diff --git a/R/modify_columns.R b/R/modify_columns.R
index 21fe317ae..595b5d603 100644
--- a/R/modify_columns.R
+++ b/R/modify_columns.R
@@ -2234,13 +2234,15 @@ cols_add <- function(
 #'
 #' @param missing_vals *Treatment of missing values*
 #'
-#'   `singl-kw:[gap|zero|remove]` // *default:* `"gap"`
+#'   `singl-kw:[gap|marker|zero|remove]` // *default:* `"gap"`
 #'
 #'   If missing values are encountered within the input data, there are three
-#'   strategies available for their handling: (1) `"gap"` will display data gaps
-#'   at the sites of missing data, where data lines will have discontinuities;
-#'   (2) `"zero"` will replace `NA` values with zero values; and (3) `"remove"`
-#'   will remove any incoming `NA` values.
+#'   strategies available for their handling: (1) `"gap"` will show data gaps
+#'   at the sites of missing data, where data lines will have discontinuities
+#'   and bar plots will have missing bars; (2) `"marker"` will behave like
+#'   `"gap"` but show prominent visual marks at the missing data locations; (3)
+#'   `"zero"` will replace `NA` values with zero values; and (4) `"remove"` will
+#'   remove any incoming `NA` values.
 #'
 #' @param autoscale *Automatically set x- and y-axis scale limits based on data*
 #'
@@ -2742,7 +2744,7 @@ cols_nanoplot <- function(
     rows = everything(),
     plot_type = c("line", "bar", "boxplot"),
     plot_height = "2em",
-    missing_vals = c("gap", "zero", "remove"),
+    missing_vals = c("gap", "marker", "zero", "remove"),
     autoscale = FALSE,
     autohide = TRUE,
     columns_x_vals = NULL,
diff --git a/R/utils_plots.R b/R/utils_plots.R
index 076afd6fc..9660d92af 100644
--- a/R/utils_plots.R
+++ b/R/utils_plots.R
@@ -29,7 +29,7 @@ generate_nanoplot <- function(
     x_vals = NULL,
     expand_x = NULL,
     expand_y = NULL,
-    missing_vals = c("gap", "zero", "remove"),
+    missing_vals = c("gap", "marker", "zero", "remove"),
     all_y_vals = NULL,
     all_single_y_vals = NULL,
     plot_type = c("line", "bar"),
@@ -895,7 +895,7 @@ generate_nanoplot <- function(
 
       if (is.na(data_y_points[i])) {
 
-        if (missing_vals == "gap") {
+        if (missing_vals == "marker") {
 
           # Create a symbol that should denote that a
           # missing value is present
@@ -905,7 +905,7 @@ generate_nanoplot <- function(
               "cx=\"", data_x_points[i], "\" ",
               "cy=\"", safe_y_d + (data_y_height / 2), "\" ",
               "r=\"", data_point_radius_i + (data_point_radius_i / 2), "\" ",
-              "stroke=\"red\" ",
+              "stroke=\"", "red", "\" ",
               "stroke-width=\"", data_point_stroke_width_i, "\" ",
               "fill=\"white\" ",
               ">",
@@ -956,7 +956,7 @@ generate_nanoplot <- function(
 
       if (is.na(data_y_points[i])) {
 
-        if (missing_vals == "gap") {
+        if (missing_vals == "marker") {
 
           # Create a symbol that should denote that a
           # missing value is present
diff --git a/man/cols_nanoplot.Rd b/man/cols_nanoplot.Rd
index 38ad7d338..c1a327227 100644
--- a/man/cols_nanoplot.Rd
+++ b/man/cols_nanoplot.Rd
@@ -10,7 +10,7 @@ cols_nanoplot(
   rows = everything(),
   plot_type = c("line", "bar", "boxplot"),
   plot_height = "2em",
-  missing_vals = c("gap", "zero", "remove"),
+  missing_vals = c("gap", "marker", "zero", "remove"),
   autoscale = FALSE,
   autohide = TRUE,
   columns_x_vals = NULL,
@@ -81,13 +81,15 @@ images inserted via \code{\link[=fmt_image]{fmt_image()}} (also having a \code{"
 
 \item{missing_vals}{\emph{Treatment of missing values}
 
-\verb{singl-kw:[gap|zero|remove]} // \emph{default:} \code{"gap"}
+\verb{singl-kw:[gap|marker|zero|remove]} // \emph{default:} \code{"gap"}
 
 If missing values are encountered within the input data, there are three
-strategies available for their handling: (1) \code{"gap"} will display data gaps
-at the sites of missing data, where data lines will have discontinuities;
-(2) \code{"zero"} will replace \code{NA} values with zero values; and (3) \code{"remove"}
-will remove any incoming \code{NA} values.}
+strategies available for their handling: (1) \code{"gap"} will show data gaps
+at the sites of missing data, where data lines will have discontinuities
+and bar plots will have missing bars; (2) \code{"marker"} will behave like
+\code{"gap"} but show prominent visual marks at the missing data locations; (3)
+\code{"zero"} will replace \code{NA} values with zero values; and (4) \code{"remove"} will
+remove any incoming \code{NA} values.}
 
 \item{autoscale}{\emph{Automatically set x- and y-axis scale limits based on data}