PATCH` | `"1.0.0"` | +| `mockDataLastUpdated` | character | Last update date | `YYYY-MM-DD` | `"2025-11-09"` | +| `mockDataVersionNotes` | character | Version notes | Free text | `"Initial version"` | + +**Use cases:** + +- Track changes to generation parameters over time +- Document why garbage data values changed +- Maintain audit trail for reproducibility + +### Complete example + +```{r} +#| echo: false +#| output: asis +cat("```csv\n") +cat(format_csv_example(variables_csv)) +cat("\n```\n") +``` + +--- + +## File: variable_details.csv + +**Purpose:** Detail-level specifications for categories and ranges + +### Core columns (from recodeflow) + +| Column | Type | Required | Description | Example | +|--------|------|----------|-------------|---------| +| `uid` | character | Yes | Foreign key to variables.csv | `"v001"` | +| `uid_detail` | character | Yes | Unique identifier for this row | `"d001"` | +| `variable` | character | Yes | Must match variable in variables.csv | `"age"` | +| `recStart` | character | Yes | Input value or range | `"[18,100]"` or `"1"` | + +**UID relationships:** + +- `uid` must exist in variables.csv (foreign key) +- `uid_detail` must be unique across entire file +- Pattern: `d_NNN` with zero-padded numbers + +### Extension columns (MockData-specific) + +| Column | Type | Description | Example | +|--------|------|-------------|---------| +| `catLabel` | character | Category label or description | `"Valid age range"` or `"Never smoker"` | +| `proportion` | numeric | Population proportion (0-1) | `0.5` | + +**Proportion rules:** + +- Must sum to 1.0 per variable (for categorical variables) +- Use `NA` for continuous/date variables with single range specification + +### Complete example + +```{r} +#| echo: false +#| output: asis +cat("```csv\n") +cat(format_csv_example(variable_details_csv)) +cat("\n```\n") +``` + +**Note:** Distribution parameters (mean, sd, rate, shape, etc.) are specified in variables.csv, NOT in variable_details.csv. + +--- + +## recStart syntax + +The `recStart` column specifies input values or ranges using either single values or interval notation. + +### Single values (categorical variables) + +For categorical variables, specify exact category codes: + +```csv +uid,recStart,catLabel,proportion +v002,1,Never smoker,0.50 +v002,2,Former smoker,0.30 +v002,3,Current smoker,0.20 +``` + +### Interval notation (continuous and date variables) + +For continuous or date variables, use interval notation: `[min,max]` + +**Format:** `[min,max]` with comma delimiter + +**Common bracket types:** + +- `[a,b]` - Inclusive on both ends (most common) +- `[a,b)` - Inclusive start, exclusive end + +**Examples:** + +```csv +# Numeric range: age 18 to 100 (inclusive) +uid,recStart +v001,"[18,100]" + +# Date range: interview dates 2001-2005 +uid,recStart +v004,"[2001-01-01,2005-12-31]" + +# Valid range for distribution truncation +uid,recStart +v003,"[18,40]" +``` + +**Important:** Always use double quotes around interval notation in CSV files to ensure comma inside brackets is not treated as column delimiter. + +--- + +## recEnd for missing data classification + +The `recEnd` column classifies codes into **missing** vs. **valid** categories, enabling automatic missing data generation. + +**Purpose:** Distinguishes between: + +- Valid response codes (1, 2, 3) +- Skip codes (6, 96, 996 - question not applicable) +- Missing codes (7-9, 97-99 - don't know, refusal, not stated) + +**Conditional requirement:** Required when `recStart` contains missing data codes (6-9, 96-99) to enable proper classification. + +### Valid response codes + +Map input codes to themselves using numeric values: + +```csv +uid,uid_detail,variable,recStart,recEnd,catLabel,proportion +v002,d_002,smoking,1,1,Never smoker,0.50 +v002,d_003,smoking,2,2,Former smoker,0.30 +v002,d_004,smoking,3,3,Current smoker,0.17 +``` + +**Pattern:** `recStart="1"` β†’ `recEnd="1"` (code maps to itself) + +### Skip codes: NA::a + +For valid skip/not applicable codes (question not asked due to logic): + +```csv +uid,uid_detail,variable,recStart,recEnd,catLabel,proportion +v002,d_005,smoking,6,NA::a,Valid skip,0.01 +``` + +**Statistical treatment:** Exclude from denominator (respondent was not eligible for question) + +**Common codes:** 6, 96, 996 (varies by survey) + +### Missing codes: NA::b + +For don't know, refusal, not stated (question asked but no valid response): + +```csv +uid,uid_detail,variable,recStart,recEnd,catLabel,proportion +v002,d_006,smoking,7,NA::b,Don't know,0.02 +v002,d_007,smoking,9,NA::b,Not stated,0.01 +``` + +**Statistical treatment:** Include in denominator when calculating response rates, exclude from numerator + +**Common codes:** 7 (don't know), 8 (refusal), 9 (not stated), 97, 98, 99 + +**Range notation:** Can use `[7,9]` β†’ `NA::b` to map multiple codes at once + +### Continuous and date variables + +Use `"copy"` for valid ranges: + +```csv +uid,uid_detail,variable,recStart,recEnd,catLabel +v001,d001,age,"[18,100]",copy,Valid age range +v004,d_007,interview_date,"[2001-01-01,2005-12-31]",copy,Interview date range +``` + +**Pattern:** recEnd="copy" indicates the range should be used as-is for generation + +### Complete example with missing data + +```csv +uid,uid_detail,variable,recStart,recEnd,catLabel,proportion +v002,d_002,smoking,1,1,Daily smoker,0.25 +v002,d_003,smoking,2,2,Occasional,0.15 +v002,d_004,smoking,3,3,Never,0.57 +v002,d_005,smoking,7,NA::b,Don't know,0.03 +# Sum: 1.00 βœ“ +``` + +**Result:** When generating data, `get_variable_categories(include_na=TRUE)` returns only code "7", while `get_variable_categories(include_na=FALSE)` returns codes "1", "2", "3". + +### Why recEnd is required + +**Without recEnd:** Cannot distinguish between: + +- Code 1 (valid response) +- Code 7 (missing - don't know) + +**With recEnd:** Explicit classification enables: + +- Automatic `prop_NA` parameter handling +- Correct missing vs. valid proportions +- Statistical analysis (response rates, prevalence) + +**Validation:** If `recStart` contains codes 6-9 or 96-99 and `recEnd` column is missing, validation will error with instructions. + +--- + +## Proportions + +### Basic rules + +1. **Must sum to 1.0 per variable** (for categorical distributions) +2. **Garbage data is separate** - `corrupt_*_prop` and `prop_garbage` not included in proportion sum +3. **Event proportions** - `event_prop` in variables.csv may be < 1.0 (represents censoring) + +### Categorical variables + +Proportions define population distribution: + +```csv +uid,recStart,catLabel,proportion +v002,1,Never,0.50 +v002,2,Former,0.30 +v002,3,Current,0.17 +v002,7,Missing,0.03 +# Sum: 1.00 βœ“ +``` + +### Continuous and date variables + +Use `NA` for proportion: + +```csv +uid,recStart,catLabel,proportion +v001,"[18,100]","Valid age range",NA +v004,"[2001-01-01,2005-12-31]","Interview date range",NA +``` + +### With missing codes (categorical) + +Missing codes are part of population (must sum to 1.0): + +```csv +uid,recStart,catLabel,proportion +v002,1,Never smoker,0.50 +v002,2,Former smoker,0.30 +v002,3,Current smoker,0.17 +v002,7,Don't know,0.03 +# Sum: 1.00 βœ“ +``` + +--- + +## Validation rules + +MockData validates configuration files on load: + +### UID validation + +1. **Pattern:** `uid` should follow format `vNNN` (e.g., v001, v042), `uid_detail` should follow `dNNN` (e.g., d001, d156) +2. **Uniqueness:** All `uid` values unique in variables.csv +3. **Uniqueness:** All `uid_detail` values unique in variable_details.csv +4. **Foreign keys:** All `uid` in variable_details exist in variables.csv + +### Column validation + +1. **Required columns present:** + - variables.csv: uid, variable, variableType + - variable_details.csv: uid, uid_detail, variable, recStart +2. **Variable name match:** variable_details.variable matches variables.variable +3. **Column placement:** Extension columns only in correct files (e.g., distribution params in variables.csv) + +### Value validation + +1. **Proportions:** Sum to 1.0 per variable (Β±0.01 tolerance) +2. **Garbage data proportions:** Between 0 and 1 +3. **Garbage data ranges:** Use interval notation `[min,max]` or sentinel `"[,]"` +4. **rType values:** One of: integer, double, factor, date, character, logical +5. **distribution values:** One of: normal, uniform, gompertz, exponential, or NA +6. **Versioning:** mockDataVersion follows semantic versioning (if present) +7. **Complete grid:** All cells have explicit values (no empty strings for optional columns - use NA or sentinel values) + +--- + +## Detailed column reference + +### uid and uid_detail: Unique identifiers + +**Purpose:** Permanent identifiers for traceability across metadata versions + +**Format requirements:** + +- `uid`: Pattern `vNNN` with zero-padding (e.g., `v001`, `v042`) +- `uid_detail`: Pattern `dNNN` with zero-padding (e.g., `d001`, `d156`) +- Zero-padding recommended for sorting: `v001` not `v1` + +**Common errors:** + +```csv +# ❌ WRONG: Inconsistent padding +uid,variable +v_1,age +v_10,smoking +v_2,BMI +# Result: Sorts incorrectly (v_1, v_10, v_2) + +# βœ… CORRECT: Zero-padded +uid,variable +v001,age +v002,smoking +v010,BMI +# Result: Sorts correctly (v001, v002, v_010) +``` + +**Edge cases:** + +- UIDs must be globally unique across all databases +- Reusing UIDs across databases for "same variable" is acceptable but requires consistent definitions +- Changing UID means "new variable" even if variable name unchanged + +**Best practices:** + +- Start numbering at v_001 (not v_000) +- Use sequential numbers for easy tracking +- Document UID assignment logic in project README +- Use project prefixes for multi-project repos: `cchs_v001`, `chms_v001` + +--- + +### role: Multi-valued variable roles + +**Purpose:** Tag variables for different purposes in analysis + +**Valid values (comma-separated):** + +| Value | Meaning | Use case | +|-------|---------|----------| +| `enabled` | **Required for generation** | Must be present to generate variable | +| `predictor` | Independent/explanatory variable | Regression models, Table 1 | +| `outcome` | Dependent/response variable | Primary/secondary outcomes | +| `metadata` | Administrative/tracking | IDs, dates, survey metadata | +| `table1` | Summary table variable | Baseline characteristics | + +**Examples:** + +```csv +# Age: predictor for models, show in Table 1 +uid,variable,role +v001,age,"enabled,predictor,table1" + +# Primary outcome: show in Table 1 +uid,variable,role +v005,dementia_diagnosis,"enabled,outcome,table1" + +# Study ID: just metadata +uid,variable,role +v020,study_id,"enabled,metadata" + +# Derived variable: not enabled (calculated post-generation) +uid,variable,role +v006,BMI_derived,outcome +``` + +**Important:** Variable will NOT be generated unless `role` contains `"enabled"`. + +**Common errors:** + +```csv +# ❌ WRONG: Forgot "enabled" +uid,variable,role +v001,age,"predictor,table1" +# Result: age will NOT be generated + +# βœ… CORRECT +uid,variable,role +v001,age,"enabled,predictor,table1" +``` + +**Multi-role filtering example:** + +```r +# Get only variables for Table 1 +table1_vars <- variables[grepl("table1", variables$role), ] + +# Get predictors +predictors <- variables[grepl("predictor", variables$role), ] + +# Get enabled variables for generation +enabled_vars <- variables[grepl("enabled", variables$role), ] +``` + +--- + +### position and seed: Generation order and reproducibility + +**Purpose:** Control variable generation order and ensure reproducible independence + +**position:** + +- Generation order (ascending) +- Use increments of 10 (10, 20, 30...) for easy insertion +- Lower numbers generated first + +**seed:** + +- Random seed for this specific variable +- **Recommended:** `seed = position Γ— 10` (e.g., position 20 β†’ seed 200) +- Prevents correlation artifacts between variables + +**Why position matters:** + +Some variables may depend on others being generated first (though MockData generally handles this automatically). + +**Why seed matters:** + +Using the same seed for all variables can create artificial correlations. Different seeds ensure statistical independence. + +**Examples:** + +```csv +# Good: Increments of 10, seed = position Γ— 10 +uid,variable,position,seed +v001,age,10,100 +v002,smoking,20,200 +v003,BMI,30,300 +``` + +**Common errors:** + +```csv +# ❌ WRONG: Same seed for all variables +uid,variable,position,seed +v001,age,10,123 +v002,smoking,20,123 +v003,BMI,30,123 +# Result: Variables may be artificially correlated + +# ❌ WRONG: Sequential positions (hard to insert) +uid,variable,position,seed +v001,age,1,10 +v002,smoking,2,20 +v003,BMI,3,30 +# Result: Hard to insert new variable between age and smoking +``` + +**Inserting variables:** + +```csv +# Original +uid,variable,position +v001,age,10 +v003,BMI,30 + +# Insert smoking between age and BMI +uid,variable,position +v001,age,10 +v002,smoking,20 # Fits perfectly +v003,BMI,30 +``` + +--- + +### sourceFormat vs sourceData + +**Purpose:** Simulate raw data formats for harmonization pipeline testing + +**Column name:** Currently `sourceFormat` in minimal-example (documentation shows `sourceData`) + +**Valid values:** + +| Value | Output type | Simulates | Example | +|-------|-------------|-----------|---------| +| `analysis` | R Date object | Analysis-ready dates | `as.Date("2001-01-01")` | +| `csv` | Character string | CSV file dates | `"2001-01-01"` | +| `sas` | Numeric | SAS date numeric | `14975` (days since 1960-01-01) | + +**Use case:** Test date parsing/harmonization logic + +**Examples:** + +```csv +# Analysis-ready (default) +uid,variable,sourceFormat +v004,interview_date,analysis + +# CSV import simulation +uid,variable,sourceFormat +v004,interview_date,csv + +# SAS import simulation +uid,variable,sourceFormat +v004,interview_date,sas +``` + +**Conversion examples:** + +```r +# CSV to Date +dates_csv <- "2001-01-01" +as.Date(dates_csv) + +# SAS to Date +dates_sas <- 14975 +as.Date(dates_sas, origin = "1960-01-01") +``` + +See [Working with date variables](tutorial-dates.html#source-data-format-simulating-raw-data-imports) for detailed examples. + +--- + +### distribution: Distribution types by variable type + +**Purpose:** Specify how values are distributed across valid ranges + +**For categorical variables:** Use `NA` (categories defined by proportions in variable_details.csv) + +**For continuous variables:** + +| Distribution | Parameters required | Use case | Example | +|--------------|---------------------|----------|---------| +| `normal` | `mean`, `sd` | Age, BMI, normally-distributed measurements | Age: mean=50, sd=15 | +| `uniform` | None (uses recStart range) | Equal probability across range | Income brackets, uniform codes | + +**For date variables:** + +| Distribution | Parameters required | Use case | Example | +|--------------|---------------------|----------|---------| +| `uniform` | None | Index dates, enrollment dates | Interview date | +| `gompertz` | `rate`, `shape`, `followup_min`, `followup_max`, `event_prop` | Age-related events (death, dementia) | Mortality with increasing hazard by age | +| `exponential` | `rate`, `followup_min`, `followup_max`, `event_prop` | Constant hazard events | Loss to follow-up | + +**Complete examples:** + +```csv +# Continuous: normal distribution +uid,variable,variableType,distribution,mean,sd +v001,age,Continuous,normal,50,15 + +# Continuous: uniform distribution +uid,variable,variableType,distribution +v010,income_bracket,Continuous,uniform + +# Categorical: use NA (proportions in variable_details.csv) +uid,variable,variableType,distribution +v002,smoking,Categorical, + +# Date: uniform (index date) +uid,variable,variableType,distribution +v004,interview_date,Date,uniform + +# Date: gompertz survival (event date) +uid,variable,variableType,distribution,rate,shape,followup_min,followup_max,event_prop +v005,death_date,Date,gompertz,0.0001,0.1,365,7300,0.2 +``` + +**Common errors:** + +```csv +# ❌ WRONG: Normal distribution without mean/sd +uid,variable,distribution,mean,sd +v001,age,normal,, + +# ❌ WRONG: Distribution for categorical variable +uid,variable,variableType,distribution +v002,smoking,Categorical,normal + +# βœ… CORRECT +uid,variable,distribution,mean,sd +v001,age,normal,50,15 +v002,smoking,, +``` + +**Parameter interpretation:** + +- **Normal:** Values drawn from N(mean, sdΒ²), truncated to recStart range +- **Gompertz:** Hazard increases exponentially with age (realistic mortality) +- **Exponential:** Constant hazard over time (random censoring) + +--- + +### Distribution comparison table + +| Distribution | Shape | Median location | Skewness | Best for | +|--------------|-------|-----------------|----------|----------| +| **normal** | Bell curve | At mean | Symmetric | Age, BMI, height, normally-distributed measurements | +| **uniform** | Flat | Middle of range | Symmetric | Dates without temporal pattern, random assignment | +| **gompertz** | Right-skewed | Shifted toward end | Positive | Mortality, age-related disease onset | +| **exponential** | Right-skewed | Shifted toward start | Positive | Time to first event, loss to follow-up | + +**Visual interpretation (for 2001-2020 date range):** + +- **uniform:** Median β‰ˆ 2010 (middle) +- **gompertz:** Median β‰ˆ 2015-2018 (later years, increasing hazard) +- **exponential:** Median β‰ˆ 2003-2007 (earlier years, constant hazard) + +--- + +## Frequently asked questions + +### General configuration + +**Q: What's the difference between variables.csv and variable_details.csv?** + +A: **variables.csv** defines variable-level metadata (one row per variable). **variable_details.csv** defines detail-level specifications (multiple rows per variable for categories/ranges). Think of it as a one-to-many relationship. + +**Q: Can I use a single CSV file instead of two?** + +A: No. The two-file structure comes from recodeflow and is required. It enables: + +- Multiple category definitions per variable +- Clean separation of variable-level vs category-level parameters +- Standardized harmonization workflow integration + +**Q: Do I need to fill in all columns?** + +A: No. Only required columns need values. Optional columns should use: + +- `NA` for not applicable +- Empty string for unknown (though `NA` preferred) +- Sentinel values like `[,]` for empty ranges + +**Q: How do I know which columns are required?** + +A: See [Quick reference](#quick-reference) table. Core required columns: + +- variables.csv: `uid`, `variable`, `variableType` +- variable_details.csv: `uid`, `uid_detail`, `variable`, `recStart` + +--- + +### Variable types + +**Q: When should I use Categorical vs Continuous for numeric codes?** + +A: + +- **Categorical:** Discrete codes with specific meanings (smoking status: 1=never, 2=former, 3=current) +- **Continuous:** Numeric measurements on a scale (age, BMI, income) + +**Rule of thumb:** If you would calculate a mean, use Continuous. If you would calculate proportions, use Categorical. + +**Q: Can I have a Continuous variable with only integer values?** + +A: Yes. Set `variableType = "Continuous"` and `rType = "integer"`. Example: Age in years. + +**Q: What's the difference between variableType and rType?** + +A: + +- `variableType`: Conceptual type from recodeflow (Categorical or Continuous) - determines generation logic +- `rType`: R output data type specified by MockData (integer, double, character, date, factor) - determines output format + +**Note:** Date variables use `variableType = "Continuous"` and `rType = "date"`. The variableType field comes from recodeflow and uses only Categorical/Continuous values. + +**Q: Should smoking status be factor or character?** + +A: Use `rType = "factor"` for categorical variables. Factors preserve category levels and enable proper statistical analysis. + +--- + +### Garbage data + +**Q: What's the difference between garbage_low/garbage_high and prop_garbage?** + +A: Two modes: + +1. **Advanced (garbage_low/garbage_high):** You specify exact invalid ranges + - Example: Age with `garbage_low_range = "[-5,10]"` generates negative ages +2. **Simple (prop_garbage):** MockData auto-generates invalid values + - Example: Categorical with `prop_garbage = 0.05` gets invalid codes like 99, 999 + +**Precedence:** If you specify `garbage_low_prop` OR `garbage_high_prop`, those take precedence. Otherwise `prop_garbage` is used. + +**Q: Why would I want garbage data?** + +A: To test data quality pipelines: + +- Validate your data cleaning code catches impossible values +- Train analysts on real-world data quality issues +- Test edge cases in harmonization logic + +**Q: Can I have both low and high garbage data?** + +A: Yes. Specify both `garbage_low_prop/garbage_low_range` AND `garbage_high_prop/garbage_high_range`: + +```csv +uid,variable,garbage_low_prop,garbage_low_range,garbage_high_prop,garbage_high_range +v003,BMI,0.02,"[-10,0]",0.01,"[60,150]" +``` + +Result: 2% have BMI < 0, 1% have BMI 60-150, rest have valid values. + +--- + +### Missing data + +**Q: What's the difference between NA::a and NA::b?** + +A: Survey missing data classification: + +- **NA::a (valid skip):** Question not asked due to logic (respondent not eligible) + - Example: Pregnancy questions skipped for males + - Statistical treatment: Exclude from denominator +- **NA::b (missing response):** Question asked but no valid answer (don't know, refusal, not stated) + - Example: Respondent refused to answer income question + - Statistical treatment: Include in denominator, exclude from numerator + +**Q: Do missing codes count toward the proportion sum?** + +A: **Yes.** All proportions must sum to 1.0, including missing codes: + +```csv +uid,recStart,recEnd,proportion +v002,1,1,0.50 +v002,2,2,0.30 +v002,3,3,0.17 +v002,7,NA::b,0.03 +# Sum = 1.00 βœ“ +``` + +**Q: How do I generate missing data for continuous/date variables?** + +A: Use `else` in recStart with NA classification: + +```csv +uid,variable,recStart,recEnd,proportion +v001,age,"[18,100]","copy", +v001,age,"else","NA::b",0.05 +``` + +Result: 5% of age values will be NA (recoded from "else" = everything not in range). + +**Q: Can I use ranges for missing codes?** + +A: Yes: + +```csv +# Map codes 997-999 to NA::b +uid,recStart,recEnd +v001,"[997,999]",NA::b +``` + +--- + +### Distributions and parameters + +**Q: What happens if normal distribution generates values outside recStart range?** + +A: Values are truncated to the recStart range. Example: + +```csv +uid,variable,distribution,mean,sd,recStart +v001,age,normal,50,15,"[18,100]" +``` + +Result: Normal distribution N(50, 15Β²) truncated to [18, 100]. No values < 18 or > 100. + +**Q: When should I use gompertz vs exponential for survival data?** + +A: + +- **Gompertz:** Age-related events where hazard increases with time (mortality, dementia, chronic disease) +- **Exponential:** Constant hazard events where risk doesn't change with time (loss to follow-up, random censoring) + +**Q: What are typical gompertz parameters?** + +A: For mortality in elderly cohorts: + +```csv +distribution,rate,shape,followup_min,followup_max,event_prop +gompertz,0.0001,0.1,365,7300,0.2 +``` + +- `rate = 0.0001`: Baseline hazard +- `shape = 0.1`: Hazard acceleration (positive = increasing hazard with age) +- `followup_max = 7300`: 20 years +- `event_prop = 0.2`: 20% experience event + +**Q: Why do my date variables all have the same value?** + +A: Check: + +1. Are you using `distribution = "uniform"`? (Required for variation) +2. Is `recStart` an interval `[start,end]` not a single date? +3. Did you set different seeds for each variable? + +--- + +### UIDs and foreign keys + +**Q: Must uid in variable_details.csv match uid in variables.csv exactly?** + +A: **Yes.** This is a foreign key relationship. Every `uid` in variable_details.csv must exist in variables.csv. + +**Q: Can I have multiple variables with the same uid?** + +A: **No.** UIDs must be unique within variables.csv. Use different UIDs for different variables. + +**Q: Can variable_details.csv have gaps in uid_detail numbering?** + +A: Yes. uid_detail values don't need to be sequential, just unique: + +```csv +uid_detail,variable +d001,age +d_003,age +d_042,age +# Valid - gaps are OK +``` + +**Q: What happens if I reference a uid that doesn't exist in variables.csv?** + +A: Validation error: + +``` +Error: uid 'v_999' in variable_details.csv not found in variables.csv +``` + +--- + +### Proportions and validation + +**Q: How strict is the "proportions must sum to 1.0" rule?** + +A: Tolerance Β±0.01. These are valid: + +- 1.00 βœ“ +- 0.99 βœ“ +- 1.01 βœ“ +- 0.98 ❌ (too far from 1.0) + +**Q: Do garbage data proportions count in the sum?** + +A: **No.** Garbage data (`garbage_low_prop`, `garbage_high_prop`, `prop_garbage`) is separate from population proportions. + +Example: + +```csv +# Proportions in variable_details.csv must sum to 1.0 +uid,recStart,proportion +v002,1,0.50 +v002,2,0.30 +v002,3,0.20 +# Sum = 1.00 βœ“ + +# Garbage data in variables.csv is additional +uid,prop_garbage +v002,0.05 +# Result: 95% valid (distributed 50/30/20), 5% invalid codes +``` + +**Q: What if I want unequal category probabilities?** + +A: Specify exact proportions in variable_details.csv: + +```csv +uid,recStart,catLabel,proportion +v002,1,Never smoker,0.60 +v002,2,Former smoker,0.25 +v002,3,Current smoker,0.15 +# Reflects real population distribution +``` + +--- + +### Database filtering and multi-cycle data + +**Q: What is databaseStart and when do I need it?** + +A: Database/cycle identifier for filtering. Needed when: + +- Generating data for multiple survey cycles (CCHS 2001, 2005, 2009) +- Variables have database-specific category codes +- Testing multi-cycle harmonization + +**Q: How do I specify which databases a row applies to?** + +A: Use comma-separated list in `databaseStart` column (variable_details.csv): + +```csv +uid,variable,databaseStart,recStart +v001,age,"cchs2001_p,cchs2005_p","[18,100]" +v002,smoking,cchs2001_p,1 +v002,smoking,cchs2005_p,01 +``` + +Row 1 applies to both databases. Rows 2-3 are database-specific (different codes for smoking). + +**Q: What if I'm only generating data for one database?** + +A: Use a single database name consistently: + +```csv +uid,variable,databaseStart,recStart +v001,age,my_study,"[18,100]" +v002,smoking,my_study,1 +``` + +Then generate with: + +```r +create_mock_data( + databaseStart = "my_study", + variables = variables, + variable_details = variable_details +) +``` + +--- + +## Troubleshooting + +### Validation errors + +**Error: "Proportions for variable 'smoking' sum to 0.97, expected 1.0"** + +**Cause:** Category proportions don't sum to 1.0 (Β±0.01 tolerance) + +**Fix:** Check proportions in variable_details.csv for that variable: + +```r +# Identify the problem +var_details %>% + filter(variable == "smoking") %>% + summarize(total = sum(proportion, na.rm = TRUE)) + +# Fix: Adjust proportions to sum to 1.0 +``` + +--- + +**Error: "uid 'v_042' in variable_details.csv not found in variables.csv"** + +**Cause:** Foreign key violation - referenced uid doesn't exist + +**Fix:** Check for typos or missing rows: + +```r +# Find orphaned uids +details_uids <- unique(variable_details$uid) +vars_uids <- unique(variables$uid) +orphans <- setdiff(details_uids, vars_uids) +print(orphans) + +# Fix: Either add missing uid to variables.csv or fix typo in variable_details.csv +``` + +--- + +**Error: "Required column 'recStart' not found in variable_details.csv"** + +**Cause:** Missing required column + +**Fix:** Add the missing column: + +```r +# Check what columns exist +names(variable_details) + +# Add missing column (with default values if needed) +variable_details$recStart <- NA +``` + +--- + +**Error: "Invalid rType value 'float' for variable 'BMI'"** + +**Cause:** rType must be one of: integer, double, factor, date, character, logical + +**Fix:** Use `"double"` not `"float"`: + +```csv +# ❌ WRONG +uid,variable,rType +v003,BMI,float + +# βœ… CORRECT +uid,variable,rType +v003,BMI,double +``` + +--- + +**Error: "distribution 'normal' requires 'mean' and 'sd' parameters"** + +**Cause:** Normal distribution missing required parameters + +**Fix:** Specify mean and sd: + +```csv +# ❌ WRONG +uid,variable,distribution,mean,sd +v001,age,normal,, + +# βœ… CORRECT +uid,variable,distribution,mean,sd +v001,age,normal,50,15 +``` + +--- + +### Generation issues + +**Problem: All date variables have the same value** + +**Possible causes:** + +1. Used single date instead of interval in recStart +2. Forgot to specify distribution +3. Same seed for all variables + +**Fix:** + +```csv +# Check recStart uses interval notation +uid,variable,recStart +v004,interview_date,"[2001-01-01,2005-12-31]" + +# Check distribution is specified +uid,variable,distribution +v004,interview_date,uniform + +# Check different seeds +uid,variable,seed +v004,interview_date,400 +v005,event_date,500 +``` + +--- + +**Problem: No variables generated (empty data frame)** + +**Possible causes:** + +1. No variables have `role = "enabled"` +2. databaseStart filter excludes all rows +3. All variables are derived variables + +**Fix:** + +```r +# Check which variables are enabled +enabled <- variables[grepl("enabled", variables$role), ] +nrow(enabled) # Should be > 0 + +# Check databaseStart filtering +filtered <- variable_details[ + grepl(databaseStart, variable_details$databaseStart), +] +nrow(filtered) # Should be > 0 +``` + +--- + +**Problem: Proportions don't match expected distribution** + +**Cause:** Forgot to account for missing data proportion + +**Fix:** Missing data proportion reduces valid category proportions: + +```csv +# If you want 50% never smokers in VALID responses: +uid,recStart,recEnd,proportion +v002,1,1,0.475 # 50% of 95% = 47.5% +v002,2,2,0.285 # 30% of 95% = 28.5% +v002,3,3,0.19 # 20% of 95% = 19% +v002,7,NA::b,0.05 # 5% missing +# Sum = 1.00 +# Result: Among VALID responses, 50/30/20 split +``` + +--- + +**Problem: Garbage data not appearing** + +**Possible causes:** + +1. Proportion too small to see in sample +2. Wrong column name (garbage_low vs corrupt_low) +3. Precedence issue (prop_garbage ignored if garbage_low_prop specified) + +**Fix:** + +```csv +# Increase proportion for testing +uid,variable,garbage_high_prop +v003,BMI,0.20 # 20% easier to verify than 1% + +# Check correct column names (garbage_ not corrupt_) +uid,variable,garbage_low_prop,garbage_low_range +v001,age,0.05,"[-5,10]" + +# If using advanced mode, don't specify prop_garbage +uid,variable,garbage_low_prop,garbage_low_range,prop_garbage +v001,age,0.05,"[-5,10]", # Leave prop_garbage empty +``` + +--- + +### Performance issues + +**Problem: Generation very slow for large n** + +**Cause:** Complex distributions (especially normal) are slower than uniform + +**Solutions:** + +1. Use uniform distribution where appropriate +2. Generate in batches +3. Simplify metadata (fewer variables, fewer categories) + +```r +# Batch generation example +batch_size <- 100000 +n_batches <- 10 + +results <- lapply(1:n_batches, function(i) { + create_mock_data( + databaseStart = "my_study", + variables = variables, + variable_details = variable_details, + n = batch_size, + seed = 1000 + i # Different seed per batch + ) +}) + +final_data <- bind_rows(results) +``` + +--- + +## Complete examples + +### Example 1: Basic categorical variable with missing codes + +**Use case:** Smoking status with standard survey missing codes + +```csv +# variables.csv +uid,variable,label,variableType,rType,role,position,seed,prop_garbage +v002,smoking,Smoking status,Categorical,factor,"enabled,predictor",20,200,0.05 + +# variable_details.csv +uid,uid_detail,variable,recStart,recEnd,catLabel,proportion +v002,d_002,smoking,1,1,Never smoker,0.50 +v002,d_003,smoking,2,2,Former smoker,0.30 +v002,d_004,smoking,3,3,Current smoker,0.17 +v002,d_005,smoking,7,NA::b,Don't know,0.03 +``` + +**Result:** 50% never/30% former/17% current smokers, 3% don't know (NA), plus 5% invalid codes (99, 999) from prop_garbage. + +--- + +### Example 2: Continuous variable with normal distribution and precise garbage ranges + +**Use case:** Body mass index with biologically impossible values for QA testing + +```csv +# variables.csv +uid,variable,label,variableType,rType,role,position,seed,garbage_low_prop,garbage_low_range,garbage_high_prop,garbage_high_range,distribution,mean,sd +v003,BMI,Body mass index,Continuous,double,"enabled,outcome",30,300,0.02,"[-10,0]",0.01,"[60,150]",normal,27.5,5.2 + +# variable_details.csv +uid,uid_detail,variable,recStart,recEnd,catLabel,proportion +v003,d_006,BMI,"[15,50]",copy,Valid BMI range, +``` + +**Result:** Normal distribution N(27.5, 5.2Β²) truncated to [15, 50], with 2% negative BMI values and 1% extremely high (60-150) values. + +--- + +### Example 3: Continuous variable with missing data + +**Use case:** Age with survey missing codes and uniform distribution + +```csv +# variables.csv +uid,variable,label,variableType,rType,role,position,seed +v001,age,Age in years,Continuous,integer,"enabled,predictor,table1",10,100 + +# variable_details.csv +uid,uid_detail,variable,recStart,recEnd,catLabel,proportion +v001,d001,age,"[18,100]",copy,Valid age range,0.90 +v001,d_002,age,997,NA::b,Don't know,0.05 +v001,d_003,age,998,NA::b,Refusal,0.03 +v001,d_004,age,999,NA::b,Not stated,0.02 +``` + +**Result:** 90% valid ages uniformly distributed 18-100, 10% missing with codes 997/998/999 (mapped to NA). + +--- + +### Example 4: Date variable (cohort entry/index date) + +**Use case:** Interview date as time origin for survival analysis + +```csv +# variables.csv +uid,variable,label,variableType,rType,role,position,seed,distribution,sourceFormat +v004,interview_date,Interview date,Date,date,"enabled,metadata",40,400,uniform,analysis + +# variable_details.csv +uid,uid_detail,variable,recStart,recEnd,catLabel,proportion +v004,d_007,interview_date,"[2001-01-01,2005-12-31]",copy,Interview date range,1 +v004,d_008,interview_date,else,NA::b,Missing interview date,0 +``` + +**Result:** Uniform distribution of dates 2001-2005 (all respondents interviewed), output as R Date objects. + +--- + +### Example 5: Survival variable with competing risks (gompertz distribution) + +**Use case:** Primary event (dementia diagnosis) with age-related hazard and temporal garbage data + +```csv +# variables.csv +uid,variable,label,variableType,rType,role,position,seed,garbage_high_prop,garbage_high_range,distribution,rate,shape,followup_min,followup_max,event_prop +v005,primary_event_date,Primary event date (dementia),Date,date,"enabled,outcome,table1",50,500,0.03,"[2021-01-01,2099-12-31]",gompertz,0.0001,0.1,0,5475,0.1 + +# variable_details.csv +uid,uid_detail,variable,recStart,recEnd,catLabel,proportion +v005,d_009,primary_event_date,"[2002-01-01,2021-01-01]",copy,Primary event date range,0.1 +v005,d_010,primary_event_date,else,NA::b,Missing event date,0 +``` + +**Interpretation:** + +- 10% experience dementia diagnosis within 0-15 years after interview +- Event times follow gompertz distribution (increasing hazard with age) +- 3% have impossible future dates (2021-2099) for QA testing +- 90% censored (no event) + +--- + +### Example 6: Multi-cycle categorical variable with database-specific codes + +**Use case:** Smoking status with different category codes across survey cycles + +```csv +# variables.csv +uid,variable,label,variableType,rType,role,position,seed +v002,smoking,Smoking status,Categorical,factor,"enabled,predictor",20,200 + +# variable_details.csv +uid,uid_detail,variable,databaseStart,recStart,recEnd,catLabel,proportion +v002,d_002,smoking,cchs2001_p,1,1,Never smoker,0.50 +v002,d_003,smoking,cchs2001_p,2,2,Former smoker,0.30 +v002,d_004,smoking,cchs2001_p,3,3,Current smoker,0.20 +v002,d_005,smoking,cchs2005_p,01,1,Never smoker,0.50 +v002,d_006,smoking,cchs2005_p,02,2,Former smoker,0.30 +v002,d_007,smoking,cchs2005_p,03,3,Current smoker,0.20 +``` + +**Result:** + +- CCHS 2001: Codes 1/2/3 (numeric) +- CCHS 2005: Codes 01/02/03 (zero-padded strings) +- Same proportions, different source codes +- Both map to harmonized values 1/2/3 (recEnd column) + +--- + +### Example 7: Derived variable (BMI from height and weight) + +**Use case:** BMI calculated post-generation from height and weight + +```csv +# variables.csv (height) +uid,variable,label,variableType,rType,role,position,seed,distribution,mean,sd +v004,height,Height in meters,Continuous,double,"enabled,predictor",40,400,normal,1.7,0.1 + +# variables.csv (weight) +uid,variable,label,variableType,rType,role,position,seed,distribution,mean,sd +v005,weight,Weight in kg,Continuous,double,"enabled,predictor",50,500,normal,75,15 + +# variables.csv (BMI_derived - NOT enabled) +uid,variable,label,variableType,rType,role,position,seed +v006,BMI_derived,BMI calculated from height and weight,Continuous,double,outcome,60,600 + +# variable_details.csv +uid,uid_detail,variable,recStart,recEnd,catLabel +v004,d_012,height,"[1.4,2.1]",copy,Valid height range (meters) +v005,d_014,weight,"[35,150]",copy,Valid weight range (kg) +v006,d_016,BMI_derived,"DerivedVar::[height, weight]","Func::bmi_fun",BMI calculated from height and weight +``` + +**Generation workflow:** + +```r +# 1. Generate height and weight +mock_data <- create_mock_data( + databaseStart = "my_study", + variables = variables, + variable_details = variable_details, + n = 1000 +) +# Result: Contains height, weight (but NOT BMI_derived) + +# 2. Calculate BMI_derived post-generation +bmi_fun <- function(height, weight) { + ifelse( + is.na(height) | is.na(weight) | height <= 0, + NA_real_, + weight / (height^2) + ) +} + +mock_data$BMI_derived <- bmi_fun(mock_data$height, mock_data$weight) +``` + +**Note:** Derived variables are NOT generated by create_mock_data(). See [Advanced topics: Derived variables](advanced-topics.html#derived-variables) for details. + +--- + +### Example 8: Complete survival analysis dataset with competing risks + +**Use case:** Cohort study with primary event, death, and censoring + +```csv +# variables.csv +uid,variable,label,variableType,rType,role,position,seed,distribution,rate,shape,followup_min,followup_max,event_prop +v004,interview_date,Interview date,Date,date,"enabled,metadata",40,400,uniform,,,,,, +v005,primary_event_date,Dementia diagnosis,Date,date,"enabled,outcome",50,500,gompertz,0.0001,0.1,0,5475,0.1 +v006,death_date,Death date,Date,date,"enabled,outcome",60,600,gompertz,0.0001,0.1,365,7300,0.2 +v_007,ltfu_date,Loss to follow-up,Date,date,"enabled,outcome",70,700,uniform,,,365,7300,0.1 +v_008,admin_censor_date,Administrative censoring,Date,date,"enabled,metadata",80,800,,,,365,7300,1 + +# variable_details.csv +uid,uid_detail,variable,recStart,recEnd,proportion +v004,d_007,interview_date,"[2001-01-01,2005-12-31]",copy,1 +v005,d_009,primary_event_date,"[2002-01-01,2021-01-01]",copy,0.1 +v006,d_011,death_date,"[2002-01-01,2024-12-31]",copy,0.2 +v_007,d_013,ltfu_date,"[2002-01-01,2024-12-31]",copy,0.1 +v_008,d_015,admin_censor_date,2024-12-31,copy,1 +``` + +**Interpretation:** + +- **Index date:** Interview 2001-2005 (100% have date) +- **Primary event:** 10% develop dementia within 0-15 years (gompertz hazard) +- **Competing risk:** 20% die within 1-20 years (gompertz hazard) +- **Censoring:** 10% lost to follow-up within 1-20 years (uniform) +- **Administrative:** All censored at 2024-12-31 + +**Result:** Realistic competing risks dataset with: + +- Some experience primary event before death/censoring +- Some die before primary event +- Some censored (lost to follow-up or administrative) +- No individual can have more than one terminal event + +See [Tutorial: Generating survival data with competing risks](tutorial-survival-data.html) for complete workflow. + +--- + +### Example 9: Categorical variable with skip logic (NA::a) + +**Use case:** Pregnancy question with valid skip for males/postmenopausal + +```csv +# variables.csv +uid,variable,label,variableType,rType,role,position,seed +v010,currently_pregnant,Currently pregnant,Categorical,factor,"enabled,outcome",100,1000 + +# variable_details.csv +uid,uid_detail,variable,recStart,recEnd,catLabel,proportion +v010,d_020,currently_pregnant,1,1,Yes,0.05 +v010,d_021,currently_pregnant,2,2,No,0.30 +v010,d_022,currently_pregnant,6,NA::a,Valid skip (not applicable),0.60 +v010,d_023,currently_pregnant,9,NA::b,Not stated,0.05 +``` + +**Result:** + +- 5% currently pregnant +- 30% not pregnant +- 60% valid skip (males, postmenopausal females - not eligible for question) +- 5% eligible but didn't answer + +**Statistical interpretation:** + +- **Denominator for prevalence:** 0.05 + 0.30 + 0.05 = 0.40 (eligible respondents) +- **Prevalence among eligible:** 0.05 / 0.40 = 12.5% +- **Response rate:** (0.05 + 0.30) / 0.40 = 87.5% + +--- + +### Example 10: Versioned metadata with garbage data evolution + +**Use case:** Tracking changes to QA testing parameters over time + +```csv +# variables.csv (version 1.0.0) +uid,variable,garbage_low_prop,garbage_low_range,mockDataVersion,mockDataVersionNotes +v001,age,0.01,"[-5,10]",1.0.0,Initial version with minimal contamination + +# variables.csv (version 1.1.0 - increased QA testing) +uid,variable,garbage_low_prop,garbage_low_range,mockDataVersion,mockDataLastUpdated,mockDataVersionNotes +v001,age,0.05,"[-10,15]",1.1.0,2025-11-15,Increased contamination for comprehensive QA testing +``` + +**Use case:** + +- Track metadata evolution +- Document why garbage data proportions changed +- Reproduce exact mock datasets from specific versions +- Audit trail for scientific publications + +--- + +## Edge cases and special configurations + +### Single-value categorical variable + +**Use case:** Binary variable with only two categories + +```csv +uid,uid_detail,variable,recStart,recEnd,proportion +v020,d_040,diabetes,0,0,0.90 +v020,d_041,diabetes,1,1,0.10 +``` + +**Result:** 90% no diabetes (0), 10% diabetes (1). + +--- + +### Administrative date (all same value) + +**Use case:** Data freeze date - everyone has same value + +```csv +# variables.csv +uid,variable,variableType,rType,distribution +v_008,admin_censor_date,Date,date, + +# variable_details.csv +uid,uid_detail,variable,recStart,recEnd,proportion +v_008,d_015,admin_censor_date,2024-12-31,copy,1 +``` + +**Result:** All rows have `2024-12-31` (single date, not a range). + +--- + +### Continuous variable with missing data using "else" + +**Use case:** Height with catch-all missing pattern + +```csv +uid,uid_detail,variable,recStart,recEnd,proportion +v004,d_012,height,"[1.4,2.1]",copy, +v004,d_013,height,else,NA::b,0.02 +``` + +**Result:** 98% valid heights [1.4, 2.1], 2% coded as `else` β†’ NA. + +--- + +### Zero-variance continuous variable (for testing) + +**Use case:** Constant value for all observations + +```csv +# variables.csv +uid,variable,distribution,mean,sd +v030,constant_value,normal,100,0.001 + +# variable_details.csv +uid,uid_detail,variable,recStart +v030,d_060,constant_value,"[99.99,100.01]" +``` + +**Result:** All values β‰ˆ 100 (effectively constant given narrow range and tiny SD). + +--- + +## Schema design principles + +### Core principles + +**1. Complete grid:** Every cell has an explicit value + +- Use `NA` for not applicable +- Use `""` (empty string) only when value is truly unknown +- Use sentinel values `[,]` for empty ranges +- No implicit defaults - be explicit + +**2. Separation of concerns:** + +- **variables.csv:** Variable-level metadata (one row per variable) +- **variable_details.csv:** Category/range specifications (multiple rows per variable) +- **Generation logic:** In R package functions, not in metadata + +**3. Traceability:** + +- UIDs provide permanent identifiers +- Versioning columns track metadata evolution +- Foreign keys link files (uid column) + +**4. Composability:** + +- Variables can be generated independently +- Metadata can be shared across databases (databaseStart filtering) +- Derived variables calculated post-generation + +**5. Validation-first:** + +- Schema validates before generation +- Fail fast with clear error messages +- Sum-to-one enforcement prevents silent errors + +--- + +### Best practices checklist + +**Before creating metadata:** + +- [ ] Choose naming convention for UIDs (project prefix + zero-padded numbers) +- [ ] Decide on databaseStart naming (single study vs multi-cycle) +- [ ] Plan versioning strategy (when to increment mockDataVersion) +- [ ] Document seed strategy (position Γ— 10 recommended) + +**During metadata creation:** + +- [ ] Use zero-padded UIDs (v001 not v1) +- [ ] Use increments of 10 for position (10, 20, 30) +- [ ] Ensure proportions sum to 1.0 for each variable +- [ ] Include "enabled" in role for variables to generate +- [ ] Use interval notation for continuous/date ranges +- [ ] Specify distribution parameters when needed +- [ ] Add catLabel for documentation + +**After metadata creation:** + +- [ ] Validate files load without errors +- [ ] Check foreign keys (all variable_details.uid exist in variables.uid) +- [ ] Verify proportions sum correctly +- [ ] Test generation with small n (100) first +- [ ] Check output matches expected distributions +- [ ] Verify garbage data appears as expected +- [ ] Document any non-obvious design decisions + +**For production use:** + +- [ ] Freeze metadata version (commit to git) +- [ ] Document mockDataVersion in README +- [ ] Include seed in generation scripts +- [ ] Save generated data with metadata version tag +- [ ] Keep audit trail of metadata changes + +--- + +## Migration from older versions + +### From recodeflow metadata (no MockData extensions) + +If you have existing recodeflow metadata without MockData extension columns: + +**1. Add required extension columns to variables.csv:** + +```r +# Minimal additions +variables$rType <- "double" # Or appropriate type +variables$role <- "enabled" +variables$position <- seq(10, by = 10, length.out = nrow(variables)) +variables$seed <- variables$position * 10 +``` + +**2. Add distribution columns (if needed):** + +```r +# For continuous variables +continuous_vars <- variables$variableType == "Continuous" +variables$distribution[continuous_vars] <- "uniform" + +# For date variables +date_vars <- variables$variableType == "Date" +variables$distribution[date_vars] <- "uniform" +``` + +**3. Add recEnd to variable_details.csv:** + +```r +# For continuous/date variables with ranges +variable_details$recEnd[is.na(variable_details$recEnd)] <- "copy" + +# For categorical variables (map codes to themselves) +# Requires manual review to identify missing codes +``` + +**4. Validate and test:** + +```r +# Load and validate +mock_data <- create_mock_data( + databaseStart = "your_database", + variables = variables, + variable_details = variable_details, + n = 100 +) + +# Verify structure +str(mock_data) +summary(mock_data) +``` + +--- + +### From MockData v0.1.x to v0.2.x + +Key changes in v0.2.0: + +**1. Garbage data column names changed:** + +```csv +# OLD (v0.1.x) +corrupt_low_prop,corrupt_low_range,corrupt_high_prop,corrupt_high_range + +# NEW (v0.2.x) +garbage_low_prop,garbage_low_range,garbage_high_prop,garbage_high_range +``` + +**Migration:** + +```r +# Rename columns +names(variables)[names(variables) == "corrupt_low_prop"] <- "garbage_low_prop" +names(variables)[names(variables) == "corrupt_low_range"] <- "garbage_low_range" +names(variables)[names(variables) == "corrupt_high_prop"] <- "garbage_high_prop" +names(variables)[names(variables) == "corrupt_high_range"] <- "garbage_high_range" +``` + +**2. Distribution parameters moved to variables.csv:** + +In v0.1.x, some parameters were in variable_details.csv. In v0.2.x, all distribution parameters are in variables.csv. + +**3. New versioning columns available:** + +```csv +mockDataVersion,mockDataLastUpdated,mockDataVersionNotes +``` + +Add these to track metadata changes over time. + +--- + +## Performance optimization + +### For large datasets (n > 1M) + +**1. Use simpler distributions:** + +```csv +# Slower +distribution,mean,sd +normal,50,15 + +# Faster +distribution +uniform +``` + +**2. Minimize variables:** + +Only include variables you actually need. Each variable adds generation time. + +**3. Batch generation:** + +```r +# Generate in chunks +batch_size <- 100000 +n_batches <- ceiling(total_n / batch_size) + +results <- lapply(1:n_batches, function(i) { + create_mock_data( + databaseStart = "my_study", + variables = variables, + variable_details = variable_details, + n = min(batch_size, total_n - (i-1)*batch_size), + seed = base_seed + i + ) +}) + +final_data <- bind_rows(results) +``` + +**4. Simplify metadata:** + +- Reduce number of categories per variable +- Use uniform instead of normal distributions +- Minimize garbage data (only for QA testing, not production) + +--- + +### Memory management + +**For n > 10M rows:** + +```r +# Generate in batches and write to disk +for (i in 1:n_batches) { + batch <- create_mock_data( + databaseStart = "my_study", + variables = variables, + variable_details = variable_details, + n = batch_size, + seed = base_seed + i + ) + + # Write to disk immediately + write.csv(batch, paste0("mock_data_batch_", i, ".csv"), row.names = FALSE) + + # Free memory + rm(batch) + gc() +} + +# Combine later if needed +all_files <- list.files(pattern = "mock_data_batch_.*\\.csv") +combined <- do.call(rbind, lapply(all_files, read.csv)) +``` + +--- + +## Reference implementation + +```{r} +#| echo: false + +# Summarize the example dataset +n_variables <- nrow(variables_csv) +n_detail_rows <- nrow(variable_details_csv) +variable_types <- table(variables_csv$variableType) +rtypes <- table(variables_csv$rType) +``` + +See [inst/extdata/minimal-example/](https://github.com/Big-Life-Lab/mockData/tree/main/inst/extdata/minimal-example) for a complete working example with `r n_variables` variables (`r paste(names(variable_types), ":", variable_types, collapse = ", ")`) and `r n_detail_rows` detail rows demonstrating: + +- All `r vars_counts$extensions` variable-level extension columns (plus `r vars_counts$core` core recodeflow columns) +- All `r details_counts$extensions` detail-level extension columns (plus `r details_counts$core` core recodeflow columns) +- All variable types (integer, factor, double, date) +- All garbage data patterns (advanced low/high, simple prop_garbage) +- All distribution types (normal, uniform, gompertz) +- Survival analysis with competing risks +- UID-based foreign keys +- Interval notation throughout +- Complete grid principle (no empty strings, explicit NA/sentinels) + +This example validates successfully and can be used as a template for new projects. diff --git a/vignettes/styles.css b/vignettes/styles.css new file mode 100644 index 0000000..6e83658 --- /dev/null +++ b/vignettes/styles.css @@ -0,0 +1,7 @@ +/* Styling for inline R output - wrapped with .r-output class */ +.r-output code { + background-color: #fffbf0; + padding: 0.1em 0.3em; + border-radius: 3px; + border: none; +} diff --git a/vignettes/tutorial-categorical-continuous.qmd b/vignettes/tutorial-categorical-continuous.qmd new file mode 100644 index 0000000..f6c3ff4 --- /dev/null +++ b/vignettes/tutorial-categorical-continuous.qmd @@ -0,0 +1,541 @@ +--- +title: "Generating categorical and continuous variables" +format: html +vignette: > + %\VignetteIndexEntry{Generating categorical and continuous variables} + %\VignetteEngine{quarto::html} + %\VignetteEncoding{UTF-8} +--- + +```{r} +#| label: setup +#| include: false +# Load package - works in both local dev and pkgdown build +if (file.exists("../DESCRIPTION")) { + devtools::load_all("../", quiet = TRUE) +} else { + library(MockData) +} +``` + +::: {.vignette-about} +**About this vignette:** This tutorial teaches the fundamentals of generating categorical and continuous variables. You'll learn how to use `create_cat_var()` and `create_con_var()` to generate individual variables with precise control over distributions and proportions. All code examples run during vignette build to ensure accuracy. +::: + +## Overview + +MockData provides two core functions for generating the most common variable types: + +- **`create_cat_var()`** - Categorical variables (smoking status, education level, disease diagnosis) +- **`create_con_var()`** - Continuous variables (age, weight, blood pressure, income) + +This tutorial focuses on the basics of these two variable types. For specialized topics, see: + +- [Missing data](tutorial-missing-data.html) - Survey missing codes and NA patterns +- [Garbage data](tutorial-garbage-data.html) - Data quality testing with intentional errors +- [Date variables](tutorial-dates.html) - Temporal data and survival times + +## Categorical variables + +Categorical variables represent discrete categories with specific meanings. Examples: smoking status, education level, disease diagnosis. + +### Basic categorical variable + +Let's generate smoking status from the minimal-example metadata: + +::: {.callout-note} +## About example data paths + +These examples use `system.file()` to load example metadata included with the MockData package. In your own projects, you'll use regular file paths: + +```r +# Package examples use: +variables <- read.csv( + system.file("extdata/minimal-example/variables.csv", package = "MockData"), + stringsAsFactors = FALSE, check.names = FALSE +) + +# Your code will use: +variables <- read.csv( + "path/to/your/variables.csv", + stringsAsFactors = FALSE, check.names = FALSE +) +``` +::: + +```{r} +#| label: load-metadata-generate-smoking +#| warning: false +#| message: false + +# Load minimal-example metadata +variables <- read.csv( + system.file("extdata/minimal-example/variables.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE +) + +variable_details <- read.csv( + system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE +) + +# Generate smoking status (categorical variable) +smoking <- create_cat_var( + var = "smoking", + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 1000, + seed = 123 +) + +# View structure +head(smoking) +str(smoking) +``` + +### Categorical variable proportions + +The `proportion` column in variable_details.csv controls the distribution of categories: + +```{r} +#| label: extract-smoking-proportions +#| echo: false + +# Extract smoking proportions from metadata +smoking_details <- variable_details[variable_details$variable == "smoking", ] +``` + +**Smoking proportions from metadata:** + +```{r} +#| label: display-smoking-table +#| echo: false +knitr::kable(smoking_details[, c("recStart", "catLabel", "proportion")]) +``` + +**Observed distribution:** + +```{r} +#| label: check-smoking-distribution +# Check the distribution +table(smoking$smoking) +prop.table(table(smoking$smoking)) +``` + +**Key insight:** The observed proportions closely match the metadata specifications. MockData samples categories according to the specified proportions. + +### Understanding categorical metadata + +For smoking (cchsflow_v0002), the metadata specifies: + +**In variables.csv:** + +- `variableType = "Categorical"` +- `rType = "factor"` - Output as R factor with levels + +**In variable_details.csv:** + +- Each category has its own row +- `recStart` contains the category code ("1", "2", "3") +- `proportion` must sum to 1.0 across all categories + +```{r} +#| label: verify-proportions-sum +#| echo: false + +# Verify proportions sum to 1.0 +prop_sum <- sum(smoking_details$proportion, na.rm = TRUE) +``` + +**Proportion validation:** Sum = `r round(prop_sum, 3)` (must be 1.0 Β± 0.01) + +## Continuous variables + +Continuous variables represent numeric measurements on a scale. Examples: age, BMI, blood pressure, income. + +### Basic continuous variable (integer) + +Let's generate age from the minimal-example metadata: + +```{r} +#| label: generate-age +#| warning: false +#| message: false + +# Generate age (continuous variable with integer output) +age <- create_con_var( + var = "age", + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 1000, + seed = 456 +) + +# View structure +head(age) +str(age) +``` + +### Continuous variable distributions + +Continuous variables use statistical distributions to generate realistic values: + +```{r} +#| label: check-age-distribution +# Check the distribution +summary(age$age) +hist(age$age, breaks = 30, main = "Age Distribution", xlab = "Age (years)", col = "lightblue") +``` + +```{r} +#| label: extract-age-parameters +#| echo: false + +# Extract age distribution parameters from metadata +age_row <- variables[variables$variable == "age", ] +age_mean <- age_row$mean +age_sd <- age_row$sd +age_distribution <- age_row$distribution +``` + +**Distribution parameters from metadata:** + +- Distribution: `r age_distribution` +- Mean: `r age_mean` +- Standard deviation: `r age_sd` + +**Interpretation:** Age is drawn from a normal distribution with mean = `r age_mean` and SD = `r age_sd`, truncated to the valid range specified in variable_details.csv. Notice the peak at 999β€”in raw data from complex sources like surveys, missing codes are often unrealistically high or low values. This is by design, but it can generate unusual patterns in the data distribution. See the [Missing data tutorial](tutorial-missing-data.html) for more information. + +### Understanding continuous metadata + +For age (cchsflow_v0001), the metadata specifies: + +**In variables.csv:** + +- `variableType = "Continuous"` +- `rType = "integer"` - Output as whole numbers +- `distribution = "normal"` - Use normal distribution +- `mean = 50`, `sd = 15` - Distribution parameters + +**In variable_details.csv:** + +- `recStart = "[18,100]"` - Valid range (interval notation) +- `proportion = NA` - Not applicable for continuous variables + +The normal distribution is truncated to [18, 100], ensuring no invalid ages are generated. + +### Continuous variable (double precision) + +Let's generate weight, which requires decimal precision: + +```{r} +#| label: generate-weight +#| warning: false +#| message: false + +# Generate weight (continuous variable with double precision) +weight <- create_con_var( + var = "weight", + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 1000, + seed = 789 +) + +# View structure +head(weight) +str(weight) +``` + +```{r} +#| label: check-weight-distribution +# Check the distribution +summary(weight$weight) +hist(weight$weight, breaks = 30, main = "Weight Distribution", xlab = "Weight (kg)", col = "lightgreen") +``` + +```{r} +#| label: extract-weight-parameters +#| echo: false + +# Extract weight distribution parameters +weight_row <- variables[variables$variable == "weight", ] +weight_mean <- weight_row$mean +weight_sd <- weight_row$sd +``` + +**Weight parameters:** + +- Distribution: normal +- Mean: `r weight_mean` kg +- Standard deviation: `r weight_sd` kg +- Output type: double (decimal values) + +**Difference from age:** Weight uses `rType = "double"` to preserve decimal precision (e.g., 72.3, 85.7), while age uses `rType = "integer"` for whole numbers (e.g., 45, 67). + +## Comparing categorical vs continuous + +| Aspect | Categorical | Continuous | +|--------|-------------|------------| +| **Use case** | Discrete categories | Numeric measurements | +| **Examples** | Smoking status, education | Age, weight, income | +| **Distribution** | Proportions | Statistical (normal, uniform) | +| **variable_details** | Multiple rows (one per category) | Single row (range specification) | +| **proportion column** | Required (must sum to 1.0) | NA (not applicable) | +| **recStart** | Category codes ("1", "2", "3") | Interval notation ("[18,100]") | +| **Output types** | factor, character | integer, double | + +## When to use individual functions vs create_mock_data() + +**Use `create_cat_var()` or `create_con_var()` when:** + +- Testing a single variable interactively +- Exploring distribution parameters +- Debugging metadata specifications +- Generating variables one at a time for specific tests + +**Use `create_mock_data()` when:** + +- Generating complete datasets with multiple variables +- Need all variables generated together +- Production workflows with saved metadata files + +**Example: Batch generation** + +```{r} +#| label: batch-generation +#| warning: false +#| message: false + +# Generate multiple variables at once +mock_data <- create_mock_data( + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 1000, + seed = 100 +) + +# Check which variables were generated +names(mock_data) +head(mock_data[, c("smoking", "age", "weight")]) +``` + +**Result:** All enabled variables generated in a single call, maintaining consistent sample size and relationships. + +## Distribution types for continuous variables + +MockData supports two distributions for continuous variables: + +### Normal distribution + +Most common for naturally-varying measurements: + +**Parameters:** + +- `distribution = "normal"` +- `mean` - Center of distribution +- `sd` - Spread (standard deviation) + +**Examples:** + +- Age (mean = 50, sd = 15) +- Weight (mean = 75, sd = 15) +- Height (mean = 1.7, sd = 0.1) + +**Properties:** + +- Bell-shaped curve +- Symmetric around mean +- ~68% within 1 SD, ~95% within 2 SD +- Values truncated to valid range + +### Uniform distribution + +Equal probability across entire range: + +**Parameters:** + +- `distribution = "uniform"` +- No additional parameters needed +- Uses range from variable_details.csv + +**Example configuration:** + +```csv +# variables.csv +uid,variable,distribution +v010,participant_id,uniform + +# variable_details.csv +uid,variable,recStart +v010,participant_id,"[1000,9999]" +``` + +**Use cases:** + +- ID numbers +- Random assignment codes +- Variables without known distribution + +## Proportions for categorical variables + +Proportions control the population distribution of categories. They must sum to 1.0 (Β±0.01 tolerance). + +### Example: Realistic smoking prevalence + +```{r} +#| label: show-smoking-proportions +#| echo: false + +# Show smoking proportions +smoking_props <- variable_details[variable_details$variable == "smoking", c("catLabel", "proportion")] +knitr::kable(smoking_props, row.names = FALSE) +``` + +These proportions might reflect: + +- Published health survey statistics +- Literature values for the population +- Target distributions for study design + +### Matching published statistics + +The proportion specification allows you to generate mock data that matches "Table 1" descriptive statistics from published papers. + +**Example scenario:** A paper reports: + +- Never smokers: 50% +- Former smokers: 30% +- Current smokers: 17% +- Don't know: 3% + +By setting these proportions in variable_details.csv, your mock data will match the published distribution. + +## Output data types (rType) + +The `rType` column in variables.csv controls the R data type of the output: + +### For categorical variables + +**factor (recommended):** + +- Preserves category levels +- Required for statistical modeling +- Example: smoking status + +**character:** + +- Plain text representation +- Use for IDs or non-analyzable categories +- Example: participant ID, study site + +### For continuous variables + +**integer:** + +- Whole numbers only +- Use for counts, age in years +- Example: age, number of children + +**double:** + +- Decimal precision +- Use for measurements requiring precision +- Example: weight, blood pressure, lab values + +**Example comparison:** + +```{r} +#| label: compare-age-weight +# Age: integer (no decimals) +head(age$age) + +# Weight: double (decimal precision) +head(weight$weight) +``` + +## Checking generated data + +Always verify that generated data matches your expectations: + +### For categorical variables + +```{r} +#| label: check-categorical +# Check factor levels +levels(smoking$smoking) + +# Check proportions +prop.table(table(smoking$smoking)) + +# Verify data type +class(smoking$smoking) +``` + +### For continuous variables + +```{r} +#| label: check-continuous +# Check range +range(age$age, na.rm = TRUE) + +# Check distribution parameters +mean(age$age, na.rm = TRUE) +sd(age$age, na.rm = TRUE) + +# Verify data type +class(age$age) +``` + +**Validation checklist:** + +- [ ] Proportions sum to ~1.0 (categorical) +- [ ] Values within expected range (continuous) +- [ ] Correct data type (factor, integer, double) +- [ ] Sample size matches n parameter +- [ ] Distribution shape looks reasonable (histogram) + +## Key concepts summary + +| Concept | Implementation | Details | +|---------|----------------|---------| +| **Categorical variables** | `create_cat_var()` | Discrete categories with proportions | +| **Continuous variables** | `create_con_var()` | Numeric measurements with distributions | +| **Proportions** | In variable_details.csv | Must sum to 1.0 for categorical | +| **Distributions** | normal, uniform | Specified in variables.csv | +| **Output types** | rType column | factor, character, integer, double | +| **Metadata validation** | Automatic | Proportions, ranges, types checked | +| **Batch generation** | `create_mock_data()` | Multiple variables at once | + +## What you learned + +In this tutorial, you learned: + +- **Categorical variables:** Using `create_cat_var()` to generate variables with discrete categories +- **Proportions:** How to specify and validate category distributions +- **Continuous variables:** Using `create_con_var()` to generate numeric measurements +- **Distributions:** Normal and uniform distributions for continuous data +- **Output types:** Choosing appropriate rType (factor, integer, double) for each variable +- **Metadata structure:** How variables.csv and variable_details.csv work together +- **Individual vs batch:** When to use single-variable functions vs `create_mock_data()` +- **Validation:** Checking that generated data matches metadata specifications + +## Next steps + +**Continue learning:** + +- [Date variables](tutorial-dates.html) - Temporal data and event times +- [Survival data](tutorial-survival-data.html) - Competing risks and censoring +- [Missing data](tutorial-missing-data.html) - Survey missing codes (NA::a vs NA::b) +- [Garbage data](tutorial-garbage-data.html) - Data quality testing + +**Reference:** + +- [Configuration reference](reference-config.html) - Complete metadata schema +- [Getting started](getting-started.html) - Overview and first examples diff --git a/vignettes/tutorial-dates.qmd b/vignettes/tutorial-dates.qmd new file mode 100644 index 0000000..f1ba7bc --- /dev/null +++ b/vignettes/tutorial-dates.qmd @@ -0,0 +1,631 @@ +--- +title: "Working with date variables" +format: html +vignette: > + %\VignetteIndexEntry{Working with date variables} + %\VignetteEngine{quarto::html} + %\VignetteEncoding{UTF-8} +--- + +```{r} +#| label: setup +#| include: false +# Load package - works in both local dev and pkgdown build +if (file.exists("../DESCRIPTION")) { + devtools::load_all("../", quiet = TRUE) +} else { + library(MockData) +} +``` + +::: {.vignette-about} +**About this vignette:** This tutorial teaches you how to generate date variables with realistic temporal patterns. You'll learn interval notation, distribution options, source format simulation, and data quality testing. All code examples run during vignette build to ensure accuracy. +::: + +## Overview + +This tutorial teaches temporal data generation in MockData. You'll learn how to create date variables for: + +- **Cohort entry dates** (index dates, baseline dates) +- **Event dates** (death, diagnosis, hospital admission) +- **Administrative dates** (censoring dates, data freeze dates) +- **Temporal data quality testing** (out-of-period dates for validation) + +Date variables use interval notation to specify ranges and support three distributions (uniform, Gompertz, exponential) for realistic temporal patterns. + +## Basic date variable setup + +### Configuration structure + +Date variables use the same two-file structure as other variables, with **interval notation** for date ranges: + +**variables.csv:** + +| uid | variable | role | variableType | variableLabel | position | +|-----|----------|------|--------------|---------------|----------| +| ices_v01 | interview_date | enabled | Date | Interview date | 1 | + +**variable_details.csv:** + +| uid | uid_detail | variable | recStart | catLabel | +|-----|------------|----------|----------|----------| +| ices_v01 | ices_d001 | interview_date | [2001-01-01,2005-12-31] | Interview date range | + +**Key points:** + +- Use **interval notation** in `recStart`: `[start_date,end_date]` (square brackets, comma-separated, ISO format) +- Dates use ISO format: YYYY-MM-DD +- Single row per date variable (not separate rows for start/end) +- All date variables from minimal-example use `ices_v*` namespace + +### Generating date variables + +```{r} +#| label: load-metadata-generate-dates +#| warning: false +#| message: false + +# Load minimal-example metadata +variables <- read.csv( + system.file("extdata/minimal-example/variables.csv", package = "MockData"), + stringsAsFactors = FALSE +) + +variable_details <- read.csv( + system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + stringsAsFactors = FALSE +) + +# Generate interview dates +interview_data <- create_mock_data( + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 100, + seed = 123 +) + +# View interview date distribution +head(interview_data$interview_date) +summary(as.Date(interview_data$interview_date)) +``` + +**Result:** 100 interview dates uniformly distributed between 2001-01-01 and 2005-12-31 (matching the minimal-example metadata). + +**Note:** The interval notation in `recStart` specifies the complete date range in a single row. + +## Generating single date variables + +For interactive development or testing, use `create_date_var()` to generate a single date variable without creating an entire dataset: + +```{r} +#| label: single-date-variable +#| warning: false +#| message: false + +# Generate just the interview_date variable +interview_dates_only <- create_date_var( + var = "interview_date", + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 100, + seed = 456 +) + +# View the result (single-column data frame) +head(interview_dates_only) +summary(as.Date(interview_dates_only$interview_date)) +``` + +**Use cases for create_date_var():** + +- Testing date specifications interactively +- Generating single variables for specific tests +- Exploring distribution patterns +- Quick prototyping before batch generation + +**For complete datasets:** Use `create_mock_data()` to generate all variables at once (as shown in the previous section). + +## Date ranges and distributions + +### Distribution options + +MockData supports three distributions for date generation: + +**Uniform (default):** All dates equally likely across the range + +- Use for: Cohort accrual with constant enrollment, administrative dates +- Example: `distribution = "uniform"` + +**Gompertz:** Useful for survival/event times with higher events near end of range + +- Use for: Typical survival patterns +- Example: `distribution = "gompertz"` + +**Exponential:** More events near start of range + +- Use for: Time-to-event with early concentration +- Example: `distribution = "exponential"` + +**Note:** Distribution types are specified in the `distribution` column of variables.csv. For interactive generation (single variable functions), you can override the metadata distribution. + +### Comparing distributions + +Different distributions create different temporal patterns. Here's how they compare using the same date range: + +```{r} +#| label: uniform-distribution +#| warning: false +#| message: false + +# Generate dates with uniform distribution (default) +uniform_dates <- create_date_var( + var = "interview_date", + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 1000, + seed = 100 +) + +# Calculate median date +median_uniform <- median(as.Date(uniform_dates$interview_date)) + +# View median +median_uniform +``` + +The uniform distribution produces a median date near the middle of the range (2001-01-01 to 2005-12-31), as expected for evenly distributed dates. + +**Distribution patterns:** + +| Distribution | Median location | Best for | +|--------------|-----------------|----------| +| **Uniform** | Middle of range (~2003) | Calendar dates, recruitment periods, random events | +| **Gompertz** | Shifted toward end (~2004-2005) | Mortality data, age-related events | +| **Exponential** | Shifted toward start (~2001-2002) | First diagnosis, early treatment, rapid events | + +**Choosing a distribution:** + +1. **Start with uniform** for calendar dates without known temporal patterns +2. **Use Gompertz** for mortality and age-related outcomes +3. **Use exponential** for first-event or early-diagnosis scenarios + +The distribution is read from the `distribution` column in variables.csv, making it easy to specify different patterns for different date variables. + +## Event proportions for survival data + +When generating event dates (death, diagnosis, hospitalization), not all individuals experience the event during follow-up. The `event_prop` parameter controls what proportion of individuals experience the event versus being censored (no event observed). + +### Basic event_prop example + +Let's generate death dates where only 30% of individuals die during the study period: + +```{r} +#| label: event-prop-example +#| warning: false +#| message: false + +# Create simple death date configuration +death_vars <- data.frame( + uid = "death_v1", + variable = "death_date", + role = "enabled", + variableType = "Date", + rType = "date", + position = 1, + distribution = "gompertz", + rate = 1e-04, + shape = 0.1, + followup_min = 0, + followup_max = 3650, + event_prop = 0.3, # 30% experience death + sourceFormat = "analysis", + stringsAsFactors = FALSE +) + +death_details <- data.frame( + uid = "death_v1", + uid_detail = "death_v1_d1", + variable = "death_date", + recStart = "[2001-01-01,2005-12-31]", + recEnd = "copy", + catLabel = "Death dates", + stringsAsFactors = FALSE +) + +# Generate death dates (requires anchor_date for survival variables) +anchor_dates <- as.Date("2001-01-01") + sample(0:1826, 100, replace = TRUE) +df_mock <- data.frame(anchor_date = anchor_dates) + +death_data <- create_date_var( + var = "death_date", + databaseStart = "tutorial", + variables = death_vars, + variable_details = death_details, + df_mock = df_mock, + n = 100, + seed = 456 +) + +# Check event proportion +n_deaths <- sum(!is.na(death_data$death_date)) +n_censored <- sum(is.na(death_data$death_date)) +observed_prop <- n_deaths / nrow(death_data) +``` + +**Results:** + +- Deaths observed: `r n_deaths` out of `r nrow(death_data)` (`r round(observed_prop * 100, 1)`%) +- Censored (no death): `r n_censored` (`r round((n_censored / nrow(death_data)) * 100, 1)`%) +- Expected: 30% deaths (from `event_prop = 0.3`) + +**Sample of first 10 observations (showing NA for censored cases):** + +```{r} +#| label: show-death-data-sample +# Display first 10 rows to show mixture of dates and NA values +head(death_data, 10) +``` + +**Key concepts:** + +- **event_prop = 0.3**: 30% of individuals experience the event (get a date) +- **Censored observations**: The remaining 70% have `NA` for death_date (event not observed) +- **Survival analysis use**: `event_prop` simulates realistic cohort data where not everyone experiences the outcome + +**When to use event_prop:** + +- Death dates in cohort studies +- Disease incidence dates +- Hospital admission dates +- Any time-to-event outcome where censoring occurs + +For complete survival data examples with competing risks and multiple event types, see the [Survival data tutorial](tutorial-survival-data.html). + +## Source data format: simulating raw data imports + +By default, MockData generates dates as R `Date` objects (analysis-ready format). However, real survey data comes in different formats depending on the source. The `sourceFormat` column in variables.csv controls how dates are generated to simulate different raw data formats. + +### Available sourceFormat values + +MockData supports three sourceFormat formats specified in the variables.csv metadata: + +**analysis (default)**: R Date objects ready for analysis + +**csv**: Character strings in ISO format (YYYY-MM-DD), simulating dates from CSV files + +**sas**: Numeric values (days since 1960-01-01), simulating SAS date format + +### Demonstrating sourceFormat formats + +The `sourceFormat` column in variables.csv controls the output format. Let's generate the same date variable in all three formats by modifying the metadata: + +```{r} +#| label: format-analysis +#| warning: false +#| message: false + +# Format 1: analysis (R Date objects) - DEFAULT +# Variables already has sourceFormat = "analysis" by default +dates_analysis <- create_date_var( + var = "interview_date", + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 5, + seed = 100 +) + +# Check the class and values +class(dates_analysis$interview_date) +head(dates_analysis$interview_date, 3) +``` + +```{r} +#| label: format-csv +#| warning: false +#| message: false + +# Format 2: csv (character strings) +vars_csv <- variables +vars_csv$sourceFormat <- "csv" + +dates_csv <- create_date_var( + var = "interview_date", + databaseStart = "minimal-example", + variables = vars_csv, + variable_details = variable_details, + n = 5, + seed = 100 # Same seed = same underlying dates +) + +# Check the class and values +class(dates_csv$interview_date) +head(dates_csv$interview_date, 3) +``` + +```{r} +#| label: format-sas +#| warning: false +#| message: false + +# Format 3: sas (numeric days since 1960-01-01) +vars_sas <- variables +vars_sas$sourceFormat <- "sas" + +dates_sas <- create_date_var( + var = "interview_date", + databaseStart = "minimal-example", + variables = vars_sas, + variable_details = variable_details, + n = 5, + seed = 100 # Same seed = same underlying dates +) + +# Check the class and values +class(dates_sas$interview_date) +head(dates_sas$interview_date, 3) +``` + +**Key insight:** The same underlying dates are represented in three different formats. Using the same seed (100) ensures all three formats contain the same dates, just stored differently. + +### Converting between formats + +All three formats represent identical dates. You can convert between them: + +```{r} +#| label: format-conversion +#| warning: false +#| message: false + +# Convert CSV format (character) to Date +csv_to_date <- as.Date(dates_csv$interview_date) + +# Convert SAS format (numeric) to Date +sas_to_date <- as.Date(dates_sas$interview_date, origin = "1960-01-01") + +# Verify all represent the same dates +all(csv_to_date == dates_analysis$interview_date) +all(sas_to_date == dates_analysis$interview_date) +``` + +### Use case: testing harmonization pipelines + +The `sourceFormat` metadata column is particularly useful for testing date parsing and harmonization code. Generate mock data in the format matching your raw source files: + +```{r} +#| label: harmonization-example +#| eval: false + +# Example: Testing harmonization from CSV source +vars_csv_source <- variables +vars_csv_source$sourceFormat <- "csv" + +# Generate mock data in CSV format +mock_csv <- create_mock_data( + databaseStart = "minimal-example", + variables = vars_csv_source, + variable_details = variable_details, + n = 1000 +) + +# Test your harmonization logic +library(dplyr) +harmonized <- mock_csv %>% + mutate( + # Parse character dates (your harmonization code) + interview_date = as.Date(interview_date, format = "%Y-%m-%d"), + + # Calculate derived variables + days_from_start = as.numeric(interview_date - as.Date("2001-01-01")) + ) + +# Verify harmonization succeeded +stopifnot(inherits(harmonized$interview_date, "Date")) +stopifnot(all(harmonized$days_from_start >= 0, na.rm = TRUE)) +``` + +### Why this matters + +Real survey data doesn't arrive as clean R Date objects: + +- **CSV files**: Dates are character strings that need parsing +- **SAS files**: Dates may be numeric (if haven doesn't auto-convert) +- **SPSS/Stata files**: Various numeric formats with different epochs + +Setting `sourceFormat` in variables.csv lets you generate mock data that matches your actual raw data format, allowing you to test your entire harmonization pipeline. + +## Data quality for dates + +### Future dates + +Simulate data entry errors where dates are in the future using **garbage_high** parameters in variables.csv: + +```{r} +#| label: garbage-future-dates +#| warning: false +#| message: false +# Create configuration with future date garbage +birth_config <- data.frame( + uid = "birth_date_v1", + variable = "birth_date", + role = "enabled", + variableType = "Date", + rType = "date", + position = 1, + garbage_high_prop = 0.02, + garbage_high_range = "[2026-01-01,2030-12-31]", + stringsAsFactors = FALSE +) + +birth_details <- data.frame( + uid = "birth_date_v1", + uid_detail = "birth_date_v1_d1", + variable = "birth_date", + recStart = "[1950-01-01,2010-12-31]", + catLabel = "Valid birth dates", + stringsAsFactors = FALSE +) + +# Write to temporary files +temp_dir <- tempdir() +birth_config_path <- file.path(temp_dir, "birth_config.csv") +birth_details_path <- file.path(temp_dir, "birth_details.csv") +write.csv(birth_config, birth_config_path, row.names = FALSE) +write.csv(birth_details, birth_details_path, row.names = FALSE) + +# Generate birth dates with future date garbage +birth_data <- create_mock_data( + databaseStart = "tutorial", + variables = birth_config_path, + variable_details = birth_details_path, + n = 1000, + seed = 789 +) + +# Check for future dates (after 2025) +future_threshold <- as.Date("2025-12-31") +n_future <- sum(birth_data$birth_date > future_threshold, na.rm = TRUE) +prop_future <- n_future / nrow(birth_data) +future_dates_sample <- head(sort(birth_data$birth_date[birth_data$birth_date > future_threshold]), 5) +``` + +**Result:** `r n_future` birth dates (`r round(prop_future * 100, 1)`%) are in the future (after 2025-12-31), which is impossible for current data. Sample of future dates: `r paste(as.character(future_dates_sample), collapse = ", ")`. + +**Key insight:** Garbage data is now specified at the **variable level** in variables.csv, not in variable_details.csv. + +### Past dates (temporal violations) + +Simulate impossibly old dates using **garbage_low** parameters: + +```{r} +#| label: garbage-past-dates +#| warning: false +#| message: false +# Create configuration with old date garbage +diag_config <- data.frame( + uid = "diagnosis_date_v1", + variable = "diagnosis_date", + role = "enabled", + variableType = "Date", + rType = "date", + position = 1, + garbage_low_prop = 0.03, + garbage_low_range = "[1850-01-01,1900-12-31]", + stringsAsFactors = FALSE +) + +diag_details <- data.frame( + uid = "diagnosis_date_v1", + uid_detail = "diagnosis_date_v1_d1", + variable = "diagnosis_date", + recStart = "[2000-01-01,2020-12-31]", + catLabel = "Valid diagnosis dates", + stringsAsFactors = FALSE +) + +# Write to temporary files +temp_dir <- tempdir() +diag_config_path <- file.path(temp_dir, "diag_config.csv") +diag_details_path <- file.path(temp_dir, "diag_details.csv") +write.csv(diag_config, diag_config_path, row.names = FALSE) +write.csv(diag_details, diag_details_path, row.names = FALSE) + +# Generate diagnosis dates with old date garbage +diag_data <- create_mock_data( + databaseStart = "tutorial", + variables = diag_config_path, + variable_details = diag_details_path, + n = 1000, + seed = 456 +) + +# Check for impossibly old dates (before 1950) +old_threshold <- as.Date("1950-01-01") +n_old <- sum(diag_data$diagnosis_date < old_threshold, na.rm = TRUE) +prop_old <- n_old / nrow(diag_data) +old_dates_sample <- head(sort(diag_data$diagnosis_date[diag_data$diagnosis_date < old_threshold]), 5) +``` + +**Result:** `r n_old` diagnosis dates (`r round(prop_old * 100, 1)`%) are from before 1950-01-01 (1850-1900 range), which is unrealistic for modern medical data. Sample of old dates: `r paste(as.character(old_dates_sample), collapse = ", ")`. + +### Use cases for garbage dates + +- **Testing validation pipelines:** Ensure your code catches impossible dates +- **Training analysts:** Show examples of real-world data quality issues +- **Data cleaning scripts:** Test date range checks and filtering logic + +**Note:** For complete examples of garbage date generation integrated into metadata files, see the [minimal-example configuration files](https://github.com/Big-Life-Lab/mockData/tree/main/inst/extdata/minimal-example). + +## Checking generated dates + +After generating dates, validate the results: + +```{r} +#| label: validate-dates +#| warning: false +#| message: false + +# Check interview date range +interview_dates <- as.Date(interview_data$interview_date) + +# Calculate summary statistics +date_min <- min(interview_dates, na.rm = TRUE) +date_max <- max(interview_dates, na.rm = TRUE) +n_missing <- sum(is.na(interview_dates)) + +# Validate dates are within expected range (from metadata) +expected_min <- as.Date("2001-01-01") +expected_max <- as.Date("2005-12-31") +all_valid <- all(interview_dates >= expected_min & + interview_dates <= expected_max, + na.rm = TRUE) +``` + +**Validation results:** + +- Date range: `r as.character(date_min)` to `r as.character(date_max)` +- Missing dates: `r n_missing` +- All dates within expected range (2001-01-01 to 2005-12-31): `r all_valid` + +This validation confirms the generated dates match the metadata specifications. + +## Key concepts summary + +| Concept | Implementation | Details | +|-------------------|---------------------------------|-------------------| +| **Date ranges** | Interval notation in `recStart` | `[2001-01-01,2005-12-31]` format (ISO dates) | +| **Distributions** | Uniform, Gompertz, Exponential | Specified in `distribution` column of variables.csv | +| **Event proportions** | `event_prop` column in variables.csv | Controls % experiencing event vs. censored (NA) | +| **Garbage dates** | `garbage_low_prop/range`, `garbage_high_prop/range` | Specified in variables.csv for data quality testing | +| **Validation** | Check ranges and distributions | Use `summary()`, `min()`, `max()` after generation | +| **Source formats** | `sourceFormat` column in variables.csv | Values: "csv" (character), "sas" (numeric), "analysis" (Date) | + +## What you learned + +In this tutorial, you learned: + +- **Date configuration basics:** How to specify date ranges using interval notation in variable_details.csv +- **Single variable generation:** Using `create_date_var()` for interactive development and testing +- **Distribution options:** Uniform, Gompertz, and exponential distributions for realistic temporal patterns +- **Distribution selection:** When to use each distribution type for different use cases +- **Event proportions:** Using `event_prop` to control the proportion of individuals experiencing events versus being censored +- **Source data formats:** Using the `sourceFormat` metadata column to simulate different raw data formats (csv, sas, analysis) +- **Format conversion:** How the same dates can be represented in different formats for harmonization testing +- **Data quality testing:** Generating corrupt future/past dates using `garbage_low` and `garbage_high` parameters for validation pipeline testing +- **Validation:** Checking generated dates are within expected ranges and match metadata specifications + +## Next steps + +**Tutorials:** + +- [Missing data](tutorial-missing-data.html) - Survey missing data codes and patterns +- [Garbage data](tutorial-garbage-data.html) - Comprehensive data quality testing +- [Getting started](getting-started.html) - Review MockData fundamentals + +**Reference:** + +- [Configuration reference](reference-config.html) - Complete metadata schema specification +- [Advanced topics](advanced-topics.html) - Technical details on distributions and workflows \ No newline at end of file diff --git a/vignettes/tutorial-garbage-data.qmd b/vignettes/tutorial-garbage-data.qmd new file mode 100644 index 0000000..eb9cff7 --- /dev/null +++ b/vignettes/tutorial-garbage-data.qmd @@ -0,0 +1,664 @@ +--- +title: "Generating garbage data for validation testing" +format: html +vignette: > + %\VignetteIndexEntry{Generating garbage data for validation testing} + %\VignetteEngine{quarto::html} + %\VignetteEncoding{UTF-8} +--- + +```{r} +#| label: setup +#| include: false +# Load package - works in both local dev and pkgdown build +if (file.exists("../DESCRIPTION")) { + devtools::load_all("../", quiet = TRUE) +} else { + library(MockData) +} +``` + +::: {.vignette-about} +**About this vignette:** This tutorial teaches you how to generate intentionally invalid "garbage" data for testing validation pipelines. You'll learn how to create realistic data quality issues across categorical, continuous, date, and survival variables, then verify your validation logic catches them correctly. All code examples run during vignette build to ensure accuracy. +::: + +## Why generate garbage data? + +Data validation is important for research quality, but how do you know your validation rules actually work? The best approach is to generate mock data with known quality issues, run your validation pipeline, and verify it catches exactly what you expect. + +Health research projects often receive large datasets and need robust validation pipelines to catch data quality issues before analysis. By generating mock data with intentional errors, you can: + +1. **Test validation logic** before applying it to real data +2. **Document expected error rates** for different quality checks +3. **Train new team members** on common data quality patterns +4. **Benchmark validation performance** with known error proportions + +Let's start with a motivating example. Suppose you're validating smoking status coding in a health survey dataset: + +```{r} +#| label: load-metadata-generate-clean +#| message: false +#| warning: false + +# Load minimal-example metadata +variable_details <- read.csv( + system.file("extdata/minimal-example/variable_details.csv", + package = "MockData"), + stringsAsFactors = FALSE +) + +variables <- read.csv( + system.file("extdata/minimal-example/variables.csv", + package = "MockData"), + stringsAsFactors = FALSE +) + +# Generate smoking variable WITHOUT garbage (clean data only) +df_clean <- data.frame() +smoking_clean <- create_cat_var( + var = "smoking", + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + df_mock = df_clean, + n = 1000, + seed = 123 +) + +# Check for invalid codes (valid codes are 1=Never, 2=Former, 3=Current, 7=Don't know) +# IMPORTANT: Exclude NA values - they are legitimate missing data, not garbage +valid_codes <- c("1", "2", "3", "7") +invalid_clean <- sum(!smoking_clean$smoking %in% valid_codes & !is.na(smoking_clean$smoking)) +``` + +With clean data generated from metadata, your validation check finds `r invalid_clean` invalid codes. This confirms the data is clean, but how do you know your validation logic actually works? + +## Unified garbage approach + +MockData uses a unified garbage generation pattern across **all variable types** (categorical, continuous, date, and survival): + +**Core pattern:** +- `garbage_low_prop` + `garbage_low_range` for values below valid range +- `garbage_high_prop` + `garbage_high_range` for values above valid range +- Specified in variables metadata (or added with `add_garbage()` helper) + +**Helper function for easy setup:** + +```r +# Add garbage to any variable type +vars_with_garbage <- add_garbage(variables, "smoking", + garbage_low_prop = 0.02, garbage_low_range = "[-2, 0]") +``` + +## Categorical garbage patterns + +Categorical variables can have several types of garbage data. The most common are: + +**Invalid codes**: Values that aren't in the valid category set. Examples: ".a", "NA", "missing", numeric codes outside the defined range. + +**Type mismatches**: Wrong data types. Example: Numeric codes stored as floats (1.0 instead of 1). + +**Encoding issues**: Character encoding problems. Example: "Montr\u00e9al" becomes "Montr\ufffdal". + +### Categorical validation logic + +Let's demonstrate the validation logic for categorical variables. This example shows how to properly validate categorical data by excluding NA values (which represent legitimate missing data, not garbage): + +```{r} +#| label: validate-categorical-clean +#| message: false +#| warning: false + +# Generate smoking variable (clean data from metadata) +df_smoking <- data.frame() +smoking_clean2 <- create_cat_var( + var = "smoking", + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + df_mock = df_smoking, + n = 2000, + seed = 789 +) + +# Validation: check for invalid codes +# Get valid codes from metadata for smoking +smoking_details <- variable_details[variable_details$variable == "smoking", ] +valid_smoking_codes <- unique(smoking_details$recStart[!is.na(smoking_details$recStart)]) + +# CRITICAL: Exclude NA values - they are legitimate missing data, not garbage +# Incorrect: invalid_smoking <- !smoking_clean2$smoking %in% valid_smoking_codes (counts NA as garbage) +# Correct: +invalid_smoking <- !smoking_clean2$smoking %in% valid_smoking_codes & !is.na(smoking_clean2$smoking) +n_invalid <- sum(invalid_smoking) +invalid_pct <- round(n_invalid / nrow(smoking_clean2) * 100, 1) +``` + +```{r} +#| label: count-na-values +#| echo: false + +# Count NA values separately +n_na <- sum(is.na(smoking_clean2$smoking)) +na_pct <- round(n_na / nrow(smoking_clean2) * 100, 1) +``` + +Validation results: + +- **Total records**: `r nrow(smoking_clean2)` +- **Invalid codes found**: `r n_invalid` (`r invalid_pct`%) +- **NA values (legitimate missing)**: `r n_na` (`r na_pct`%) + +Since we generated clean data without garbage specification, we correctly find 0 invalid codes. The NA values represent legitimate missing data patterns from the metadata proportions, not garbage. + +### Generating categorical garbage + +Now let's generate smoking data with intentional invalid codes using these garbage functions. For smoking (valid codes: 1, 2, 3, 7), we'll generate invalid codes below the valid range: + +```{r} +#| label: generate-categorical-garbage +#| message: false +#| warning: false + +# Add garbage to smoking using helper function +vars_smoking_garbage <- add_garbage(variables, "smoking", + garbage_low_prop = 0.03, garbage_low_range = "[-2, 0]") + +# Generate smoking with garbage +smoking_garbage <- create_cat_var( + var = "smoking", + databaseStart = "minimal-example", + variables = vars_smoking_garbage, # Uses modified variables with garbage + variable_details = variable_details, + n = 1000, + seed = 999 +) + +# Validate: check for invalid codes +# Get valid codes from metadata +smoking_details_check <- variable_details[variable_details$variable == "smoking", ] +valid_codes_check <- unique(smoking_details_check$recStart[!is.na(smoking_details_check$recStart)]) + +# Find garbage values (exclude NA - legitimate missing data) +smoking_values <- as.numeric(as.character(smoking_garbage$smoking)) +garbage_smoking <- smoking_values[smoking_values < 1 & !is.na(smoking_values)] +n_garbage_smoking <- length(garbage_smoking) +garbage_smoking_pct <- round(n_garbage_smoking / nrow(smoking_garbage) * 100, 1) +``` + +**Validation results:** + +- **Total records**: `r nrow(smoking_garbage)` +- **Garbage values found**: `r n_garbage_smoking` (`r garbage_smoking_pct`%) +- **Expected**: ~3% (from garbage_low_prop = 0.03) +- **Garbage codes generated**: `r paste(sort(unique(garbage_smoking)), collapse = ", ")` + +These functions generated invalid categorical codes (-2, -1, 0) by treating the valid codes as ordinal. This allows validation testing without pre-defining specific invalid category rows in metadata. + +### Alternative: Direct metadata modification + +Instead of using `add_garbage()`, you can modify the variables data frame directly: + +```{r} +#| label: categorical-direct-modification +#| message: false +#| warning: false + +# Direct modification approach (equivalent to add_garbage) +vars_smoking_direct <- variables +vars_smoking_direct$garbage_low_prop[vars_smoking_direct$variable == "smoking"] <- 0.03 +vars_smoking_direct$garbage_low_range[vars_smoking_direct$variable == "smoking"] <- "[-2, 0]" + +# Generate smoking with garbage (using directly modified variables) +smoking_direct <- create_cat_var( + var = "smoking", + databaseStart = "minimal-example", + variables = vars_smoking_direct, + variable_details = variable_details, + n = 1000, + seed = 999 # Same seed as helper example +) + +# Validate: should match add_garbage() results +smoking_direct_values <- as.numeric(as.character(smoking_direct$smoking)) +garbage_direct <- smoking_direct_values[smoking_direct_values < 1 & !is.na(smoking_direct_values)] +``` + +Both approaches produce identical results. Use `add_garbage()` for cleaner code or direct modification when building programmatic workflows. + +## Continuous variable garbage + +Continuous variables have different garbage patterns than categorical variables. Common issues include: + +**Out-of-range values**: Numbers outside biologically/logically plausible ranges. Example: Age = 250 years. + +**Type garbage data**: Values stored as wrong type. Example: Age stored as character "45.5" instead of numeric. + +**Precision issues**: Inappropriate decimal places. Example: Age = 45.7829 (overly precise). + +MockData generates continuous garbage using the same pattern: + +- Use `garbage_low_prop` + `garbage_low_range` for values below valid range +- Use `garbage_high_prop` + `garbage_high_range` for values above valid range +- Specify exact ranges using interval notation (e.g., `[-10, 0]` or `[200, 300]`) + +### Out-of-range values with helper function + +Let's generate age data with out-of-range garbage. The valid range is 18-100 years, so we'll add high-range garbage above 100 using the `add_garbage()` helper: + +```{r} +#| label: generate-continuous-garbage-helper +#| message: false +#| warning: false + +# Add high-range garbage to age using helper function +vars_age_garbage <- add_garbage(variables, "age", + garbage_high_prop = 0.02, garbage_high_range = "[120, 200]") + +# Generate age data with garbage +df_age <- data.frame() +age_garbage <- create_con_var( + var = "age", + databaseStart = "minimal-example", + variables = vars_age_garbage, + variable_details = variable_details, + df_mock = df_age, + n = 2000, + seed = 200 +) + +# CORRECT VALIDATION: Extract valid range and missing codes from metadata +age_details <- variable_details[variable_details$variable == "age", ] + +# Get valid range from metadata (where recEnd = "copy") +valid_range_row <- age_details[age_details$recEnd == "copy", ] +# Parse interval notation [18,100] to extract min and max +library(stringr) +range_str <- valid_range_row$recStart[1] +range_values <- as.numeric(str_extract_all(range_str, "\\d+")[[1]]) +valid_min <- range_values[1] # 18 +valid_max <- range_values[2] # 100 + +# Get missing codes from metadata (where recEnd contains "NA::") +missing_codes_rows <- age_details[grepl("NA::", age_details$recEnd), ] +missing_codes <- as.numeric(missing_codes_rows$recStart) + +# Validate: Garbage should be high-range (> 100) AND not a missing code +is_garbage <- age_garbage$age > valid_max & + !age_garbage$age %in% missing_codes & + !is.na(age_garbage$age) +n_garbage <- sum(is_garbage) +garbage_pct <- round(n_garbage / nrow(age_garbage) * 100, 1) + +# Display actual garbage values +garbage_values <- age_garbage$age[is_garbage] +``` + +**Validation results:** + +- **Total records**: `r nrow(age_garbage)` +- **Garbage values found**: `r n_garbage` (`r garbage_pct`%) +- **Expected**: ~2% (from garbage_high_prop = 0.02) +- **Sample garbage values**: `r paste(head(sort(garbage_values), 8), collapse = ", ")` + +```{r} +#| label: calculate-age-ranges +#| echo: false + +# Calculate ranges for display +max_age <- max(age_garbage$age[age_garbage$age < 900], na.rm = TRUE) +min_age <- min(age_garbage$age, na.rm = TRUE) +``` + +**Value ranges:** + +- **Overall range**: `r round(min_age, 1)` to `r round(max_age, 1)` years +- **Valid range (from metadata)**: `r valid_min` to `r valid_max` +- **Missing codes (from metadata)**: `r paste(missing_codes, collapse = ", ")` + +**Key validation principle:** Garbage values are high-range (> 100) AND not missing codes (997, 998, 999). This confirms the validator correctly excludes legitimate missing data from garbage detection. + +### Direct modification approach + +Instead of using `add_garbage()`, you can modify the variables data frame directly. This approach is useful when building programmatic workflows: + +```{r} +#| label: continuous-direct-modification +#| message: false +#| warning: false + +# Direct modification approach - add low-range garbage (negative ages) +vars_age_direct <- variables +vars_age_direct$garbage_low_prop[vars_age_direct$variable == "age"] <- 0.02 +vars_age_direct$garbage_low_range[vars_age_direct$variable == "age"] <- "[-10, 10]" + +# Generate age data with low-range garbage +df_age2 <- data.frame() +age_direct <- create_con_var( + var = "age", + databaseStart = "minimal-example", + variables = vars_age_direct, + variable_details = variable_details, + df_mock = df_age2, + n = 2000, + seed = 201 +) + +# Validate: check for low-range garbage (below minimum valid age) +low_range_garbage <- age_direct$age < 18 & !age_direct$age %in% c(997, 998, 999) +n_low_garbage <- sum(low_range_garbage, na.rm = TRUE) +``` + +```{r} +#| label: calculate-low-garbage-percentages +#| echo: false + +low_garbage_pct <- round(n_low_garbage / nrow(age_direct) * 100, 1) +min_low_garbage <- if(n_low_garbage > 0) min(age_direct$age[low_range_garbage], na.rm = TRUE) else NA +``` + +The validator detects: + +- **Low-range garbage (< 18)**: `r n_low_garbage` (`r low_garbage_pct`%) +- **Minimum garbage value**: `r ifelse(is.na(min_low_garbage), "none", round(min_low_garbage, 1))` + +Both approaches (`add_garbage()` helper and direct modification) produce identical results when using the same parameters. + +## Date variable garbage + +Date variables use the same garbage generation pattern as categorical and continuous variables. Common date quality issues include: + +**Out-of-range dates**: Dates outside valid collection periods. Example: Interview date in 2050. + +**Impossible dates**: Dates that violate temporal logic. Example: Death date before birth date. + +**Format issues**: Dates stored incorrectly. Example: "2020-13-45" (invalid month/day). + +### Generating date garbage with helper function + +Let's generate interview dates with some far-future garbage dates to test validation logic: + +```{r} +#| label: generate-date-garbage-helper +#| message: false +#| warning: false + +# Add high-range garbage to interview_date (future dates for testing) +vars_date_garbage <- add_garbage(variables, "interview_date", + garbage_high_prop = 0.03, garbage_high_range = "[2030-01-01, 2050-12-31]") + +# Generate interview dates with garbage +df_dates <- data.frame() +interview_garbage <- create_date_var( + var = "interview_date", + databaseStart = "minimal-example", + variables = vars_date_garbage, + variable_details = variable_details, + df_mock = df_dates, + n = 1000, + seed = 300 +) + +# Validate: check for future dates (impossible interviews) +future_threshold <- as.Date("2030-01-01") +future_interviews <- interview_garbage$interview_date > future_threshold +n_future <- sum(future_interviews, na.rm = TRUE) +future_pct <- round(n_future / nrow(interview_garbage) * 100, 1) +``` + +**Validation results:** + +- **Total records**: `r nrow(interview_garbage)` +- **Future interview dates**: `r n_future` (`r future_pct`%) +- **Expected**: ~3% (from garbage_high_prop = 0.03) + +### Direct modification for date variables + +You can also modify the variables data frame directly for date garbage: + +```{r} +#| label: date-direct-modification +#| message: false +#| warning: false + +# Direct modification - add low-range garbage (past dates) +vars_date_direct <- variables +vars_date_direct$garbage_low_prop[vars_date_direct$variable == "interview_date"] <- 0.02 +vars_date_direct$garbage_low_range[vars_date_direct$variable == "interview_date"] <- "[1950-01-01, 1990-12-31]" + +# Generate with low-range garbage +interview_direct <- create_date_var( + var = "interview_date", + databaseStart = "minimal-example", + variables = vars_date_direct, + variable_details = variable_details, + n = 1000, + seed = 301 +) + +# Validate: check for very old dates +old_threshold <- as.Date("1990-12-31") +old_interviews <- interview_direct$interview_date <= old_threshold +n_old <- sum(old_interviews, na.rm = TRUE) +``` + +```{r} +#| label: calculate-old-percentages +#| echo: false + +old_pct <- round(n_old / nrow(interview_direct) * 100, 1) +``` + +Both approaches work identically for date variables: + +- **Old interview dates (≀ 1990)**: `r n_old` (`r old_pct`%) +- **Expected**: ~2% (from garbage_low_prop = 0.02) + +For more advanced date generation techniques, see the [Date variables tutorial](tutorial-dates.html). + +## Survival data garbage + +::: {.callout-note} +## Creating raw survival data for testing data cleaning pipelines + +The [Survival data tutorial](tutorial-survival-data.html) teaches how to create **clean, analysis-ready survival data** with correct temporal ordering. This section teaches how to create **raw survival data with temporal violations** for testing data quality and cleaning pipelines. + +Use this approach when you need to: +- Test temporal validation logic (death before entry, impossible dates) +- Train analysts to identify date sequence violations +- Validate data cleaning scripts that fix temporal inconsistencies +::: + +Survival analysis requires coordinated date validation across multiple time points. Garbage data helps test the complex validation rules for temporal consistency. + +Common survival data quality issues: + +**Date sequence violations**: Death before birth, death before interview + +**Impossible survival times**: Negative follow-up time, follow-up exceeding study period + +**Censoring inconsistencies**: Status indicates death but no death date recorded + +### Generating survival data with temporal violations + +The `prop_garbage` parameter in `create_wide_survival_data()` is deprecated. Instead, add garbage to individual date variables using these functions: + +```{r} +#| label: generate-survival-garbage +#| message: false +#| warning: false + +# Define metadata (pass full data frames) +surv_variables <- data.frame( + variable = c("study_entry", "death_date"), + variableType = c("Date", "Date"), + rType = c("date", "date"), + role = c("enabled", "enabled"), + distribution = c("uniform", "gompertz"), + rate = c(NA, 0.0001), + shape = c(NA, 0.1), + followup_min = c(NA, 30), + followup_max = c(NA, 3650), + event_prop = c(NA, 1.0), + sourceFormat = c("analysis", "analysis"), + stringsAsFactors = FALSE +) + +surv_variable_details <- data.frame( + variable = c("study_entry", "death_date"), + recStart = c("[2010-01-01,2015-12-31]", "[30,3650]"), + stringsAsFactors = FALSE +) + +# Add garbage to death_date (future dates for temporal violation testing) +surv_vars_with_garbage <- add_garbage(surv_variables, "death_date", + garbage_high_prop = 0.03, garbage_high_range = "[2030-01-01, 2099-12-31]") + +# Generate survival dates (create_date_var applies garbage automatically) +survival_dates <- create_wide_survival_data( + var_entry_date = "study_entry", + var_event_date = "death_date", + var_death_date = NULL, + var_ltfu = NULL, + var_admin_censor = NULL, + databaseStart = "test", + variables = surv_vars_with_garbage, # Uses modified variables with garbage + variable_details = surv_variable_details, + n = 2000, + seed = 400 +) + +# Validate: check for impossibly future death dates (temporal violation proxy) +future_threshold <- as.Date("2030-01-01") +future_deaths <- survival_dates$death_date > future_threshold +n_violations <- sum(future_deaths, na.rm = TRUE) +``` + +```{r} +#| label: calculate-violation-percentage +#| echo: false + +violation_pct <- round(n_violations / nrow(survival_dates) * 100, 1) +``` + +Validation detects `r n_violations` future death dates (`r violation_pct`%), approximately matching our 3% garbage specification. + +**Key points about survival garbage:** + +- `create_wide_survival_data()` creates clean, temporally-ordered survival data +- Add garbage to individual date variables using `add_garbage()` helper +- `create_date_var()` (called internally) applies garbage automatically +- Test temporal validation by checking for impossible dates (e.g., far-future death dates) +- This approach separates concerns: date-level garbage vs. survival data generation + +### Testing follow-up time calculations + +Temporal violations also produce invalid derived variables like impossibly long follow-up times: + +```{r} +#| label: test-followup-time +#| message: false +#| warning: false + +# Calculate follow-up time in days (entry to event) +survival_dates$followup_days <- as.numeric( + difftime( + survival_dates$death_date, + survival_dates$study_entry, + units = "days" + ) +) + +# Validate: follow-up should be within reasonable range (max 20 years = 7300 days) +max_reasonable_followup <- 7300 +invalid_followup <- survival_dates$followup_days > max_reasonable_followup +n_invalid_fu <- sum(invalid_followup, na.rm = TRUE) +``` + +```{r} +#| label: calculate-invalid-fu-percentage +#| echo: false + +invalid_fu_pct <- round(n_invalid_fu / nrow(survival_dates) * 100, 1) +``` + +Validation results for derived variables: + +- **Impossibly long follow-up time (> 20 years)**: `r n_invalid_fu` (`r invalid_fu_pct`%) + +The invalid follow-up times correspond to our temporal violations (future garbage dates), confirming validators can catch these derived quality issues. + +## Building a validation pipeline + +Now that we understand individual garbage patterns, let's build a complete validation pipeline that tests all quality checks systematically. We'll use MockData functions to generate a dataset with multiple garbage types: + +```{r} +#| label: build-validation-pipeline +#| message: false +#| warning: false + +# Generate complete dataset with multiple garbage types using create_mock_data() +full_data <- create_mock_data( + databaseStart = "minimal-example", + variables = system.file("extdata/minimal-example/variables.csv", package = "MockData"), + variable_details = system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + n = 5000, + seed = 500 +) + +# Run validation suite +# Check 1: Categorical codes (smoking) - exclude NA values +smoking_details <- variable_details[variable_details$variable == "smoking", ] +valid_smoking <- unique(smoking_details$recStart[!is.na(smoking_details$recStart)]) +smoking_invalid <- !full_data$smoking %in% valid_smoking & !is.na(full_data$smoking) + +# Check 2: Age range (valid: 18-100, excluding missing codes) +age_invalid <- (full_data$age < 18 | full_data$age > 100) & !full_data$age %in% c(997, 998, 999) + +# Check 3: Combined validation (any record with any issue) +any_issue <- smoking_invalid | age_invalid + +# Build results table +validation_results <- data.frame( + check = c("smoking: invalid codes", "age: out of range", "Any validation failure"), + n_fail = c(sum(smoking_invalid), sum(age_invalid, na.rm = TRUE), sum(any_issue, na.rm = TRUE)), + pct_fail = c( + round(sum(smoking_invalid) / nrow(full_data) * 100, 2), + round(sum(age_invalid, na.rm = TRUE) / nrow(full_data) * 100, 2), + round(sum(any_issue, na.rm = TRUE) / nrow(full_data) * 100, 2) + ) +) + +# Display results +validation_results +``` + +This validation suite detects intentional garbage patterns if they exist in the dataset, confirming each validator works correctly. + +## What you learned + +In this tutorial, you learned how to: + +- **Use the unified garbage approach** with `garbage_low_prop/range` and `garbage_high_prop/range` for all variable types +- **Generate categorical garbage** by treating valid codes as ordinal and specifying out-of-range values +- **Use the `add_garbage()` helper** to easily add garbage specifications to variables metadata +- **Create continuous garbage patterns** using these functions for precise control +- **Test date validation logic** by generating out-of-period dates using garbage parameters +- **Add temporal violations in survival data** by adding garbage to individual date variables (not via `create_wide_survival_data()` function parameter) +- **Build comprehensive validation pipelines** that test multiple quality checks systematically +- **Verify validator accuracy** by comparing detected rates to known garbage proportions + +The key principle: generate mock data with **known** quality issues, run your validators, and confirm they detect **exactly** what you expect. This approach gives you confidence that your validation pipeline will catch real data quality problems in production. + +## Next steps + +- **Practice with your project**: Generate garbage data matching your specific validation rules +- **Test edge cases**: Create scenarios that stress-test validator boundary conditions +- **Document expected rates**: Use garbage data to establish baseline error rate expectations +- **Automate validation testing**: Integrate garbage data generation into your CI/CD pipeline + +**Related vignettes**: + +- [Date variables tutorial](tutorial-dates.html): Learn advanced date generation techniques +- [Missing data tutorial](tutorial-missing-data.html): Learn about survey missing data codes +- [Getting started](getting-started.html): Review MockData fundamentals diff --git a/vignettes/tutorial-missing-data.qmd b/vignettes/tutorial-missing-data.qmd new file mode 100644 index 0000000..3c0ebe3 --- /dev/null +++ b/vignettes/tutorial-missing-data.qmd @@ -0,0 +1,362 @@ +--- +title: "Missing data in health surveys" +format: html +vignette: > + %\VignetteIndexEntry{Missing data in health surveys} + %\VignetteEngine{quarto::html} + %\VignetteEncoding{UTF-8} +--- + +```{r} +#| label: setup +#| include: false +# Load package - works in both local dev and pkgdown build +if (file.exists("../DESCRIPTION")) { + devtools::load_all("../", quiet = TRUE) +} else { + library(MockData) +} +``` + +::: {.vignette-about} +**About this vignette:** This tutorial teaches you how to generate realistic missing data in mock health survey datasets. You'll learn how to add missing data codes commonly used in Canadian health surveys (like the CCHS and CHMS), including valid skip, don't know, refusal, and not stated. All code examples run during vignette build to ensure accuracy. +::: + +## Understanding missing data in health surveys + +Health surveys use structured missing data codes to distinguish between different types of non-response. Unlike general R data where `NA` represents any missing value, survey data differentiates between several categories of missingness. This distinction is crucial for accurate statistical analysis. + +Consider a simple example: calculating smoking prevalence from survey data. If you treat all missing values the same way, you'll get biased estimates. Let's see why. + +```{r} +#| message: false +#| warning: false + +# Generate smoking data with two approaches +set.seed(123) + +# Wrong approach: treating all missing as NA +smoking_wrong <- data.frame( + smoker = sample(c("Yes", "No", NA), 1000, + replace = TRUE, + prob = c(0.20, 0.70, 0.10)) +) + +# Correct approach: using survey missing codes +smoking_correct <- data.frame( + smoker = sample(c("1", "2", "6", "7", "9"), 1000, + replace = TRUE, + prob = c(0.20, 0.70, 0.05, 0.03, 0.02)) +) +``` + +Now let's calculate prevalence both ways: + +```{r} +#| message: false +#| warning: false + +# Wrong calculation (naive approach) +wrong_prevalence <- mean(smoking_wrong$smoker == "Yes", na.rm = TRUE) + +# Correct calculation (excluding valid skip, including DK/RF/NS in denominator) +valid_responses <- smoking_correct$smoker %in% c("1", "2", "7", "9") +correct_prevalence <- sum(smoking_correct$smoker == "1") / sum(valid_responses) +``` + +```{r} +#| echo: false + +# Calculate for inline display +wrong_pct <- round(wrong_prevalence * 100, 1) +correct_pct <- round(correct_prevalence * 100, 1) +``` + +The naive approach gives us a prevalence of `r wrong_pct`%, while the correct approach gives `r correct_pct`%. This difference matters when making population-level estimates or comparing across surveys. + +### Why missing data codes matter + +In health surveys, not all missing values mean the same thing. Canadian health surveys like the Canadian Community Health Survey (CCHS) and Canadian Health Measures Survey (CHMS) use standardized systems of missing data codes: + +- **Valid skip (996)**: The question was not asked because skip logic determined it wasn't applicable +- **Don't know (997)**: The question was asked but the respondent didn't know the answer +- **Refusal (998)**: The question was asked but the respondent refused to answer +- **Not stated (999)**: The question was asked but no response was recorded + +Each type has different statistical implications. Valid skips should be excluded from your denominator (they weren't part of the eligible population for that question). But don't know, refusal, and not stated should be included in the denominator when calculating response rates, even though they're excluded from the numerator when calculating prevalence. + +Let's generate some realistic data to see this in action: + +```{r} +#| message: false +#| warning: false + +# Load metadata for examples +variable_details <- read.csv( + system.file("extdata/minimal-example/variable_details.csv", + package = "MockData"), + stringsAsFactors = FALSE +) + +variables <- read.csv( + system.file("extdata/minimal-example/variables.csv", + package = "MockData"), + stringsAsFactors = FALSE +) + +# Create smoking data using MockData +# smoking has categories: 1=Never, 2=Former, 3=Current, 7=Don't know +df_mock <- data.frame() +smoking_data <- create_cat_var( + var = "smoking", + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + df_mock = df_mock, + n = 1000, + seed = 456 +) + +# Show distribution +table(smoking_data$smoking) +``` + +### The three types of missing data codes + +Health surveys categorize missing data into three main types, each requiring different statistical treatment. + +**Valid skip (code 996)** + +A valid skip occurs when skip logic determines a question should not be asked. For example, if someone reports they've never smoked, they won't be asked "How many cigarettes per day do you smoke?" This isn't truly missing dataβ€”it's a logical consequence of their previous answer. + +Statistical treatment: Exclude from both the numerator and denominator. These respondents weren't eligible for the question. + +**Don't know / Refusal / Not stated (codes 997, 998, 999)** + +These codes represent questions that were asked but didn't receive valid responses: + +- **997 (Don't know)**: Respondent was uncertain about the answer +- **998 (Refusal)**: Respondent declined to answer +- **999 (Not stated)**: Question was asked but no response was recorded + +Statistical treatment: Include in the denominator when calculating response rates (they were eligible and asked), but exclude from the numerator when calculating prevalence (we don't know their true status). + +**Not applicable (code 996)** + +This is similar to valid skipβ€”the question doesn't apply to the respondent's situation. The statistical treatment is the same as valid skip. + +Let's demonstrate the difference with a worked example using smoking status: + +```{r} +#| message: false +#| warning: false + +# Calculate response rate (includes DK in denominator, excludes any skip codes) +asked <- smoking_data$smoking %in% c("1", "2", "3", "7") +valid_response <- smoking_data$smoking %in% c("1", "2", "3") +response_rate <- sum(valid_response) / sum(asked) + +# Calculate prevalence of current smoking (excludes DK from numerator, but includes in denominator) +current_smoker <- smoking_data$smoking == "3" +prevalence <- sum(current_smoker) / sum(asked) +``` + +```{r} +#| echo: false + +# Format for display +response_pct <- round(response_rate * 100, 1) +prevalence_pct <- round(prevalence * 100, 1) +n_asked <- sum(asked) +n_dk <- sum(smoking_data$smoking == "7") +``` + +In this dataset: + +- **Sample size**: `r nrow(smoking_data)` respondents +- **Asked**: `r n_asked` (all respondents for this variable) +- **Response rate**: `r response_pct`% (valid responses Γ· asked) +- **Current smoking prevalence**: `r prevalence_pct`% (current smokers Γ· asked) +- **Don't know responses**: `r n_dk` (`r round(n_dk/n_asked*100, 1)`% of those asked) + +Notice how "Don't know" (code 7) is included in the denominator when calculating response rate but excluded from the numerator when calculating current smoking prevalence. + +### Example with both skip and missing codes + +Let's look at the BMI variable, which demonstrates both valid skip (NA::a) and missing codes (NA::b): + +```{r} +#| message: false +#| warning: false + +# Look at BMI variable metadata +bmi_details <- variable_details[variable_details$variable == "BMI", ] +print(bmi_details[, c("variable", "recStart", "recEnd", "catLabel", "proportion")], row.names = FALSE) +``` + +This shows how missing codes appear in survey metadata. The `recStart` column contains the category codes, including continuous range ([15,50]), valid skip (996 for not applicable, mapped to NA::a), and missing data codes ([997,999] for don't know/refusal/not stated, mapped to NA::b). + +We can use this metadata to generate mock data with realistic proportions: + +```{r} +#| message: false +#| warning: false + +# Generate age data with missing codes +df_mock_age <- data.frame() +age_data <- create_con_var( + var = "age", + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + df_mock = df_mock_age, + n = 5000, + seed = 789 +) + +# Calculate response rate excluding missing codes +valid_ages <- !is.na(age_data$age) & age_data$age >= 18 & age_data$age <= 100 +missing_codes <- age_data$age %in% c(997, 998, 999) +asked_age <- valid_ages | missing_codes +response_rate_age <- sum(valid_ages) / sum(asked_age) + +# Summary statistics on valid ages only +mean_age <- mean(age_data$age[valid_ages], na.rm = TRUE) +``` + +```{r} +#| echo: false + +response_age_pct <- round(response_rate_age * 100, 1) +n_asked_age <- sum(asked_age) +n_dk_age <- sum(age_data$age == 997, na.rm = TRUE) +n_refusal_age <- sum(age_data$age == 998, na.rm = TRUE) +n_ns_age <- sum(age_data$age == 999, na.rm = TRUE) +mean_age_rounded <- round(mean_age, 1) +``` + +For this age variable: + +- **Sample size**: `r nrow(age_data)` respondents +- **Response rate**: `r response_age_pct`% (`r sum(valid_ages)` valid responses Γ· `r n_asked_age` asked) +- **Mean age** (valid responses only): `r mean_age_rounded` years +- **Don't know responses**: `r n_dk_age` (`r round(n_dk_age/n_asked_age*100, 1)`% of those asked) +- **Refusal**: `r n_refusal_age` (`r round(n_refusal_age/n_asked_age*100, 1)`% of those asked) +- **Not stated**: `r n_ns_age` (`r round(n_ns_age/n_asked_age*100, 1)`% of those asked) + +This demonstrates how health survey data includes measurable proportions of missing data codes, and why distinguishing between them matters for accurate statistical reporting. + +## The recEnd column: Enabling missing data classification + +To generate realistic missing data, MockData needs to distinguish between **valid response codes** (1, 2, 3) and **missing data codes** (6-9, 96-99). The `recEnd` column in variable_details.csv provides this classification. We follow the recodeflow approach that supports tagged NA using the `haven` and other packages. `recodeflow` can add tagged_NA when recoding and tranforming variables. `NA::a` is assigned 'not applicable' and `NA::b` is assing 'missing/refused/not stated'. + +### How recEnd works + +The `recEnd` column maps input codes to their classification: + +**Valid responses:** Map codes to themselves using numeric values + +```r +# variable_details.csv +uid,uid_detail,variable,recStart,recEnd,catLabel,proportion +v_002,d_002,smoking,1,1,Daily smoker,0.25 +v_002,d_003,smoking,2,2,Occasional,0.15 +v_002,d_004,smoking,3,3,Never,0.57 +``` + +**Missing codes:** Use NA::b for don't know, refusal, not stated + +```r +# variable_details.csv (continued) +v_002,d_005,smoking,7,NA::b,Don't know,0.03 +``` + +**Skip codes:** Use NA::a for valid skip/not applicable + +```r +v_002,d_006,smoking,6,NA::a,Valid skip,0.01 +``` + +### Why recEnd is required + +Without recEnd, MockData cannot tell the difference between: + +- Code 1 (valid: Daily smoker) +- Code 7 (missing: Don't know) + +Both are just numbers in `recStart`. The `recEnd` column provides explicit classification: + +- `recEnd = "1"` β†’ Valid response code +- `recEnd = "NA::b"` β†’ Missing data (DK/Refusal/NS) +- `recEnd = "NA::a"` β†’ Skip code (not applicable) + +### Conditional requirement + +The recEnd column is **conditionally required** when your variable_details.csv contains missing data codes (6-9, 96-99): + +**Validation error:** If you use codes like 7, 8, or 9 in `recStart` without a recEnd column, you'll get this error: + +``` +recEnd column required in variable_details when using missing data codes (6-9, 96-99). + Use 'NA::a' for skip codes (6, 96, 996), + Use 'NA::b' for missing codes (7-9, 97-99) representing DK/Refusal/NS, + and numeric codes (e.g., '1', '2', '3') for valid responses. +``` + +**When recEnd is optional:** For simple variables without missing codes, recEnd can be omitted: + +```r +# Simple categorical variable (no missing codes) - recEnd optional +uid,uid_detail,variable,recStart,catLabel,proportion +v_010,d_100,gender,1,Male,0.5 +v_010,d_101,gender,2,Female,0.5 +``` + +### Complete example with recEnd + +```{r} +#| message: false +#| warning: false + +# Create variable_details with recEnd column +smoking_details_recEnd <- data.frame( + uid = "cchsflow_v0002", + uid_detail = c("cchsflow_d00005", "cchsflow_d00006", "cchsflow_d00007", "cchsflow_d00008"), + variable = "smoking", + recStart = c("1", "2", "3", "7"), + recEnd = c("1", "2", "3", "NA::b"), # Explicit classification + catLabel = c("Never smoker", "Former smoker", "Current smoker", "Don't know"), + proportion = c(0.5, 0.3, 0.17, 0.03), + stringsAsFactors = FALSE +) + +# Show the configuration +print(smoking_details_recEnd, row.names = FALSE) +``` + +This configuration tells MockData: + +- Codes 1, 2, 3 are **valid responses** (recEnd maps to themselves) +- Code 7 is a **missing code** (recEnd = "NA::b") +- When generating data, 3% will be "Don't know" responses + +### NA:: conventions + +MockData uses recodeflow's NA:: convention for missing data classification: + +**NA::a (skip codes):** + +- Question not asked due to skip logic +- Example: "Have you smoked in the last 30 days?" is skipped for never smokers +- **Statistical treatment:** Exclude from denominator (not eligible) +- Common codes: 6, 96, 996 + +**NA::b (missing codes):** + +- Question asked but no valid response given +- Includes: Don't know (7, 97), Refusal (8, 98), Not stated (9, 99) +- **Statistical treatment:** Include in denominator for response rates +- Common codes: 7-9, 97-99 + +This convention enables automatic missing data handling throughout MockData's generation functions. + diff --git a/vignettes/tutorial-survival-data.qmd b/vignettes/tutorial-survival-data.qmd new file mode 100644 index 0000000..4911af0 --- /dev/null +++ b/vignettes/tutorial-survival-data.qmd @@ -0,0 +1,457 @@ +--- +title: "Generating survival data with competing risks" +format: html +vignette: > + %\VignetteIndexEntry{Generating survival data with competing risks} + %\VignetteEngine{quarto::html} + %\VignetteEncoding{UTF-8} +--- + +```{r} +#| label: setup +#| include: false +# Load package - works in both local dev and pkgdown build +if (file.exists("../DESCRIPTION")) { + devtools::load_all("../", quiet = TRUE) +} else { + library(MockData) +} +``` + +::: {.vignette-about} +**About this vignette:** This tutorial teaches survival data generation for cohort studies. You'll learn how to create time-to-event data with competing risks (death, disease incidence, loss-to-follow-up), apply temporal ordering constraints, and generate survival indicators for analysis. All code examples run during vignette build to ensure accuracy. +::: + +## Overview + +Survival analysis requires careful coordination of multiple date variables with strict temporal ordering: + +- **Cohort entry date** (baseline, index date) +- **Event dates** (disease incidence, outcomes of interest) +- **Competing risks** (death prevents observation of primary event) +- **Censoring events** (loss to follow-up, administrative censoring) + +MockData's `create_wide_survival_data()` generates these dates with proper temporal constraints and realistic distributions. + +::: {.callout-important} +## About this tutorial: Clean survival data with correct temporal ordering + +This tutorial teaches how to create **meaningful, analysis-ready survival data** with correct temporal ordering. All dates follow proper survival analysis constraints (entry ≀ event, death as competing risk, etc.). + +**For data quality testing:** If you need to generate **raw data with temporal violations** (e.g., death before entry, impossible dates) for testing data cleaning pipelines, see the [Garbage data tutorial](tutorial-garbage-data.html#survival-data-garbage) which covers survival-specific garbage patterns. +::: + +## Basic survival data generation + +### Minimal example: entry + event + +The simplest survival data has two dates: cohort entry and a single event. + +```{r} +#| label: survival-basic +#| warning: false +#| message: false + +# Load minimal-example metadata +variables <- read.csv( + system.file("extdata/minimal-example/variables.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE +) + +variable_details <- read.csv( + system.file("extdata/minimal-example/variable_details.csv", package = "MockData"), + stringsAsFactors = FALSE, + check.names = FALSE +) + +# Generate entry + event dates +surv_basic <- create_wide_survival_data( + var_entry_date = "interview_date", + var_event_date = "primary_event_date", # disease incidence or similar + var_death_date = NULL, + var_ltfu = NULL, # Loss to follow-up + var_admin_censor = NULL, # i.e. End of study follow-up + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 1000, + seed = 123 +) + +# View first few rows +head(surv_basic) +``` + +**Result:** Each row has an interview date (cohort entry) and primary event date. Some event dates are `NA` (censored - event did not occur during follow-up). + +### Event proportions + +Not all individuals experience the primary event. The `event_prop` parameter in variables.csv controls event occurrence rate: + +```{r} +#| label: check-event-prop +#| echo: false + +# Check event proportion from metadata +primary_event_row <- variables[variables$variable == "primary_event_date", ] +event_prop <- primary_event_row$event_prop + +# Calculate actual event rate +n_events <- sum(!is.na(surv_basic$primary_event_date)) +observed_prop <- n_events / nrow(surv_basic) +``` + +**Configuration:** The primary_event_date variable has `event_prop = `r event_prop`` in variables.csv, meaning `r event_prop * 100`% of individuals experience the event. + +**Observed:** `r n_events` out of `r nrow(surv_basic)` individuals (`r round(observed_prop * 100, 1)`%) experienced the primary event. + +## Competing risks: adding death + +Death is a competing risk - individuals who die cannot experience the primary event. MockData handles this temporal logic automatically. + +```{r} +#| label: competing-risks +#| warning: false +#| message: false + +# Generate entry + event + death +surv_compete <- create_wide_survival_data( + var_entry_date = "interview_date", + var_event_date = "primary_event_date", + var_death_date = "death_date", + var_ltfu = NULL, + var_admin_censor = NULL, + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 1000, + seed = 456 +) + +# Check temporal ordering +head(surv_compete[, c("interview_date", "primary_event_date", "death_date")]) +``` + +### Competing risk logic + +MockData applies these rules: + +1. **Entry date is baseline**: All other dates occur after entry +2. **Death prevents events**: If death < event, set event to NA (cannot observe event after death) +3. **Temporal ordering**: interview_date ≀ event_date, interview_date ≀ death_date + +```{r} +#| label: verify-temporal-ordering +# Verify temporal ordering +# Note: Dates are already R Date objects (sourceFormat = "analysis" in variables.csv) +interview_dates <- surv_compete$interview_date +event_dates <- surv_compete$primary_event_date +death_dates <- surv_compete$death_date + +# Check: All events occur after entry +all_events_after_entry <- all( + event_dates[!is.na(event_dates)] >= interview_dates[!is.na(event_dates)], + na.rm = TRUE +) + +# Check: All deaths occur after entry +all_deaths_after_entry <- all( + death_dates[!is.na(death_dates)] >= interview_dates[!is.na(death_dates)], + na.rm = TRUE +) +``` + +**Temporal ordering validation:** + +- All events occur after entry: `r all_events_after_entry` +- All deaths occur after entry: `r all_deaths_after_entry` + +This confirms MockData correctly enforces temporal constraints. + +## Complete survival data: entry + event + death + censoring + +Real cohort studies have multiple censoring mechanisms: + +- **Loss to follow-up**: Participants drop out +- **Administrative censoring**: Study ends on specific date + +```{r} +#| label: survival-complete +#| warning: false +#| message: false + +# Generate complete survival data (all 5 date variables) +surv_complete <- create_wide_survival_data( + var_entry_date = "interview_date", + var_event_date = "primary_event_date", + var_death_date = "death_date", + var_ltfu = "ltfu_date", + var_admin_censor = "admin_censor_date", + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 2000, + seed = 789 +) + +# View structure +head(surv_complete) +``` + +## Creating survival indicators + +Survival analysis requires deriving time-to-event and event indicators from the date variables. + +### Calculate observation end date + +Observation ends at the earliest of: primary event, death, loss to follow-up, or administrative censoring. + +```{r} +#| label: calculate-end-date +# Dates are already R Date objects (sourceFormat = "analysis") +# Calculate end date (earliest of all outcomes) +# Build list of existing date columns +date_cols <- c("primary_event_date", "death_date", "ltfu_date", "admin_censor_date") +existing_cols <- date_cols[date_cols %in% names(surv_complete)] + +# Calculate minimum date across existing columns +if (length(existing_cols) > 0) { + # Use row-wise minimum to avoid pmin Inf issues with all-NA rows + surv_complete$t_end <- as.Date( + apply(surv_complete[, existing_cols, drop = FALSE], 1, function(row_dates) { + valid_dates <- row_dates[!is.na(row_dates)] + if (length(valid_dates) == 0) return(NA_real_) + min(valid_dates) + }), + origin = "1970-01-01" + ) +} else { + surv_complete$t_end <- as.Date(NA) +} + +# Calculate follow-up time in days +# Date subtraction returns difftime object; convert to numeric days +surv_complete$followup_days <- as.numeric(difftime(surv_complete$t_end, surv_complete$interview_date, units = "days")) + +head(surv_complete[, c("interview_date", "t_end", "followup_days")]) +``` + +### Create event indicator + +Event indicator identifies why observation ended: + +- **0**: Censored (loss to follow-up or administrative censoring) +- **1**: Primary event occurred +- **2**: Death occurred (competing risk) + +```{r} +#| label: create-event-indicator +# Create event indicator +surv_complete$event_indicator <- ifelse( + !is.na(surv_complete$primary_event_date) & surv_complete$primary_event_date == surv_complete$t_end, 1, # Event + ifelse(!is.na(surv_complete$death_date) & surv_complete$death_date == surv_complete$t_end, 2, # Death + 0) # Censored +) + +# Tabulate outcomes +table(surv_complete$event_indicator) +``` + +```{r} +#| label: calculate-percentages +#| echo: false + +# Calculate percentages for display +event_counts <- table(surv_complete$event_indicator) +pct_censored <- round(100 * event_counts["0"] / nrow(surv_complete), 1) +pct_event <- round(100 * event_counts["1"] / nrow(surv_complete), 1) +pct_death <- round(100 * event_counts["2"] / nrow(surv_complete), 1) +``` + +**Result:** + +- **Censored (0)**: `r event_counts["0"]` (`r pct_censored`%) - lost to follow-up or administratively censored +- **Primary event (1)**: `r event_counts["1"]` (`r pct_event`%) - experienced primary event +- **Death (2)**: `r event_counts["2"]` (`r pct_death`%) - died before primary event + +## Distributions for survival data + +Survival dates use realistic distributions to match real-world patterns: + +**Uniform**: Constant hazard (administrative censoring, loss to follow-up) + +```r +distribution = "uniform" +``` + +**Gompertz**: Age-dependent hazard (death, chronic disease) + +```r +distribution = "gompertz" +rate = 0.0001 +shape = 0.1 +``` + +**Exponential**: Constant hazard with early concentration + +```r +distribution = "exponential" +rate = 0.001 +``` + +Distribution parameters are specified in variables.csv and used automatically by `create_wide_survival_data()`. + +## Date output formats: sourceFormat column + +By default, survival dates are generated as R Date objects (`sourceFormat = "analysis"`). However, you can simulate different raw data formats using the `sourceFormat` column in variables.csv: + +**Available sourceFormat values:** + +- **analysis** (default): R Date objects ready for analysis +- **csv**: Character strings in ISO format (YYYY-MM-DD), simulating CSV file imports +- **sas**: Numeric values (days since 1960-01-01), simulating SAS date format + +**Why this matters:** + +Real cohort data doesn't arrive as clean R Date objects: + +- CSV files from survey instruments contain character dates requiring parsing +- SAS files may have numeric dates that need conversion +- Different data sources require different harmonization approaches + +**Example: Testing different source formats** + +The `sourceFormat` value in variables.csv controls the output format. Let's generate interview_date in SAS numeric format while keeping other dates in analysis format: + +```{r} +#| label: sourceformat-sas-example +#| warning: false +#| message: false + +# Modify only interview_date to use SAS format +vars_sas <- variables +vars_sas$sourceFormat[vars_sas$variable == "interview_date"] <- "sas" + +surv_sas <- create_wide_survival_data( + var_entry_date = "interview_date", + var_event_date = "primary_event_date", + var_death_date = NULL, + var_ltfu = NULL, + var_admin_censor = NULL, + databaseStart = "minimal-example", + variables = vars_sas, # Modified to use SAS format for interview_date + variable_details = variable_details, + n = 100, + seed = 123 +) + +# Check the format: interview_date is numeric (SAS), others are Date +head(surv_sas) +``` + +**Result:** The `interview_date` column is numeric (days since 1960-01-01), while `primary_event_date` remains a Date object. This simulates mixed-format raw data that requires harmonization. + +To convert SAS dates to R Date format: + +```{r} +#| label: convert-sas-dates +#| warning: false +#| message: false + +# Convert SAS numeric dates to R Date +interview_converted <- as.Date(surv_sas$interview_date, origin = "1960-01-01") +head(interview_converted) +``` + +## Temporal violations for QA testing + +The minimal-example metadata includes temporal violations through the `garbage_high_prop` and `garbage_high_range` parameters. These generate future dates that violate temporal constraints for testing validation pipelines: + +```{r} +#| label: temporal-violations-qa +#| warning: false +#| message: false + +# Generate survival data with configured garbage dates +surv_qa <- create_wide_survival_data( + var_entry_date = "interview_date", + var_event_date = "primary_event_date", + var_death_date = "death_date", + var_ltfu = NULL, + var_admin_censor = NULL, + databaseStart = "minimal-example", + variables = variables, + variable_details = variable_details, + n = 1000, + seed = 999 +) + +# Check for temporal violations +# Look for events that occur after impossibly far in the future (2025+) +future_threshold <- as.Date("2025-01-01") + +# Count future dates in primary_event_date +n_future_events <- sum(surv_qa$primary_event_date > future_threshold, na.rm = TRUE) + +# Count future dates in death_date +n_future_deaths <- sum(surv_qa$death_date > future_threshold, na.rm = TRUE) + +# Total violations +n_violations <- n_future_events + n_future_deaths +prop_violations <- round(100 * n_violations / nrow(surv_qa), 1) +``` + +```{r} +#| label: store-qa-variables +#| echo: false + +# Store variables for inline display +n_total_qa <- nrow(surv_qa) +``` + +**Validation detects:** `r n_violations` temporal violations out of `r n_total_qa` observations (`r prop_violations`%). These future dates (> 2025-01-01) represent data quality issues that your validation pipeline should flag. + +**Breakdown:** + +- Future primary events: `r n_future_events` +- Future deaths: `r n_future_deaths` + +This demonstrates how MockData's garbage parameters help test validation logic by generating realistic data quality issues. + +## Key concepts summary + +| Concept | Implementation | Details | +|---------|----------------|---------| +| **Competing risks** | Death prevents primary event | If death < event, set event to NA | +| **Event proportions** | `event_prop` in variables.csv | Controls % experiencing each outcome | +| **Temporal ordering** | Automatic constraint enforcement | All dates β‰₯ entry date | +| **Distributions** | Gompertz, uniform, exponential | Specified in variables.csv | +| **End date** | `pmin(event, death, ltfu, admin)` | Earliest outcome defines observation end | +| **Event indicator** | Derived from date comparison | 0=censored, 1=event, 2=death | +| **QA testing** | `prop_garbage` parameter | Generates temporal violations for validation testing | + +## What you learned + +In this tutorial, you learned: + +- **Basic survival generation**: Entry date + event date with event proportions +- **Competing risks**: Death as a competing event that prevents primary event observation +- **Temporal constraints**: How MockData enforces proper date ordering +- **Complete cohort data**: Entry + event + death + loss-to-follow-up + administrative censoring +- **Derived variables**: Creating follow-up time and event indicators from raw dates +- **Distributions**: Using Gompertz, uniform, and exponential for realistic temporal patterns +- **QA testing**: Generating temporal violations to validate data quality pipelines + +## Next steps + +**Tutorials:** + +- [Date variables](tutorial-dates.html) - Learn interval notation and date distributions +- [Garbage data](tutorial-garbage-data.html) - Testing validation pipelines +- [Getting started](getting-started.html) - Review MockData fundamentals + +**Reference:** + +- [Configuration reference](reference-config.html) - Complete metadata schema +- [Advanced topics](advanced-topics.html) - Technical implementation details