diff --git a/R/default_forest_panels.R b/R/default_forest_panels.R
index b738066..b1c814c 100644
--- a/R/default_forest_panels.R
+++ b/R/default_forest_panels.R
@@ -9,7 +9,16 @@
 #' @return `list` ready to be passed to `forest_model`
 #' @export
 #'
-default_forest_panels <- function(model = NULL, factor_separate_line = FALSE, measure = NULL, trans_char = "I") {
+default_forest_panels <- function(model = NULL, factor_separate_line = FALSE, measure = NULL, trans_char = "I", which_global_p = "logtest") {
+    if (which_global_p != "logtest") {
+        if (which_global_p == "waldtest") {
+            global_p_text <- "(Wald test)"
+        } else if (which_global_p == "sctest") {
+            global_p_text <- "(Score (logrank))"
+        }
+    } else {
+        global_p_text <- "(Likelihood ratio test)"
+    }
   if (is.list(model) && inherits(model[[1]], "rma")) {
     model <- model[[1]]
   }
@@ -70,7 +79,7 @@ default_forest_panels <- function(model = NULL, factor_separate_line = FALSE, me
       forest_panel(width = 0.03, item = "vline", hjust = 0.5),
       forest_panel(
         width = 0.12,
-        display = if_else(reference, if_else(is_na(p.value), "Reference", "Reference;  Variable logrank:"),
+        display = if_else(reference, if_else(is_na(p.value), "Reference", paste0("Reference | Global p ", global_p_text, ":")),
           sprintf("%0.2f (%0.2f, %0.2f)", trans(estimate), trans(conf.low), trans(conf.high))
         ),
         display_na = NA
diff --git a/R/forest_model.R b/R/forest_model.R
index a1be244..5c44d93 100644
--- a/R/forest_model.R
+++ b/R/forest_model.R
@@ -28,6 +28,10 @@
 #' - 'none', don't show.
 #' - 'bottom', show global p value in the bottom.
 #' - 'aside', show global p value along with 'Reference', this is useful when you plot a list of models.
+#' @param which_global_p Select which global p value to show, only works for Cox model.
+#' - 'logtest', Likelihood ratio test.
+#' - 'waldtest', Wald test.
+#' - 'sctest', Score (logrank).
 #' @param n_logical_true_only whether to only count TRUE values in n for logical
 #'   covariates
 #'
@@ -127,7 +131,7 @@
 #'
 #' print(forest_model(glm(outcome ~ ., binomial(), data_for_logistic)))
 forest_model <- function(model,
-                         panels = default_forest_panels(model, factor_separate_line = factor_separate_line),
+                         panels = default_forest_panels(model, factor_separate_line = factor_separate_line, which_global_p = which_global_p),
                          covariates = NULL, exponentiate = NULL, funcs = NULL,
                          factor_separate_line = FALSE,
                          format_options = forest_model_format_options(),
@@ -136,8 +140,10 @@ forest_model <- function(model,
                          recalculate_width = TRUE, recalculate_height = TRUE,
                          model_list = NULL, merge_models = FALSE, exclude_infinite_cis = TRUE,
                          show_global_p = c("none", "bottom", "aside"),
+                         which_global_p = c("logtest", "waldtest", "sctest"),
                          n_logical_true_only = FALSE) {
   show_global_p <- match.arg(show_global_p)
+  which_global_p <- match.arg(which_global_p)
   mapping <- aes(estimate, xmin = conf.low, xmax = conf.high)
   if (!is.null(model_list)) {
     if (!is.list(model_list)) {
@@ -161,7 +167,7 @@ forest_model <- function(model,
         (inherits(model_list[[1]], "glm") && model_list[[1]]$family$link == "logit")
     }
     if (missing(panels)) {
-      panels <- default_forest_panels(model_list[[1]], factor_separate_line = factor_separate_line)
+      panels <- default_forest_panels(model_list[[1]], factor_separate_line = factor_separate_line, which_global_p = which_global_p)
     }
   } else {
     if (is.null(exponentiate)) {
@@ -286,9 +292,23 @@ forest_model <- function(model,
 
     if (show_global_p != "none") {
       if (inherits(model, "coxph")) {
-        p_val <- as.numeric(summary(model)$sctest[3])
+        p_val_logtest <- as.numeric(summary(model)$logtest[3])
+        p_val_waldtest <- as.numeric(summary(model)$waldtest[3])
+        p_val_sctest <- as.numeric(summary(model)$sctest[3])
+        if (which_global_p != "logtest") {
+            if (which_global_p == "waldtest") {
+                p_val <- p_val_waldtest
+                global_p_text <- "(Wald test)"
+            } else if (which_global_p == "sctest") {
+                p_val <- p_val_sctest
+                global_p_text <- "(Score (logrank))"
+            }
+        } else {
+            p_val <- p_val_logtest
+            global_p_text <- "(Likelihood ratio test)"
+        }
         if (show_global_p == "bottom") {
-          label <- paste("Global p", format.pval(p_val, digits = 1, eps = 1e-3))
+          label <- paste("    Global p ", global_p_text, ":", format.pval(p_val, digits = 1, eps = 1e-3))
           forest_terms <- forest_terms %>%
             dplyr::add_row(term_label = "Global p", variable = label)
         } else if (show_global_p == "aside") {
diff --git a/man/forest_model.Rd b/man/forest_model.Rd
index c828f3d..d61e067 100644
--- a/man/forest_model.Rd
+++ b/man/forest_model.Rd
@@ -22,6 +22,7 @@ forest_model(
   merge_models = FALSE,
   exclude_infinite_cis = TRUE,
   show_global_p = c("none", "bottom", "aside"),
+  which_global_p = c("logtest", "waldtest", "sctest"),
   n_logical_true_only = FALSE
 )
 }
@@ -71,6 +72,11 @@ displayed as text. Defaults to \code{TRUE}, since otherwise plot is malformed}
 - 'bottom', show global p value in the bottom.
 - 'aside', show global p value along with 'Reference', this is useful when you plot a list of models.}
 
+\item{which_global_p}{Select which global p value to show, only works for Cox model.
+- 'logtest', Likelihood ratio test.
+- 'waldtest', Wald test.
+- 'sctest', Score (logrank).}
+
 \item{n_logical_true_only}{whether to only count TRUE values in n for logical
 covariates}
 }