diff --git a/NEWS.md b/NEWS.md
index e8b56db2bc..d2f9a43fe1 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,5 +1,10 @@
 # tern 0.9.6.9007
 
+### Enhancements
+* Added the `denom` parameter to `s_count_cumulative()`, `s_count_missed_doses()`, and `s_count_occurrences_by_grade()`.
+* Added `"N_row"` as an optional input to `denom` in `s_count_occurrences()`.
+* Refactored `a_count_occurrences_by_grade()` to no longer use `make_afun()`.
+
 ### Bug Fixes
 * Fixed bug in `a_summary()` causing non-unique `row_name` values to occur when multiple statistics are selected for count variables.
 
@@ -15,7 +20,7 @@
 * Refactored `estimate_incidence_rate` to work as both an analyze function and a summarize function, controlled by the added `summarize` parameter. When `summarize = TRUE`, labels can be fine-tuned via the new `label_fmt` argument to the same function.
 * Added `fraction` statistic to the `analyze_var_count` method group.
 * Improved `summarize_glm_count()` documentation and all its associated functions to better describe the results and the functions' purpose.
-* Added `method` argument to `s_odds_ratio()` and `estimate_odds_ratio()` to control whether exact or approximate conditional likelihood calculations are used. 
+* Added `method` argument to `s_odds_ratio()` and `estimate_odds_ratio()` to control whether exact or approximate conditional likelihood calculations are used.
 
 ### Bug Fixes
 * Added defaults for `d_count_cumulative` parameters as described in the documentation.
@@ -72,7 +77,7 @@
 ### Miscellaneous
 * Added function `expect_snapshot_ggplot` to test setup file to process plot snapshot tests and allow plot dimensions to be set.
 * Adapted to argument renames introduced in `ggplot2` 3.5.0.
-* Renamed `individual_patient_plot.R` to `g_ipp.R`. 
+* Renamed `individual_patient_plot.R` to `g_ipp.R`.
 * Removed all instances of deprecated parameters `time_unit_input`, `time_unit_output`, `na_level` and `indent_mod`.
 * Removed deprecated functions `summarize_vars`, `control_summarize_vars`, `a_compare`, `create_afun_summary`, `create_afun_compare`, and `summary_custom`.
 * Removed `vdiffr` package from Suggests in DESCRIPTION file.
diff --git a/R/analyze_variables.R b/R/analyze_variables.R
index 5a8ae1c31f..5af2961f10 100644
--- a/R/analyze_variables.R
+++ b/R/analyze_variables.R
@@ -238,11 +238,6 @@ s_summary.numeric <- function(x,
 
 #' @describeIn analyze_variables Method for `factor` class.
 #'
-#' @param denom (`string`)\cr choice of denominator for factor proportions. Options are:
-#'   * `n`: number of values in this row and column intersection.
-#'   * `N_row`: total number of values in this row across columns.
-#'   * `N_col`: total number of values in this column across rows.
-#'
 #' @return
 #'   * If `x` is of class `factor` or converted from `character`, returns a `list` with named `numeric` items:
 #'     * `n`: The [length()] of `x`.
@@ -283,12 +278,11 @@ s_summary.numeric <- function(x,
 #' @export
 s_summary.factor <- function(x,
                              na.rm = TRUE, # nolint
-                             denom = c("n", "N_row", "N_col"),
+                             denom = c("n", "N_col", "N_row"),
                              .N_row, # nolint
                              .N_col, # nolint
                              ...) {
   assert_valid_factor(x)
-  denom <- match.arg(denom)
 
   if (na.rm) {
     x <- x[!is.na(x)] %>% fct_discard("<Missing>")
@@ -301,20 +295,23 @@ s_summary.factor <- function(x,
   y$n <- length(x)
 
   y$count <- as.list(table(x, useNA = "ifany"))
-  dn <- switch(denom,
-    n = length(x),
-    N_row = .N_row,
-    N_col = .N_col
-  )
+
+  denom <- match.arg(denom) %>%
+    switch(
+      n = length(x),
+      N_row = .N_row,
+      N_col = .N_col
+    )
+
   y$count_fraction <- lapply(
     y$count,
     function(x) {
-      c(x, ifelse(dn > 0, x / dn, 0))
+      c(x, ifelse(denom > 0, x / denom, 0))
     }
   )
   y$fraction <- lapply(
     y$count,
-    function(count) c("num" = count, "denom" = dn)
+    function(count) c("num" = count, "denom" = denom)
   )
 
   y$n_blq <- sum(grepl("BLQ|LTR|<[1-9]|<PCLLOQ", x))
@@ -346,7 +343,7 @@ s_summary.factor <- function(x,
 #' @export
 s_summary.character <- function(x,
                                 na.rm = TRUE, # nolint
-                                denom = c("n", "N_row", "N_col"),
+                                denom = c("n", "N_col", "N_row"),
                                 .N_row, # nolint
                                 .N_col, # nolint
                                 .var,
@@ -370,11 +367,6 @@ s_summary.character <- function(x,
 
 #' @describeIn analyze_variables Method for `logical` class.
 #'
-#' @param denom (`string`)\cr choice of denominator for proportion. Options are:
-#'   * `n`: number of values in this row and column intersection.
-#'   * `N_row`: total number of values in this row across columns.
-#'   * `N_col`: total number of values in this column across rows.
-#'
 #' @return
 #'   * If `x` is of class `logical`, returns a `list` with named `numeric` items:
 #'     * `n`: The [length()] of `x` (possibly after removing `NA`s).
@@ -406,22 +398,22 @@ s_summary.character <- function(x,
 #' @export
 s_summary.logical <- function(x,
                               na.rm = TRUE, # nolint
-                              denom = c("n", "N_row", "N_col"),
+                              denom = c("n", "N_col", "N_row"),
                               .N_row, # nolint
                               .N_col, # nolint
                               ...) {
-  denom <- match.arg(denom)
   if (na.rm) x <- x[!is.na(x)]
   y <- list()
   y$n <- length(x)
   count <- sum(x, na.rm = TRUE)
-  dn <- switch(denom,
-    n = length(x),
-    N_row = .N_row,
-    N_col = .N_col
-  )
+  denom <- match.arg(denom) %>%
+    switch(
+      n = length(x),
+      N_row = .N_row,
+      N_col = .N_col
+    )
   y$count <- count
-  y$count_fraction <- c(count, ifelse(dn > 0, count / dn, 0))
+  y$count_fraction <- c(count, ifelse(denom > 0, count / denom, 0))
   y$n_blq <- 0L
   y
 }
diff --git a/R/argument_convention.R b/R/argument_convention.R
index e2b64b31c1..9e48b22308 100644
--- a/R/argument_convention.R
+++ b/R/argument_convention.R
@@ -30,6 +30,10 @@
 #' @param col_by (`factor`)\cr defining column groups.
 #' @param conf_level (`proportion`)\cr confidence level of the interval.
 #' @param data (`data.frame`)\cr the dataset containing the variables to summarize.
+#' @param denom (`string`)\cr choice of denominator for proportion. Options are:
+#'   * `n`: number of values in this row and column intersection.
+#'   * `N_row`: total number of values in this row across columns.
+#'   * `N_col`: total number of values in this column across rows.
 #' @param df (`data.frame`)\cr data set containing all analysis variables.
 #' @param groups_lists (named `list` of `list`)\cr optionally contains for each `subgroups` variable a
 #'   list, which specifies the new group levels via the names and the
diff --git a/R/count_cumulative.R b/R/count_cumulative.R
index 90ee067f8b..0022c5c98e 100644
--- a/R/count_cumulative.R
+++ b/R/count_cumulative.R
@@ -78,7 +78,10 @@ h_count_cumulative <- function(x,
     length(x[is_keep & x > threshold])
   }
 
-  result <- c(count = count, fraction = count / .N_col)
+  result <- c(
+    count = count,
+    fraction = if (count == 0 && .N_col == 0) 0 else count / .N_col
+  )
   result
 }
 
@@ -112,11 +115,20 @@ s_count_cumulative <- function(x,
                                lower_tail = TRUE,
                                include_eq = TRUE,
                                .N_col, # nolint
+                               .N_row, # nolint
+                               denom = c("N_col", "n", "N_row"),
                                ...) {
   checkmate::assert_numeric(thresholds, min.len = 1, any.missing = FALSE)
 
+  denom <- match.arg(denom) %>%
+    switch(
+      n = length(x),
+      N_row = .N_row,
+      N_col = .N_col
+    )
+
   count_fraction_list <- Map(function(thres) {
-    result <- h_count_cumulative(x, thres, lower_tail, include_eq, .N_col = .N_col, ...)
+    result <- h_count_cumulative(x, thres, lower_tail, include_eq, .N_col = denom, ...)
     label <- d_count_cumulative(thres, lower_tail, include_eq)
     formatters::with_label(result, label)
   }, thresholds)
diff --git a/R/count_missed_doses.R b/R/count_missed_doses.R
index 239b40ad01..8b3153cf47 100644
--- a/R/count_missed_doses.R
+++ b/R/count_missed_doses.R
@@ -58,13 +58,17 @@ d_count_missed_doses <- function(thresholds) {
 #' @keywords internal
 s_count_missed_doses <- function(x,
                                  thresholds,
-                                 .N_col) { # nolint
+                                 .N_col, # nolint
+                                 .N_row, # nolint
+                                 denom = c("N_col", "n", "N_row")) {
   stat <- s_count_cumulative(
     x = x,
     thresholds = thresholds,
     lower_tail = FALSE,
     include_eq = TRUE,
-    .N_col = .N_col
+    .N_col = .N_col,
+    .N_row = .N_row,
+    denom = denom
   )
   labels <- d_count_missed_doses(thresholds)
   for (i in seq_along(stat$count_fraction)) {
diff --git a/R/count_occurrences.R b/R/count_occurrences.R
index 73052eb08c..1802eb80a1 100644
--- a/R/count_occurrences.R
+++ b/R/count_occurrences.R
@@ -51,9 +51,10 @@ NULL
 #' @describeIn count_occurrences Statistics function which counts number of patients that report an
 #' occurrence.
 #'
-#' @param denom (`string`)\cr choice of denominator for patient proportions. Can be:
-#'   - `N_col`: total number of patients in this column across rows
-#'   - `n`: number of patients with any occurrences
+#' @param denom (`string`)\cr choice of denominator for proportion. Options are:
+#'   * `N_col`: total number of patients in this column across rows.
+#'   * `n`: number of patients with any occurrences.
+#'   * `N_row`: total number of patients in this row across columns.
 #'
 #' @return
 #' * `s_count_occurrences()` returns a list with:
@@ -66,6 +67,7 @@ NULL
 #' s_count_occurrences(
 #'   df,
 #'   .N_col = 4L,
+#'   .N_row = 4L,
 #'   .df_row = df,
 #'   .var = "MHDECOD",
 #'   id = "USUBJID"
@@ -73,8 +75,9 @@ NULL
 #'
 #' @export
 s_count_occurrences <- function(df,
-                                denom = c("N_col", "n"),
+                                denom = c("N_col", "n", "N_row"),
                                 .N_col, # nolint
+                                .N_row, # nolint
                                 .df_row,
                                 drop = TRUE,
                                 .var = "MHDECOD",
@@ -84,7 +87,6 @@ s_count_occurrences <- function(df,
   checkmate::assert_count(.N_col)
   checkmate::assert_multi_class(df[[.var]], classes = c("factor", "character"))
   checkmate::assert_multi_class(df[[id]], classes = c("factor", "character"))
-  denom <- match.arg(denom)
 
   occurrences <- if (drop) {
     # Note that we don't try to preserve original level order here since a) that would required
@@ -101,10 +103,12 @@ s_count_occurrences <- function(df,
     df[[.var]]
   }
   ids <- factor(df[[id]])
-  dn <- switch(denom,
-    n = nlevels(ids),
-    N_col = .N_col
-  )
+  denom <- match.arg(denom) %>%
+    switch(
+      n = nlevels(ids),
+      N_row = .N_row,
+      N_col = .N_col
+    )
   has_occurrence_per_id <- table(occurrences, ids) > 0
   n_ids_per_occurrence <- as.list(rowSums(has_occurrence_per_id))
   list(
@@ -118,12 +122,12 @@ s_count_occurrences <- function(df,
           c(i, i / denom)
         }
       },
-      denom = dn
+      denom = denom
     ),
     fraction = lapply(
       n_ids_per_occurrence,
       function(i, denom) c("num" = i, "denom" = denom),
-      denom = dn
+      denom = denom
     )
   )
 }
@@ -147,9 +151,10 @@ s_count_occurrences <- function(df,
 a_count_occurrences <- function(df,
                                 labelstr = "",
                                 id = "USUBJID",
-                                denom = c("N_col", "n"),
+                                denom = c("N_col", "n", "N_row"),
                                 drop = TRUE,
                                 .N_col, # nolint
+                                .N_row, # nolint
                                 .var = NULL,
                                 .df_row = NULL,
                                 .stats = NULL,
@@ -159,7 +164,7 @@ a_count_occurrences <- function(df,
                                 na_str = default_na_str()) {
   denom <- match.arg(denom)
   x_stats <- s_count_occurrences(
-    df = df, denom = denom, .N_col = .N_col, .df_row = .df_row, drop = drop, .var = .var, id = id
+    df = df, denom = denom, .N_col = .N_col, .N_row = .N_row, .df_row = .df_row, drop = drop, .var = .var, id = id
   )
   if (is.null(unlist(x_stats))) {
     return(NULL)
diff --git a/R/count_occurrences_by_grade.R b/R/count_occurrences_by_grade.R
index d77a049a7a..d23001605d 100644
--- a/R/count_occurrences_by_grade.R
+++ b/R/count_occurrences_by_grade.R
@@ -16,6 +16,7 @@
 #' row/column context and operates on the level of the latest row split or the root of the table if no row splits have
 #' occurred.
 #'
+#' @inheritParams count_occurrences
 #' @inheritParams argument_convention
 #' @param grade_groups (named `list` of `character`)\cr list containing groupings of grades.
 #' @param remove_single (`flag`)\cr `TRUE` to not include the elements of one-element grade groups
@@ -149,15 +150,24 @@ h_append_grade_groups <- function(grade_groups, refs, remove_single = TRUE, only
 #' @export
 s_count_occurrences_by_grade <- function(df,
                                          .var,
+                                         .N_row, # nolint
                                          .N_col, # nolint
                                          id = "USUBJID",
                                          grade_groups = list(),
                                          remove_single = TRUE,
                                          only_grade_groups = FALSE,
+                                         denom = c("N_col", "n", "N_row"),
                                          labelstr = "") {
   assert_valid_factor(df[[.var]])
   assert_df_with_variables(df, list(grade = .var, id = id))
 
+  denom <- match.arg(denom) %>%
+    switch(
+      n = nlevels(factor(df[[id]])),
+      N_row = .N_row,
+      N_col = .N_col
+    )
+
   if (nrow(df) < 1) {
     grade_levels <- levels(df[[.var]])
     l_count <- as.list(rep(0, length(grade_levels)))
@@ -201,7 +211,17 @@ s_count_occurrences_by_grade <- function(df,
     l_count <- h_append_grade_groups(grade_groups, l_count, remove_single, only_grade_groups)
   }
 
-  l_count_fraction <- lapply(l_count, function(i, denom) c(i, i / denom), denom = .N_col)
+  l_count_fraction <- lapply(
+    l_count,
+    function(i, denom) {
+      if (i == 0 && denom == 0) {
+        c(0, 0)
+      } else {
+        c(i, i / denom)
+      }
+    },
+    denom = denom
+  )
 
   list(
     count_fraction = l_count_fraction
@@ -215,22 +235,72 @@ s_count_occurrences_by_grade <- function(df,
 #' * `a_count_occurrences_by_grade()` returns the corresponding list with formatted [rtables::CellValue()].
 #'
 #' @examples
-#' #  We need to ungroup `count_fraction` first so that the `rtables` formatting
-#' # function `format_count_fraction()` can be applied correctly.
-#' afun <- make_afun(a_count_occurrences_by_grade, .ungroup_stats = "count_fraction")
-#' afun(
+#' a_count_occurrences_by_grade(
 #'   df,
 #'   .N_col = 10L,
+#'   .N_row = 10L,
 #'   .var = "AETOXGR",
 #'   id = "USUBJID",
 #'   grade_groups = list("ANY" = levels(df$AETOXGR))
 #' )
 #'
 #' @export
-a_count_occurrences_by_grade <- make_afun(
-  s_count_occurrences_by_grade,
-  .formats = c("count_fraction" = format_count_fraction_fixed_dp)
-)
+a_count_occurrences_by_grade <- function(df,
+                                         labelstr = "",
+                                         id = "USUBJID",
+                                         grade_groups = list(),
+                                         remove_single = TRUE,
+                                         only_grade_groups = FALSE,
+                                         denom = c("N_col", "n", "N_row"),
+                                         .N_col, # nolint
+                                         .N_row, # nolint
+                                         .df_row,
+                                         .var = NULL,
+                                         .stats = NULL,
+                                         .formats = NULL,
+                                         .labels = NULL,
+                                         .indent_mods = NULL,
+                                         na_str = default_na_str()) {
+  x_stats <- s_count_occurrences_by_grade(
+    df = df, .var = .var, .N_row = .N_row, .N_col = .N_col, id = id,
+    grade_groups = grade_groups, remove_single = remove_single, only_grade_groups = only_grade_groups,
+    denom = denom, labelstr = labelstr
+  )
+
+  if (is.null(unlist(x_stats))) {
+    return(NULL)
+  }
+  x_lvls <- names(x_stats[[1]])
+
+  # Fill in with formatting defaults if needed
+  .stats <- get_stats("count_occurrences_by_grade", stats_in = .stats)
+  if (length(.formats) == 1 && is.null(names(.formats))) {
+    .formats <- rep(.formats, length(.stats)) %>% setNames(.stats)
+  }
+  .formats <- get_formats_from_stats(.stats, .formats)
+  .labels <- get_labels_from_stats(.stats, .labels, row_nms = x_lvls)
+  .indent_mods <- get_indents_from_stats(.stats, .indent_mods, row_nms = x_lvls)
+
+  if ("count_fraction_fixed_dp" %in% .stats) x_stats[["count_fraction_fixed_dp"]] <- x_stats[["count_fraction"]]
+  x_stats <- x_stats[.stats]
+
+  # Ungroup statistics with values for each level of x
+  x_ungrp <- ungroup_stats(x_stats, .formats, .labels, list())
+  x_stats <- x_ungrp[["x"]]
+  .formats <- x_ungrp[[".formats"]]
+
+  # Auto format handling
+  .formats <- apply_auto_formatting(.formats, x_stats, .df_row, .var)
+
+  in_rows(
+    .list = x_stats,
+    .formats = .formats,
+    .names = unlist(.labels),
+    .labels = unlist(.labels),
+    .indent_mods = .indent_mods,
+    .format_na_strs = na_str
+  )
+}
 
 #' @describeIn count_occurrences_by_grade Layout-creating function which can take statistics function
 #'   arguments and additional format arguments. This function is a wrapper for [rtables::analyze()].
@@ -300,40 +370,36 @@ count_occurrences_by_grade <- function(lyt,
                                        nested = TRUE,
                                        ...,
                                        table_names = var,
-                                       .stats = NULL,
-                                       .formats = NULL,
+                                       .stats = "count_fraction",
+                                       .formats = list(count_fraction = format_count_fraction_fixed_dp),
                                        .indent_mods = NULL,
                                        .labels = NULL) {
   checkmate::assert_flag(riskdiff)
+  extra_args <- list(
+    .stats = .stats, .formats = .formats, .labels = .labels, .indent_mods = .indent_mods, na_str = na_str
+  )
   s_args <- list(
     id = id, grade_groups = grade_groups, remove_single = remove_single, only_grade_groups = only_grade_groups, ...
   )
 
-  afun <- make_afun(
-    a_count_occurrences_by_grade,
-    .stats = .stats,
-    .formats = .formats,
-    .indent_mods = .indent_mods,
-    .ungroup_stats = "count_fraction"
-  )
-
-  extra_args <- if (isFALSE(riskdiff)) {
-    s_args
+  if (isFALSE(riskdiff)) {
+    extra_args <- c(extra_args, s_args)
   } else {
-    list(
-      afun = list("s_count_occurrences_by_grade" = afun),
-      .stats = .stats,
-      .indent_mods = .indent_mods,
-      s_args = s_args
+    extra_args <- c(
+      extra_args,
+      list(
+        afun = list("s_count_occurrences_by_grade" = a_count_occurrences_by_grade),
+        s_args = s_args
+      )
     )
   }
 
   analyze(
     lyt = lyt,
     vars = var,
+    afun = ifelse(isFALSE(riskdiff), a_count_occurrences_by_grade, afun_riskdiff),
     var_labels = var_labels,
     show_labels = show_labels,
-    afun = ifelse(isFALSE(riskdiff), afun, afun_riskdiff),
     table_names = table_names,
     na_str = na_str,
     nested = nested,
@@ -377,29 +443,37 @@ summarize_occurrences_by_grade <- function(lyt,
                                            grade_groups = list(),
                                            remove_single = TRUE,
                                            only_grade_groups = FALSE,
+                                           riskdiff = FALSE,
                                            na_str = default_na_str(),
                                            ...,
-                                           .stats = NULL,
-                                           .formats = NULL,
+                                           .stats = "count_fraction",
+                                           .formats = list(count_fraction = format_count_fraction_fixed_dp),
                                            .indent_mods = NULL,
                                            .labels = NULL) {
+  checkmate::assert_flag(riskdiff)
   extra_args <- list(
+    .stats = .stats, .formats = .formats, .labels = .labels, .indent_mods = .indent_mods, na_str = na_str
+  )
+  s_args <- list(
     id = id, grade_groups = grade_groups, remove_single = remove_single, only_grade_groups = only_grade_groups, ...
   )
 
-  cfun <- make_afun(
-    a_count_occurrences_by_grade,
-    .stats = .stats,
-    .formats = .formats,
-    .labels = .labels,
-    .indent_mods = .indent_mods,
-    .ungroup_stats = "count_fraction"
-  )
+  if (isFALSE(riskdiff)) {
+    extra_args <- c(extra_args, s_args)
+  } else {
+    extra_args <- c(
+      extra_args,
+      list(
+        afun = list("s_count_occurrences_by_grade" = a_count_occurrences_by_grade),
+        s_args = s_args
+      )
+    )
+  }
 
   summarize_row_groups(
     lyt = lyt,
     var = var,
-    cfun = cfun,
+    cfun = ifelse(isFALSE(riskdiff), a_count_occurrences_by_grade, afun_riskdiff),
     na_str = na_str,
     extra_args = extra_args
   )
diff --git a/R/count_patients_with_event.R b/R/count_patients_with_event.R
index fb4275fcf6..995873bef9 100644
--- a/R/count_patients_with_event.R
+++ b/R/count_patients_with_event.R
@@ -65,7 +65,7 @@ s_count_patients_with_event <- function(df,
                                         filters,
                                         .N_col, # nolint
                                         .N_row, # nolint
-                                        denom = c("n", "N_row", "N_col")) {
+                                        denom = c("n", "N_col", "N_row")) {
   col_names <- names(filters)
   filter_values <- filters
 
diff --git a/R/count_patients_with_flags.R b/R/count_patients_with_flags.R
index e7fd062639..57272b36f0 100644
--- a/R/count_patients_with_flags.R
+++ b/R/count_patients_with_flags.R
@@ -58,7 +58,7 @@ s_count_patients_with_flags <- function(df,
                                         flag_labels = NULL,
                                         .N_col, # nolint
                                         .N_row, # nolint
-                                        denom = c("n", "N_row", "N_col")) {
+                                        denom = c("n", "N_col", "N_row")) {
   checkmate::assert_character(flag_variables)
   if (!is.null(flag_labels)) {
     checkmate::assert_character(flag_labels, len = length(flag_variables), any.missing = FALSE)
diff --git a/R/count_values.R b/R/count_values.R
index 4009e543a7..4f7b475eea 100644
--- a/R/count_values.R
+++ b/R/count_values.R
@@ -38,7 +38,7 @@ s_count_values <- function(x,
                            na.rm = TRUE, # nolint
                            .N_col, # nolint
                            .N_row, # nolint
-                           denom = c("n", "N_row", "N_col")) {
+                           denom = c("n", "N_col", "N_row")) {
   UseMethod("s_count_values", x)
 }
 
diff --git a/man/analyze_variables.Rd b/man/analyze_variables.Rd
index ac83afe9f1..18a6b603dc 100644
--- a/man/analyze_variables.Rd
+++ b/man/analyze_variables.Rd
@@ -44,7 +44,7 @@ s_summary(x, na.rm = TRUE, denom, .N_row, .N_col, .var, ...)
 \method{s_summary}{factor}(
   x,
   na.rm = TRUE,
-  denom = c("n", "N_row", "N_col"),
+  denom = c("n", "N_col", "N_row"),
   .N_row,
   .N_col,
   ...
@@ -53,7 +53,7 @@ s_summary(x, na.rm = TRUE, denom, .N_row, .N_col, .var, ...)
 \method{s_summary}{character}(
   x,
   na.rm = TRUE,
-  denom = c("n", "N_row", "N_col"),
+  denom = c("n", "N_col", "N_row"),
   .N_row,
   .N_col,
   .var,
@@ -64,7 +64,7 @@ s_summary(x, na.rm = TRUE, denom, .N_row, .N_col, .var, ...)
 \method{s_summary}{logical}(
   x,
   na.rm = TRUE,
-  denom = c("n", "N_row", "N_col"),
+  denom = c("n", "N_col", "N_row"),
   .N_row,
   .N_col,
   ...
diff --git a/man/argument_convention.Rd b/man/argument_convention.Rd
index 775937acba..f973f4135c 100644
--- a/man/argument_convention.Rd
+++ b/man/argument_convention.Rd
@@ -49,6 +49,13 @@ that constitute the split. A custom label can be set for this level via the \cod
 
 \item{data}{(\code{data.frame})\cr the dataset containing the variables to summarize.}
 
+\item{denom}{(\code{string})\cr choice of denominator for proportion. Options are:
+\itemize{
+\item \code{n}: number of values in this row and column intersection.
+\item \code{N_row}: total number of values in this row across columns.
+\item \code{N_col}: total number of values in this column across rows.
+}}
+
 \item{df}{(\code{data.frame})\cr data set containing all analysis variables.}
 
 \item{groups_lists}{(named \code{list} of \code{list})\cr optionally contains for each \code{subgroups} variable a
diff --git a/man/count_cumulative.Rd b/man/count_cumulative.Rd
index b5cba3acd5..86d3cfb773 100644
--- a/man/count_cumulative.Rd
+++ b/man/count_cumulative.Rd
@@ -30,6 +30,8 @@ s_count_cumulative(
   lower_tail = TRUE,
   include_eq = TRUE,
   .N_col,
+  .N_row,
+  denom = c("N_col", "n", "N_row"),
   ...
 )
 
@@ -39,6 +41,8 @@ a_count_cumulative(
   lower_tail = TRUE,
   include_eq = TRUE,
   .N_col,
+  .N_row,
+  denom = c("N_col", "n", "N_row"),
   ...
 )
 }
@@ -85,6 +89,16 @@ unmodified default behavior. Can be negative.}
 
 \item{.N_col}{(\code{integer(1)})\cr column-wise N (column count) for the full column being analyzed that is typically
 passed by \code{rtables}.}
+
+\item{.N_row}{(\code{integer(1)})\cr row-wise N (row group count) for the group of observations being analyzed
+(i.e. with no column-based subsetting) that is typically passed by \code{rtables}.}
+
+\item{denom}{(\code{string})\cr choice of denominator for proportion. Options are:
+\itemize{
+\item \code{n}: number of values in this row and column intersection.
+\item \code{N_row}: total number of values in this row across columns.
+\item \code{N_col}: total number of values in this column across rows.
+}}
 }
 \value{
 \itemize{
diff --git a/man/count_missed_doses.Rd b/man/count_missed_doses.Rd
index 3b2768f0e3..262c573a49 100644
--- a/man/count_missed_doses.Rd
+++ b/man/count_missed_doses.Rd
@@ -25,9 +25,21 @@ count_missed_doses(
 
 s_count_nonmissing(x)
 
-s_count_missed_doses(x, thresholds, .N_col)
+s_count_missed_doses(
+  x,
+  thresholds,
+  .N_col,
+  .N_row,
+  denom = c("N_col", "n", "N_row")
+)
 
-a_count_missed_doses(x, thresholds, .N_col)
+a_count_missed_doses(
+  x,
+  thresholds,
+  .N_col,
+  .N_row,
+  denom = c("N_col", "n", "N_row")
+)
 }
 \arguments{
 \item{lyt}{(\code{PreDataTableLayouts})\cr layout that analyses will be added to.}
@@ -67,6 +79,16 @@ unmodified default behavior. Can be negative.}
 
 \item{.N_col}{(\code{integer(1)})\cr column-wise N (column count) for the full column being analyzed that is typically
 passed by \code{rtables}.}
+
+\item{.N_row}{(\code{integer(1)})\cr row-wise N (row group count) for the group of observations being analyzed
+(i.e. with no column-based subsetting) that is typically passed by \code{rtables}.}
+
+\item{denom}{(\code{string})\cr choice of denominator for proportion. Options are:
+\itemize{
+\item \code{n}: number of values in this row and column intersection.
+\item \code{N_row}: total number of values in this row across columns.
+\item \code{N_col}: total number of values in this column across rows.
+}}
 }
 \value{
 \itemize{
diff --git a/man/count_occurrences.Rd b/man/count_occurrences.Rd
index 856f6f29e1..b7b7320aed 100644
--- a/man/count_occurrences.Rd
+++ b/man/count_occurrences.Rd
@@ -41,8 +41,9 @@ summarize_occurrences(
 
 s_count_occurrences(
   df,
-  denom = c("N_col", "n"),
+  denom = c("N_col", "n", "N_row"),
   .N_col,
+  .N_row,
   .df_row,
   drop = TRUE,
   .var = "MHDECOD",
@@ -53,9 +54,10 @@ a_count_occurrences(
   df,
   labelstr = "",
   id = "USUBJID",
-  denom = c("N_col", "n"),
+  denom = c("N_col", "n", "N_row"),
   drop = TRUE,
   .N_col,
+  .N_row,
   .var = NULL,
   .df_row = NULL,
   .stats = NULL,
@@ -108,15 +110,19 @@ unmodified default behavior. Can be negative.}
 
 \item{df}{(\code{data.frame})\cr data set containing all analysis variables.}
 
-\item{denom}{(\code{string})\cr choice of denominator for patient proportions. Can be:
+\item{denom}{(\code{string})\cr choice of denominator for proportion. Options are:
 \itemize{
-\item \code{N_col}: total number of patients in this column across rows
-\item \code{n}: number of patients with any occurrences
+\item \code{N_col}: total number of patients in this column across rows.
+\item \code{n}: number of patients with any occurrences.
+\item \code{N_row}: total number of patients in this row across columns.
 }}
 
 \item{.N_col}{(\code{integer(1)})\cr column-wise N (column count) for the full column being analyzed that is typically
 passed by \code{rtables}.}
 
+\item{.N_row}{(\code{integer(1)})\cr row-wise N (row group count) for the group of observations being analyzed
+(i.e. with no column-based subsetting) that is typically passed by \code{rtables}.}
+
 \item{.df_row}{(\code{data.frame})\cr data frame across all of the columns for the given row split.}
 
 \item{.var, var}{(\code{string})\cr single variable name that is passed by \code{rtables} when requested
@@ -233,6 +239,7 @@ basic_table() \%>\%
 s_count_occurrences(
   df,
   .N_col = 4L,
+  .N_row = 4L,
   .df_row = df,
   .var = "MHDECOD",
   id = "USUBJID"
diff --git a/man/count_occurrences_by_grade.Rd b/man/count_occurrences_by_grade.Rd
index 547fa84d69..5c6df5f444 100644
--- a/man/count_occurrences_by_grade.Rd
+++ b/man/count_occurrences_by_grade.Rd
@@ -21,8 +21,8 @@ count_occurrences_by_grade(
   nested = TRUE,
   ...,
   table_names = var,
-  .stats = NULL,
-  .formats = NULL,
+  .stats = "count_fraction",
+  .formats = list(count_fraction = format_count_fraction_fixed_dp),
   .indent_mods = NULL,
   .labels = NULL
 )
@@ -34,10 +34,11 @@ summarize_occurrences_by_grade(
   grade_groups = list(),
   remove_single = TRUE,
   only_grade_groups = FALSE,
+  riskdiff = FALSE,
   na_str = default_na_str(),
   ...,
-  .stats = NULL,
-  .formats = NULL,
+  .stats = "count_fraction",
+  .formats = list(count_fraction = format_count_fraction_fixed_dp),
   .indent_mods = NULL,
   .labels = NULL
 )
@@ -45,23 +46,33 @@ summarize_occurrences_by_grade(
 s_count_occurrences_by_grade(
   df,
   .var,
+  .N_row,
   .N_col,
   id = "USUBJID",
   grade_groups = list(),
   remove_single = TRUE,
   only_grade_groups = FALSE,
+  denom = c("N_col", "n", "N_row"),
   labelstr = ""
 )
 
 a_count_occurrences_by_grade(
   df,
-  .var,
-  .N_col,
+  labelstr = "",
   id = "USUBJID",
   grade_groups = list(),
   remove_single = TRUE,
   only_grade_groups = FALSE,
-  labelstr = ""
+  denom = c("N_col", "n", "N_row"),
+  .N_col,
+  .N_row,
+  .df_row,
+  .var = NULL,
+  .stats = NULL,
+  .formats = NULL,
+  .labels = NULL,
+  .indent_mods = NULL,
+  na_str = default_na_str()
 )
 }
 \arguments{
@@ -115,12 +126,24 @@ unmodified default behavior. Can be negative.}
 \item{.var, var}{(\code{string})\cr single variable name that is passed by \code{rtables} when requested
 by a statistics function.}
 
+\item{.N_row}{(\code{integer(1)})\cr row-wise N (row group count) for the group of observations being analyzed
+(i.e. with no column-based subsetting) that is typically passed by \code{rtables}.}
+
 \item{.N_col}{(\code{integer(1)})\cr column-wise N (column count) for the full column being analyzed that is typically
 passed by \code{rtables}.}
 
+\item{denom}{(\code{string})\cr choice of denominator for proportion. Options are:
+\itemize{
+\item \code{N_col}: total number of patients in this column across rows.
+\item \code{n}: number of patients with any occurrences.
+\item \code{N_row}: total number of patients in this row across columns.
+}}
+
 \item{labelstr}{(\code{string})\cr label of the level of the parent split currently being summarized
 (must be present as second argument in Content Row Functions). See \code{\link[rtables:summarize_row_groups]{rtables::summarize_row_groups()}}
 for more information.}
+
+\item{.df_row}{(\code{data.frame})\cr data frame across all of the columns for the given row split.}
 }
 \value{
 \itemize{
@@ -248,12 +271,10 @@ s_count_occurrences_by_grade(
   grade_groups = list("ANY" = levels(df$AETOXGR))
 )
 
-#  We need to ungroup `count_fraction` first so that the `rtables` formatting
-# function `format_count_fraction()` can be applied correctly.
-afun <- make_afun(a_count_occurrences_by_grade, .ungroup_stats = "count_fraction")
-afun(
+a_count_occurrences_by_grade(
   df,
   .N_col = 10L,
+  .N_row = 10L,
   .var = "AETOXGR",
   id = "USUBJID",
   grade_groups = list("ANY" = levels(df$AETOXGR))
diff --git a/man/count_patients_with_event.Rd b/man/count_patients_with_event.Rd
index 841bc102e5..a9aafc9a6d 100644
--- a/man/count_patients_with_event.Rd
+++ b/man/count_patients_with_event.Rd
@@ -27,7 +27,7 @@ s_count_patients_with_event(
   filters,
   .N_col,
   .N_row,
-  denom = c("n", "N_row", "N_col")
+  denom = c("n", "N_col", "N_row")
 )
 
 a_count_patients_with_event(
@@ -36,7 +36,7 @@ a_count_patients_with_event(
   filters,
   .N_col,
   .N_row,
-  denom = c("n", "N_row", "N_col")
+  denom = c("n", "N_col", "N_row")
 )
 }
 \arguments{
diff --git a/man/count_patients_with_flags.Rd b/man/count_patients_with_flags.Rd
index 1e9fe8a013..5cade48d70 100644
--- a/man/count_patients_with_flags.Rd
+++ b/man/count_patients_with_flags.Rd
@@ -30,7 +30,7 @@ s_count_patients_with_flags(
   flag_labels = NULL,
   .N_col,
   .N_row,
-  denom = c("n", "N_row", "N_col")
+  denom = c("n", "N_col", "N_row")
 )
 
 a_count_patients_with_flags(
@@ -40,7 +40,7 @@ a_count_patients_with_flags(
   flag_labels = NULL,
   .N_col,
   .N_row,
-  denom = c("n", "N_row", "N_col")
+  denom = c("n", "N_col", "N_row")
 )
 }
 \arguments{
diff --git a/man/count_values.Rd b/man/count_values.Rd
index 91c8660aa9..39b44918ba 100644
--- a/man/count_values.Rd
+++ b/man/count_values.Rd
@@ -29,7 +29,7 @@ s_count_values(
   na.rm = TRUE,
   .N_col,
   .N_row,
-  denom = c("n", "N_row", "N_col")
+  denom = c("n", "N_col", "N_row")
 )
 
 \method{s_count_values}{character}(x, values = "Y", na.rm = TRUE, ...)
@@ -44,7 +44,7 @@ a_count_values(
   na.rm = TRUE,
   .N_col,
   .N_row,
-  denom = c("n", "N_row", "N_col")
+  denom = c("n", "N_col", "N_row")
 )
 }
 \arguments{
diff --git a/tests/testthat/_snaps/count_cumulative.md b/tests/testthat/_snaps/count_cumulative.md
index a7f11e2bff..928125ec98 100644
--- a/tests/testthat/_snaps/count_cumulative.md
+++ b/tests/testthat/_snaps/count_cumulative.md
@@ -76,3 +76,19 @@
         > 3   3 (60%)   4 (66.7%)
         > 7   1 (20%)   2 (33.3%)
 
+# count_cumulative works with denom argument specified
+
+    Code
+      res
+    Output
+                   A         B    
+      ————————————————————————————
+      x            5         2    
+        a                         
+          > 3   3 (60%)   1 (100%)
+          > 7   1 (20%)   1 (100%)
+      y            0         4    
+        a                         
+          > 3      0      3 (75%) 
+          > 7      0      1 (25%) 
+
diff --git a/tests/testthat/_snaps/count_missed_doses.md b/tests/testthat/_snaps/count_missed_doses.md
index 5b9ab387bb..34981b9674 100644
--- a/tests/testthat/_snaps/count_missed_doses.md
+++ b/tests/testthat/_snaps/count_missed_doses.md
@@ -58,3 +58,21 @@
         At least 3 missed doses   3 (60%)   5 (83.3%)
         At least 7 missed doses   2 (40%)   2 (33.3%)
 
+# count_missed_doses works with denom argument specified
+
+    Code
+      res
+    Output
+                                       A         B    
+      ————————————————————————————————————————————————
+      x                                               
+        Missed Doses                                  
+          n                            5         1    
+          At least 3 missed doses   3 (60%)   1 (100%)
+          At least 7 missed doses   2 (40%)   1 (100%)
+      y                                               
+        Missed Doses                                  
+          n                            0         4    
+          At least 3 missed doses      0      4 (100%)
+          At least 7 missed doses      0      1 (25%) 
+
diff --git a/tests/testthat/_snaps/count_occurrences_by_grade.md b/tests/testthat/_snaps/count_occurrences_by_grade.md
index 50c754c762..94cf945880 100644
--- a/tests/testthat/_snaps/count_occurrences_by_grade.md
+++ b/tests/testthat/_snaps/count_occurrences_by_grade.md
@@ -228,6 +228,39 @@
       
       
 
+# a_count_occurrences_by_grade works with healthy input.
+
+    Code
+      res
+    Output
+      RowsVerticalSection (in_rows) object print method:
+      ----------------------------
+         row_name formatted_cell indent_mod row_label
+      1         1        2 (20%)          0         1
+      2         2        2 (20%)          0         2
+      3         3        2 (20%)          0         3
+      4         4              0          0         4
+      5         5              0          0         5
+      6         1      2 (20.0%)          0         1
+      7         2      2 (20.0%)          0         2
+      8         3      2 (20.0%)          0         3
+      9         4              0          0         4
+      10        5              0          0         5
+
+# a_count_occurrences_by_grade works with custom input.
+
+    Code
+      res
+    Output
+      RowsVerticalSection (in_rows) object print method:
+      ----------------------------
+          row_name formatted_cell indent_mod  row_label
+      1   Level: 1        2 (20%)          1   Level: 1
+      2      LVL 2        2 (20%)          2      LVL 2
+      3 Count of 3        2 (20%)          0 Count of 3
+      4  Missing 4         0 (0%)          3  Missing 4
+      5          5         0 (0%)          0          5
+
 # count_occurrences_by_grade works with default arguments for intensity
 
     Code
@@ -248,9 +281,9 @@
                      A           B         D  
                    (N=3)       (N=3)     (N=0)
       ————————————————————————————————————————
-      MILD           0       2 (66.7%)    NA  
-      MODERATE   1 (33.3%)   1 (33.3%)    NA  
-      SEVERE     2 (66.7%)       0        NA  
+      MILD           0       2 (66.7%)     0  
+      MODERATE   1 (33.3%)   1 (33.3%)     0  
+      SEVERE     2 (66.7%)       0         0  
 
 # count_occurrences_by_grade label works when more than one variables are analyzed
 
@@ -322,17 +355,17 @@
     Code
       res
     Output
-                         A               B             D     
-                      (N=10)          (N=10)         (N=0)   
-      ———————————————————————————————————————————————————————
-      LOW                                                    
-        MILD       0.00 (0.00%)    1.00 (10.00%)   0.00 (NA%)
-        MODERATE   0.00 (0.00%)    0.00 (0.00%)    0.00 (NA%)
-        SEVERE     2.00 (20.00%)   0.00 (0.00%)    0.00 (NA%)
-      HIGH                                                   
-        MILD       0.00 (0.00%)    1.00 (10.00%)   0.00 (NA%)
-        MODERATE   1.00 (10.00%)   1.00 (10.00%)   0.00 (NA%)
-        SEVERE     0.00 (0.00%)    0.00 (0.00%)    0.00 (NA%)
+                         A               B              D      
+                      (N=10)          (N=10)          (N=0)    
+      —————————————————————————————————————————————————————————
+      LOW                                                      
+        MILD       0.00 (0.00%)    1.00 (10.00%)   0.00 (0.00%)
+        MODERATE   0.00 (0.00%)    0.00 (0.00%)    0.00 (0.00%)
+        SEVERE     2.00 (20.00%)   0.00 (0.00%)    0.00 (0.00%)
+      HIGH                                                     
+        MILD       0.00 (0.00%)    1.00 (10.00%)   0.00 (0.00%)
+        MODERATE   1.00 (10.00%)   1.00 (10.00%)   0.00 (0.00%)
+        SEVERE     0.00 (0.00%)    0.00 (0.00%)    0.00 (0.00%)
 
 # summarize_occurrences_by_grade works with custom arguments for grade
 
@@ -400,3 +433,55 @@
         MODERATE    7 (3.5%)     9 (5.1%)       6 (3.7%)           -1.6 (-5.7 - 2.5)      
         SEVERE     17 (8.4%)    23 (13.0%)     22 (13.6%)          -4.6 (-10.8 - 1.7)     
 
+# count_occurrences_by_grade works with denom argument specified
+
+    Code
+      res
+    Output
+                      A           B    
+      —————————————————————————————————
+      LOW          2 (100%)   1 (100%) 
+        MILD          0       1 (100%) 
+        MODERATE      0           0    
+        SEVERE     2 (100%)       0    
+      HIGH         1 (100%)   2 (100%) 
+        MILD          0       1 (50.0%)
+        MODERATE   1 (100%)   1 (50.0%)
+        SEVERE        0           0    
+
+# summarize_occurrences works as expected with risk difference column
+
+    Code
+      res
+    Output
+                   A: Drug X    B: Placebo   C: Combination   Risk Difference (%) (95% CI)
+                    (N=202)      (N=177)        (N=162)                 (N=379)           
+      ————————————————————————————————————————————————————————————————————————————————————
+      F                                                                                   
+        MILD        3 (1.5%)     4 (2.3%)       1 (0.6%)           -0.8 (-3.5 - 2.0)      
+        MODERATE    8 (4.0%)     6 (3.4%)       6 (3.7%)            0.6 (-3.2 - 4.4)      
+        SEVERE     22 (10.9%)   21 (11.9%)     20 (12.3%)          -1.0 (-7.4 - 5.4)      
+      M                                                                                   
+        MILD        3 (1.5%)        0           1 (0.6%)            1.5 (-0.2 - 3.2)      
+        MODERATE   11 (5.4%)     9 (5.1%)       8 (4.9%)            0.4 (-4.1 - 4.9)      
+        SEVERE     12 (5.9%)    17 (9.6%)      12 (7.4%)           -3.7 (-9.1 - 1.8)      
+
+---
+
+    Code
+      res
+    Output
+                     A: Drug X   B: Placebo   C: Combination   Risk Difference (%) (95% CI)
+                      (N=202)     (N=177)        (N=162)                 (N=379)           
+      —————————————————————————————————————————————————————————————————————————————————————
+      F                                                                                    
+          -Any-      20 (9.9%)   19 (10.7%)     19 (11.7%)          -0.8 (-7.0 - 5.3)      
+          MILD       2 (1.0%)     2 (1.1%)          0               -0.1 (-2.2 - 1.9)      
+          MODERATE   4 (2.0%)     3 (1.7%)       3 (1.9%)            0.3 (-2.4 - 3.0)      
+          SEVERE     14 (6.9%)   14 (7.9%)      16 (9.9%)           -1.0 (-6.3 - 4.3)      
+      M                                                                                    
+          -Any-      14 (6.9%)   21 (11.9%)     17 (10.5%)          -4.9 (-10.8 - 1.0)     
+          MILD       1 (0.5%)        0           1 (0.6%)            0.5 (-0.5 - 1.5)      
+          MODERATE   4 (2.0%)     7 (4.0%)       5 (3.1%)           -2.0 (-5.4 - 1.5)      
+          SEVERE     9 (4.5%)    14 (7.9%)      11 (6.8%)           -3.5 (-8.3 - 1.4)      
+
diff --git a/tests/testthat/_snaps/estimate_incidence_rate.md b/tests/testthat/_snaps/estimate_incidence_rate.md
deleted file mode 100644
index 7133820dea..0000000000
--- a/tests/testthat/_snaps/estimate_incidence_rate.md
+++ /dev/null
@@ -1,134 +0,0 @@
-# control_incidence_rate works with customized parameters
-
-    Code
-      res
-    Output
-      $conf_level
-      [1] 0.9
-      
-      $conf_type
-      [1] "exact"
-      
-      $input_time_unit
-      [1] "month"
-      
-      $num_pt_year
-      [1] 100
-      
-
-# h_incidence_rate_normal works as expected with healthy input
-
-    Code
-      res
-    Output
-      $rate
-      [1] 0.01
-      
-      $rate_ci
-      [1] -0.001630872  0.021630872
-      
-
-# h_incidence_rate_normal_log works as expected with healthy input
-
-    Code
-      res
-    Output
-      $rate
-      [1] 0.01
-      
-      $rate_ci
-      [1] 0.003125199 0.031997963
-      
-
-# h_incidence_rate_exact works as expected with healthy input
-
-    Code
-      res
-    Output
-      $rate
-      [1] 0.01
-      
-      $rate_ci
-      [1] 0.001776808 0.031478968
-      
-
-# h_incidence_rate_byar works as expected with healthy input
-
-    Code
-      res
-    Output
-      $rate
-      [1] 0.01
-      
-      $rate_ci
-      [1] 0.002820411 0.027609866
-      
-
-# h_incidence_rate works as expected with healthy input
-
-    Code
-      res
-    Output
-      $rate
-      [1] 1
-      
-      $rate_ci
-      [1] 0.3125199 3.1997963
-      
-
-# s_incidence_rate works as expected with healthy input
-
-    Code
-      res
-    Output
-      $person_years
-      [1] 9.058333
-      attr(,"label")
-      [1] "Total patient-years at risk"
-      
-      $n_events
-      [1] 4
-      attr(,"label")
-      [1] "Number of adverse events observed"
-      
-      $rate
-      [1] 44.15823
-      attr(,"label")
-      [1] "AE rate per 100 patient-years"
-      
-      $rate_ci
-      [1]  19.40154 100.50487
-      attr(,"label")
-      [1] "90% CI"
-      
-      $n_rate
-      [1]  4.00000 44.15823
-      attr(,"label")
-      [1] "Number of adverse events observed (AE rate per 100 patient-years)"
-      
-
-# estimate_incidence_rate works as expected with healthy input
-
-    Code
-      res
-    Output
-                                                A                 B       
-                                              (N=3)             (N=3)     
-      ————————————————————————————————————————————————————————————————————
-      Total patient-years at risk              3.8               5.2      
-      Number of adverse events observed         1                 3       
-      AE rate per 100 patient-years           26.20             57.23     
-      90% CI                              (5.06, 135.73)   (22.14, 147.94)
-
-# estimate_incidence_rate `n_rate` statistic works as expected
-
-    Code
-      res
-    Output
-                                                                             A         B   
-                                                                           (N=3)     (N=3) 
-      —————————————————————————————————————————————————————————————————————————————————————
-      Number of adverse events observed                                      1         3   
-      AE rate per 100 patient-years                                        2.18      4.77  
-      Number of adverse events observed (AE rate per 100 patient-years)   1 (2.2)   3 (4.8)
-
diff --git a/tests/testthat/test-analyze_variables.R b/tests/testthat/test-analyze_variables.R
index f64d01f045..9940e36c3e 100644
--- a/tests/testthat/test-analyze_variables.R
+++ b/tests/testthat/test-analyze_variables.R
@@ -165,7 +165,7 @@ testthat::test_that("a_summary work with healthy input.", {
   res_out <- testthat::expect_silent(result)
 
   # numeric input - a_summary
-  result <- a_summary(x = x, .N_col = 10, .N_row = 20, .var = "bla")
+  result <- a_summary(x = x, .N_col = 10, .N_row = 10, .var = "bla")
   res <- testthat::expect_silent(result)
   testthat::expect_identical(res_out, res)
   testthat::expect_snapshot(res)
diff --git a/tests/testthat/test-count_cumulative.R b/tests/testthat/test-count_cumulative.R
index b773669c69..49c20ebbdd 100644
--- a/tests/testthat/test-count_cumulative.R
+++ b/tests/testthat/test-count_cumulative.R
@@ -102,3 +102,29 @@ testthat::test_that("count_cumulative works with customized arguments", {
   res <- testthat::expect_silent(result)
   testthat::expect_snapshot(res)
 })
+
+testthat::test_that("count_cumulative works with denom argument specified", {
+  set.seed(1, kind = "Mersenne-Twister")
+  df <- data.frame(
+    a = c(sample(1:10, 10), NA),
+    type = factor(sample(c("x", "y"), 11, replace = TRUE)),
+    grp = factor(c(rep("A", 5), rep("B", 6)), levels = c("A", "B"))
+  )
+
+  result <- basic_table() %>%
+    split_cols_by("grp") %>%
+    split_rows_by("type") %>%
+    summarize_row_groups(format = "xx.") %>%
+    count_cumulative(
+      vars = "a",
+      thresholds = c(3, 7),
+      lower_tail = FALSE,
+      include_eq = FALSE,
+      na.rm = FALSE,
+      denom = "n"
+    ) %>%
+    build_table(df)
+
+  res <- testthat::expect_silent(result)
+  testthat::expect_snapshot(res)
+})
diff --git a/tests/testthat/test-count_missed_doses.R b/tests/testthat/test-count_missed_doses.R
index 3061125599..ea46ec1eb2 100644
--- a/tests/testthat/test-count_missed_doses.R
+++ b/tests/testthat/test-count_missed_doses.R
@@ -28,7 +28,8 @@ testthat::test_that("s_count_missed_doses works as expected", {
   result <- s_count_missed_doses(
     x = c(0, 1, 0, 2, 3, 4, 0, 2),
     thresholds = c(2, 5),
-    .N_col = 10
+    .N_col = 10,
+    .N_row = 10
   )
 
   res <- testthat::expect_silent(result)
@@ -54,3 +55,26 @@ testthat::test_that("count_missed_doses works as expected", {
   res <- testthat::expect_silent(result)
   testthat::expect_snapshot(res)
 })
+
+testthat::test_that("count_missed_doses works with denom argument specified", {
+  set.seed(1)
+  df <- data.frame(
+    a = c(sample(1:10, 10), NA),
+    type = factor(sample(c("x", "y"), 11, replace = TRUE)),
+    grp = factor(c(rep("A", 5), rep("B", 6)), levels = c("A", "B"))
+  )
+
+  result <- basic_table() %>%
+    split_cols_by("grp") %>%
+    split_rows_by("type") %>%
+    count_missed_doses(
+      "a",
+      thresholds = c(3, 7),
+      var_labels = "Missed Doses",
+      denom = "n"
+    ) %>%
+    build_table(df)
+
+  res <- testthat::expect_silent(result)
+  testthat::expect_snapshot(res)
+})
diff --git a/tests/testthat/test-count_occurrences.R b/tests/testthat/test-count_occurrences.R
index 35994b913e..dec4fa5cbb 100644
--- a/tests/testthat/test-count_occurrences.R
+++ b/tests/testthat/test-count_occurrences.R
@@ -4,7 +4,7 @@ testthat::test_that("s_count_occurrences functions as expected with valid input
     MHDECOD = c("MH1", "MH2", "MH1", "MH1", "MH1", "MH3")
   )
 
-  result <- s_count_occurrences(df = df, .N_col = 4L, .df_row = df)
+  result <- s_count_occurrences(df = df, .N_col = 4L, .N_row = 4L, .df_row = df)
 
   res <- testthat::expect_silent(result)
   testthat::expect_snapshot(res)
@@ -18,7 +18,7 @@ testthat::test_that("s_count_occurrences drops non appearing levels by default",
       levels = c("MH1", "MH2", "MH3", "MHX")
     )
   )
-  result <- s_count_occurrences(df = df, .N_col = 4L, .df_row = df)
+  result <- s_count_occurrences(df = df, .N_col = 4L, .N_row = 4L, .df_row = df)
   testthat::expect_false("MHX" %in% c(names(result$count), names(result$count_fraction), names(result$fraction)))
 })
 
@@ -30,7 +30,7 @@ testthat::test_that("s_count_occurrences keeps non appearing levels if requested
       levels = c("MH1", "MH2", "MH3", "MHX")
     )
   )
-  result <- s_count_occurrences(df = df, .N_col = 4L, .df_row = df, drop = FALSE)
+  result <- s_count_occurrences(df = df, .N_col = 4L, .N_row = 4L, .df_row = df, drop = FALSE)
   testthat::expect_true("MHX" %in% names(result$count))
   testthat::expect_true("MHX" %in% names(result$count_fraction))
   testthat::expect_true("MHX" %in% names(result$fraction))
@@ -48,6 +48,7 @@ testthat::test_that("s_count_occurrences fails when it receives empty .df_row an
   testthat::expect_error(s_count_occurrences(
     df = df_sub,
     .N_col = 4L,
+    .N_row = 4L,
     .df_row = df_sub,
     drop = TRUE
   ))
@@ -59,7 +60,7 @@ testthat::test_that("s_count_occurrences functions as expected when requesting d
     MHDECOD = c("MH1", "MH2", "MH1", "MH1", "MH1", "MH3")
   )
 
-  result <- s_count_occurrences(df = df, denom = "n", .N_col = 4L, .df_row = df)
+  result <- s_count_occurrences(df = df, denom = "n", .N_col = 4L, .N_row = 4L, .df_row = df)
 
   res <- testthat::expect_silent(result)
   testthat::expect_snapshot(res)
@@ -74,7 +75,7 @@ testthat::test_that("a_count_occurrences works with healthy input.", {
     x = factor(c("a", "a", "b", "c", "a"))
   )
   result <- a_count_occurrences(
-    df = df, .N_col = 10, .stats = get_stats("count_occurrences"), .var = "x", id = "id", .df_row = df
+    df = df, .N_col = 10, .N_row = 10, .stats = get_stats("count_occurrences"), .var = "x", id = "id", .df_row = df
   )
   res_out <- testthat::expect_silent(result)
 
@@ -84,7 +85,7 @@ testthat::test_that("a_count_occurrences works with healthy input.", {
     x = c("a", "a", "b", "c", "a")
   )
   result <- a_count_occurrences(
-    df = df, .N_col = 10, .stats = get_stats("count_occurrences"), .var = "x", id = "id", .df_row = df
+    df = df, .N_col = 10, .N_row = 10, .stats = get_stats("count_occurrences"), .var = "x", id = "id", .df_row = df
   )
   res_out <- testthat::expect_silent(result)
 })
@@ -98,7 +99,7 @@ testthat::test_that("a_count_occurrences works with custom input.", {
   )
 
   result <- a_count_occurrences(
-    df = df, .df_row = df, .var = "x", id = "id", .N_col = 5,
+    df = df, .df_row = df, .var = "x", id = "id", .N_col = 5, .N_row = 5,
     .stats = c("count", "count_fraction"), drop = FALSE,
     .formats = c(count_fraction = "xx (xx%)"),
     .labels = c(a = "Level: a", b = "LVL B", count.c = "Count of c", d = "Missing D"),
diff --git a/tests/testthat/test-count_occurrences_by_grade.R b/tests/testthat/test-count_occurrences_by_grade.R
index 105c906585..7f5b09bfdc 100644
--- a/tests/testthat/test-count_occurrences_by_grade.R
+++ b/tests/testthat/test-count_occurrences_by_grade.R
@@ -135,6 +135,34 @@ testthat::test_that("s_count_occurrences_by_grade works with valid input for int
   testthat::expect_snapshot(res)
 })
 
+testthat::test_that("a_count_occurrences_by_grade works with healthy input.", {
+  options("width" = 100)
+
+  result <- a_count_occurrences_by_grade(
+    df = raw_data, .N_col = 10, .N_row = 10, .df_row = raw_data,
+    .stats = get_stats("count_occurrences_by_grade"),
+    .var = "AETOXGR", id = "USUBJID"
+  )
+  res <- testthat::expect_silent(result)
+  testthat::expect_snapshot(res)
+})
+
+testthat::test_that("a_count_occurrences_by_grade works with custom input.", {
+  options("width" = 100)
+
+  result <- a_count_occurrences_by_grade(
+    df = raw_data, .N_col = 10, .N_row = 10, .df_row = raw_data,
+    .stats = "count_fraction",
+    .formats = c(count_fraction = "xx (xx%)"),
+    .labels = list("1" = "Level: 1", "2" = "LVL 2", "count_fraction.3" = "Count of 3", "4" = "Missing 4"),
+    .indent_mods = list("1" = 1L, "2" = 2L, "count_fraction.4" = 3L),
+    .var = "AETOXGR", id = "USUBJID"
+  )
+
+  res <- testthat::expect_silent(result)
+  testthat::expect_snapshot(res)
+})
+
 testthat::test_that("count_occurrences_by_grade works with default arguments for intensity", {
   df <- raw_data
   df_adsl <- unique(df[c("ARM", "ARM_EMPTY", "USUBJID")])
@@ -414,3 +442,53 @@ testthat::test_that("count_occurrences_by_grade works as expected with risk diff
   res <- testthat::expect_silent(result)
   testthat::expect_snapshot(res)
 })
+
+testthat::test_that("count_occurrences_by_grade works with denom argument specified", {
+  df <- raw_data
+  df_adsl <- unique(df[c("ARM", "ARM_EMPTY", "USUBJID")])
+
+  result <- basic_table() %>%
+    split_cols_by("ARM") %>%
+    split_rows_by("BMRKR") %>%
+    summarize_occurrences_by_grade(var = "BMRKR", denom = "n") %>%
+    count_occurrences_by_grade(var = "AESEV", denom = "n") %>%
+    build_table(df, alt_counts_df = df_adsl)
+
+  res <- testthat::expect_silent(result[-c(2, 6)])
+  testthat::expect_snapshot(res)
+})
+
+testthat::test_that("summarize_occurrences works as expected with risk difference column", {
+  tern_ex_adae$AESEV <- factor(tern_ex_adae$AESEV)
+
+  # Default parameters
+  result <- basic_table(show_colcounts = TRUE) %>%
+    split_cols_by("ARM", split_fun = add_riskdiff("A: Drug X", "B: Placebo")) %>%
+    split_rows_by("SEX", child_labels = "visible") %>%
+    summarize_occurrences_by_grade(
+      var = "AESEV",
+      riskdiff = TRUE
+    ) %>%
+    build_table(tern_ex_adae)
+
+  res <- testthat::expect_silent(result)
+  testthat::expect_snapshot(res)
+
+  # Grade groups, custom id var
+  grade_groups <- list("-Any-" = levels(tern_ex_adae$AESEV))
+
+  result <- basic_table(show_colcounts = TRUE) %>%
+    split_cols_by("ARM", split_fun = add_riskdiff("A: Drug X", "B: Placebo")) %>%
+    split_rows_by("SEX", child_labels = "visible") %>%
+    summarize_occurrences_by_grade(
+      var = "AESEV",
+      riskdiff = TRUE,
+      .indent_mods = 1L,
+      grade_groups = grade_groups,
+      id = "SITEID"
+    ) %>%
+    build_table(tern_ex_adae)
+
+  res <- testthat::expect_silent(result)
+  testthat::expect_snapshot(res)
+})
diff --git a/tests/testthat/test-g_km.R b/tests/testthat/test-g_km.R
index ebce5ad5d0..e137387214 100644
--- a/tests/testthat/test-g_km.R
+++ b/tests/testthat/test-g_km.R
@@ -1,3 +1,5 @@
+library(nestcolor)
+
 df <- tern_ex_adtte %>%
   filter(PARAMCD == "OS") %>%
   mutate(is_event = CNSR == 0)