diff --git a/R/assertions.R b/R/assertions.R
index e7ecb15acf..996db62016 100644
--- a/R/assertions.R
+++ b/R/assertions.R
@@ -225,8 +225,7 @@ assert_valid_var.factor <- function(
   checkmate::assert_character(
     levels(x),
     min.chars = min_chars,
-    .var.name = paste("level of", label),
-    ...
+    .var.name = paste("level of", label)
   )
   checkmate::assert_factor(
     x,
diff --git a/R/fstg01.R b/R/fstg01.R
index 16878f95d9..8ae6b5033d 100644
--- a/R/fstg01.R
+++ b/R/fstg01.R
@@ -19,8 +19,9 @@
 #'
 #' @note
 #'  * `adam_db` object must contain the table specified by `dataset` with `"PARAMCD"`, `"ARM"`,
-#'  `"AVALC"`, and the columns specified by `"subgroups"` which is denoted as
-#'  `c("SEX", "AGEGR1", "RACE")` by default.
+#'  `"AVALC"`, and the columns specified by `subgroups` which is denoted as
+#'  `c("SEX", "AGEGR1", "RACE")` by default. The column specified by `response` has the default value
+#'  `c("CR", "PR")`.
 #'
 #' @return a list of `ggplot` objects.
 #' @export
@@ -32,16 +33,22 @@ fstg01_main <- function(adam_db,
                         strata_var = NULL,
                         ...) {
   assert_all_tablenames(adam_db, c("adsl", dataset))
+  df_lbl <- paste0("adam_db$", dataset)
   checkmate::assert_string(arm_var)
   checkmate::assert_string(rsp_var)
   checkmate::assert_character(subgroups, null.ok = TRUE)
   checkmate::assert_character(strata_var, null.ok = TRUE)
-  assert_valid_variable(adam_db$adrs, arm_var, types = list("factor"))
-  assert_valid_variable(adam_db$adrs, c("USUBJID", "PARAMCD"), types = list(c("character", "factor")))
-  assert_valid_variable(adam_db$adrs, rsp_var, types = list("logical"))
-  assert_valid_variable(adam_db$adrs, c(subgroups, strata_var), types = list(c("factor", "numeric")))
-  assert_single_value(adam_db$adrs$PARAMCD)
-  checkmate::assert_factor(adam_db$adrs[[arm_var]], n.levels = 2)
+  assert_valid_variable(adam_db[[dataset]], arm_var, types = list("factor"), n.levels = 2, label = df_lbl)
+  assert_valid_variable(adam_db[[dataset]], c("USUBJID", "PARAMCD"),
+    types = list(c("character", "factor")),
+    label = df_lbl
+  )
+  assert_valid_variable(adam_db[[dataset]], rsp_var, types = list("logical"), label = df_lbl)
+  assert_valid_variable(adam_db[[dataset]], c(subgroups, strata_var),
+    types = list(c("factor")), na_ok = TRUE,
+    label = df_lbl
+  )
+  assert_single_value(adam_db[[dataset]]$PARAMCD, label = df_lbl)
 
   variables <- list(
     arm = arm_var,
@@ -69,11 +76,15 @@ fstg01_main <- function(adam_db,
 #' @describeIn fstg01 Preprocessing
 #'
 #' @inheritParams fstg01_main
+#' @param response (`character`) the response variable name(s).
 #'
 #' @export
 fstg01_pre <- function(adam_db, dataset = "adrs", response = c("CR", "PR"), ...) {
   adam_db[[dataset]] <- adam_db[[dataset]] %>%
-    mutate(is_rsp = .data$AVALC %in% response)
+    mutate(
+      ARM = droplevels(.data$ARM),
+      is_rsp = .data$AVALC %in% response
+    )
 
   adam_db
 }
@@ -95,15 +106,19 @@ fstg01_post <- function(tlg, ...) {
 #' @export
 #'
 #' @examples
-#' library(dunlin)
 #' library(dplyr)
+#' library(dunlin)
 #'
-#' proc_data <- log_filter(syn_data, PARAMCD == "OVRINV" & ARM %in% c("A: Drug X", "B: Placebo"), "adrs")
-#' proc_data$adrs$ARM <- droplevels(proc_data$adrs$ARM)
+#' proc_data <- log_filter(
+#'   syn_data,
+#'   PARAMCD == "OVRINV" & ARM %in% c("A: Drug X", "B: Placebo"), "adrs"
+#' )
 #' run(fstg01, proc_data, response = c("CR", "PR"), dataset = "adrs")
 #'
-#' proc_data <- log_filter(syn_data, PARAMCD == "BESRSPI" & ARM %in% c("A: Drug X", "B: Placebo"), "adrs")
-#' proc_data$adrs$ARM <- droplevels(proc_data$adrs$ARM)
+#' proc_data <- log_filter(
+#'   syn_data,
+#'   PARAMCD == "BESRSPI" & ARM %in% c("A: Drug X", "B: Placebo"), "adrs"
+#' )
 #' run(fstg01, proc_data,
 #'   response = c("CR"), subgroups = c("SEX", "AGEGR1", "RACE"),
 #'   conf_level = 0.90, dataset = "adrs"
diff --git a/R/kmg01.R b/R/kmg01.R
index 57c89a91c9..16df2d6951 100644
--- a/R/kmg01.R
+++ b/R/kmg01.R
@@ -32,7 +32,7 @@ kmg01_main <- function(adam_db,
     na_ok = FALSE,
     label = df_lbl
   )
-  assert_single_value(adam_db[[dataset]]$PARAMCD, label = past0(df_lbl, "$PARAMCD"))
+  assert_single_value(adam_db[[dataset]]$PARAMCD, label = paste0(df_lbl, "$PARAMCD"))
   assert_valid_variable(adam_db[[dataset]], "USUBJID", empty_ok = TRUE, types = list(c("character", "factor")))
   variables <- list(tte = "AVAL", is_event = "is_event", arm = arm_var)
 
diff --git a/man/fstg01.Rd b/man/fstg01.Rd
index 4451e946f3..061aac7827 100644
--- a/man/fstg01.Rd
+++ b/man/fstg01.Rd
@@ -45,6 +45,8 @@ fstg01
 Commonly used arguments include \code{col_symbol_size}, \code{col}, \code{vline}, \code{groups_lists}, \code{conf_level},
 \code{method}, \code{label_all}, etc.}
 
+\item{response}{(\code{character}) the response variable name(s).}
+
 \item{tlg}{(\code{TableTree}, \code{Listing} or \code{ggplot}) object typically produced by a \code{main} function.}
 }
 \value{
@@ -71,20 +73,25 @@ a list of \code{ggplot} objects.
 \note{
 \itemize{
 \item \code{adam_db} object must contain the table specified by \code{dataset} with \code{"PARAMCD"}, \code{"ARM"},
-\code{"AVALC"}, and the columns specified by \code{"subgroups"} which is denoted as
-\code{c("SEX", "AGEGR1", "RACE")} by default.
+\code{"AVALC"}, and the columns specified by \code{subgroups} which is denoted as
+\code{c("SEX", "AGEGR1", "RACE")} by default. The column specified by \code{response} has the default value
+\code{c("CR", "PR")}.
 }
 }
 \examples{
-library(dunlin)
 library(dplyr)
+library(dunlin)
 
-proc_data <- log_filter(syn_data, PARAMCD == "OVRINV" & ARM \%in\% c("A: Drug X", "B: Placebo"), "adrs")
-proc_data$adrs$ARM <- droplevels(proc_data$adrs$ARM)
+proc_data <- log_filter(
+  syn_data,
+  PARAMCD == "OVRINV" & ARM \%in\% c("A: Drug X", "B: Placebo"), "adrs"
+)
 run(fstg01, proc_data, response = c("CR", "PR"), dataset = "adrs")
 
-proc_data <- log_filter(syn_data, PARAMCD == "BESRSPI" & ARM \%in\% c("A: Drug X", "B: Placebo"), "adrs")
-proc_data$adrs$ARM <- droplevels(proc_data$adrs$ARM)
+proc_data <- log_filter(
+  syn_data,
+  PARAMCD == "BESRSPI" & ARM \%in\% c("A: Drug X", "B: Placebo"), "adrs"
+)
 run(fstg01, proc_data,
   response = c("CR"), subgroups = c("SEX", "AGEGR1", "RACE"),
   conf_level = 0.90, dataset = "adrs"
diff --git a/tests/testthat/test-fstg01.R b/tests/testthat/test-fstg01.R
index 02699ac1e9..ba7ff9d7c9 100644
--- a/tests/testthat/test-fstg01.R
+++ b/tests/testthat/test-fstg01.R
@@ -2,8 +2,6 @@
 
 test_that("fstg01 works as expected", {
   proc_data <- dunlin::log_filter(syn_data, PARAMCD == "OVRINV" & ARM %in% c("A: Drug X", "B: Placebo"), "adrs")
-  proc_data$adrs$ARM <- droplevels(proc_data$adrs$ARM)
-
   pre_data <- expect_silent(fstg01_pre(proc_data, dataset = "adrs", response = c("CR", "PR")))
   raw_res <- expect_silent(fstg01_main(pre_data, dataset = "adrs"))
   checkmate::assert_true(grid::is.grob(raw_res))
@@ -13,7 +11,6 @@ test_that("fstg01 works as expected", {
 
 test_that("fstg01 works as expected with custom color set", {
   proc_data <- dunlin::log_filter(syn_data, PARAMCD == "BESRSPI" & ARM %in% c("A: Drug X", "B: Placebo"), "adrs")
-  proc_data$adrs$ARM <- droplevels(proc_data$adrs$ARM)
 
   res1 <- expect_silent(run(fstg01, proc_data, response = c("CR", "PR"), dataset = "adrs", col = "gray"))
   checkmate::assert_true(grid::is.grob(res1))
@@ -24,7 +21,6 @@ test_that("fstg01 works as expected with custom color set", {
 
 test_that("fstg01 works if changes are in subgroups, strata_var, conf_level, and label_all", {
   proc_data <- dunlin::log_filter(syn_data, PARAMCD == "BESRSPI" & ARM %in% c("A: Drug X", "B: Placebo"), "adrs")
-  proc_data$adrs$ARM <- droplevels(proc_data$adrs$ARM)
 
   res1 <- expect_silent(run(fstg01, proc_data, response = c("CR", "PR"), subgroups = NULL, dataset = "adrs"))
   checkmate::assert_true(grid::is.grob(res1))
@@ -35,3 +31,13 @@ test_that("fstg01 works if changes are in subgroups, strata_var, conf_level, and
   ))
   checkmate::assert_true(grid::is.grob(res2))
 })
+
+test_that("fstg01 can handle some NA values in subgroups", {
+  proc_data <- dunlin::log_filter(syn_data, PARAMCD == "BESRSPI" & ARM %in% c("A: Drug X", "B: Placebo"), "adrs")
+  proc_data$adrs[1:2, "SEX"] <- NA
+  proc_data$adrs[3:4, "AGEGR1"] <- NA
+  proc_data$adrs[5:6, "RACE"] <- NA
+
+  res <- expect_silent(run(fstg01, proc_data, response = c("CR", "PR"), dataset = "adrs"))
+  checkmate::assert_true(grid::is.grob(res))
+})