diff --git a/DESCRIPTION b/DESCRIPTION
index abeb65ab40..d4bcf6e5f8 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -122,6 +122,7 @@ Collate:
     'h_step.R'
     'h_survival_biomarkers_subgroups.R'
     'h_survival_duration_subgroups.R'
+    'imputation_rule.R'
     'incidence_rate.R'
     'individual_patient_plot.R'
     'kaplan_meier_plot.R'
diff --git a/NAMESPACE b/NAMESPACE
index e1dadcff6a..026707e077 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -120,6 +120,7 @@ export(format_extreme_values_ci)
 export(format_fraction)
 export(format_fraction_fixed_dp)
 export(format_fraction_threshold)
+export(format_sigfig)
 export(format_xx)
 export(g_forest)
 export(g_ipp)
@@ -211,6 +212,7 @@ export(has_counts_difference)
 export(has_fraction_in_any_col)
 export(has_fraction_in_cols)
 export(has_fractions_difference)
+export(imputation_rule)
 export(keep_content_rows)
 export(keep_rows)
 export(logistic_regression_cols)
diff --git a/NEWS.md b/NEWS.md
index bd1d7c197c..6d123d6996 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,6 +1,12 @@
 # tern 0.9.0.9001
+### New Features
+* Added `imputation_rule` function to apply imputation rule to data.
+* Added new format function `format_sigfig` to allow for numeric value formatting by a specified number of significant figures.
+
 ### Enhancements
 * Refactored `tabulate_rsp_subgroups` to pass sanitation checks by preventing creation of degenerate subtables.
+* Updated `analyze_vars_in_cols` to use caching, allow implementation of imputation rule via the `imp_rule` argument, and allow user to specify cell alignment via the `.aligns` argument.
+* Updated `add_rowcounts` to allow addition of row counts from `alt_counts_df` using the `alt_counts` argument.
 
 # tern 0.9.0
 ### New Features
diff --git a/R/analyze_variables.R b/R/analyze_variables.R
index d198ce999c..7033f3084e 100644
--- a/R/analyze_variables.R
+++ b/R/analyze_variables.R
@@ -271,7 +271,7 @@ s_summary.factor <- function(x,
     }
   )
 
-  y$n_blq <- sum(grepl("BLQ|LTR|<[1-9]", x))
+  y$n_blq <- sum(grepl("BLQ|LTR|<[1-9]|<PCLLOQ", x))
 
   y
 }
diff --git a/R/analyze_vars_in_cols.R b/R/analyze_vars_in_cols.R
index 91eea31965..b45a3c8434 100644
--- a/R/analyze_vars_in_cols.R
+++ b/R/analyze_vars_in_cols.R
@@ -8,6 +8,17 @@
 #'
 #' @inheritParams argument_convention
 #' @inheritParams rtables::analyze_colvars
+#' @param imp_rule (`character`)\cr imputation rule setting. Defaults to `NULL` for no imputation rule. Can
+#'   also be `"1/3"` to implement 1/3 imputation rule or `"1/2"` to implement 1/2 imputation rule. In order
+#'   to use an imputation rule, the `avalcat_var` argument must be specified. See [imputation_rule()]
+#'   for more details on imputation.
+#' @param avalcat_var (`character`)\cr if `imp_rule` is not `NULL`, name of variable that indicates whether a
+#'   row in the data corresponds to an analysis value in category `"BLQ"`, `"LTR"`, `"<PCLLOQ"`, or none of
+#'   the above (defaults to `"AVALCAT1"`). Variable must be present in the data and should match the variable
+#'   used to calculate the `n_blq` statistic (if included in `.stats`).
+#' @param cache (`flag`)\cr whether to store computed values in a temporary caching environment. This will
+#'   speed up calculations in large tables, but should be set to `FALSE` if the same `rtable` layout is
+#'   used for multiple tables with different data. Defaults to `FALSE`.
 #' @param row_labels (`character`)\cr as this function works in columns space, usual `.labels`
 #'   character vector applies on the column space. You can change the row labels by defining this
 #'   parameter to a named character vector with names corresponding to the split values. It defaults
@@ -143,10 +154,14 @@ analyze_vars_in_cols <- function(lyt,
                                  row_labels = NULL,
                                  do_summarize_row_groups = FALSE,
                                  split_col_vars = TRUE,
+                                 imp_rule = NULL,
+                                 avalcat_var = "AVALCAT1",
+                                 cache = FALSE,
                                  .indent_mods = NULL,
                                  nested = TRUE,
                                  na_level = NULL,
-                                 .formats = NULL) {
+                                 .formats = NULL,
+                                 .aligns = NULL) {
   checkmate::assert_string(na_level, null.ok = TRUE)
   checkmate::assert_character(row_labels, null.ok = TRUE)
   checkmate::assert_int(.indent_mods, null.ok = TRUE)
@@ -201,6 +216,8 @@ analyze_vars_in_cols <- function(lyt,
     )
   }
 
+  env <- new.env() # create caching environment
+
   if (do_summarize_row_groups) {
     if (length(unique(vars)) > 1) {
       stop("When using do_summarize_row_groups only one label level var should be inserted.")
@@ -208,10 +225,31 @@ analyze_vars_in_cols <- function(lyt,
 
     # Function list for do_summarize_row_groups. Slightly different handling of labels
     cfun_list <- Map(
-      function(stat) {
-        function(u, .spl_context, labelstr, ...) {
+      function(stat, use_cache, cache_env) {
+        function(u, .spl_context, labelstr, .df_row, ...) {
           # Statistic
-          res <- s_summary(u, ...)[[stat]]
+          var_row_val <- paste(
+            gsub("\\._\\[\\[[0-9]+\\]\\]_\\.", "", paste(tail(.spl_context$cur_col_split_val, 1)[[1]], collapse = "_")),
+            paste(.spl_context$value, collapse = "_"),
+            sep = "_"
+          )
+          if (use_cache) {
+            if (is.null(cache_env[[var_row_val]])) cache_env[[var_row_val]] <- s_summary(u, ...)
+            x_stats <- cache_env[[var_row_val]]
+          } else {
+            x_stats <- s_summary(u, ...)
+          }
+
+          if (is.null(imp_rule) || !stat %in% c("mean", "sd", "cv", "geom_mean", "geom_cv", "median", "min", "max")) {
+            res <- x_stats[[stat]]
+          } else {
+            res_imp <- imputation_rule(
+              .df_row, x_stats, stat,
+              imp_rule = imp_rule, post = as.numeric(tail(.spl_context$value, 1)) > 0, avalcat_var = avalcat_var
+            )
+            res <- res_imp[["val"]]
+            na_level <- res_imp[["na_level"]]
+          }
 
           # Label check and replacement
           if (length(row_labels) > 1) {
@@ -234,11 +272,14 @@ analyze_vars_in_cols <- function(lyt,
             label = lbl,
             format = formats_v[names(formats_v) == stat][[1]],
             format_na_str = na_level,
-            indent_mod = ifelse(is.null(.indent_mods), 0L, .indent_mods)
+            indent_mod = ifelse(is.null(.indent_mods), 0L, .indent_mods),
+            align = .aligns
           )
         }
       },
-      stat = .stats
+      stat = .stats,
+      use_cache = cache,
+      cache_env = replicate(length(.stats), env)
     )
 
     # Main call to rtables
@@ -251,10 +292,31 @@ analyze_vars_in_cols <- function(lyt,
   } else {
     # Function list for analyze_colvars
     afun_list <- Map(
-      function(stat) {
-        function(u, .spl_context, ...) {
+      function(stat, use_cache, cache_env) {
+        function(u, .spl_context, .df_row, ...) {
           # Main statistics
-          res <- s_summary(u, ...)[[stat]]
+          var_row_val <- paste(
+            gsub("\\._\\[\\[[0-9]+\\]\\]_\\.", "", paste(tail(.spl_context$cur_col_split_val, 1)[[1]], collapse = "_")),
+            paste(.spl_context$value, collapse = "_"),
+            sep = "_"
+          )
+          if (use_cache) {
+            if (is.null(cache_env[[var_row_val]])) cache_env[[var_row_val]] <- s_summary(u, ...)
+            x_stats <- cache_env[[var_row_val]]
+          } else {
+            x_stats <- s_summary(u, ...)
+          }
+
+          if (is.null(imp_rule) || !stat %in% c("mean", "sd", "cv", "geom_mean", "geom_cv", "median", "min", "max")) {
+            res <- x_stats[[stat]]
+          } else {
+            res_imp <- imputation_rule(
+              .df_row, x_stats, stat,
+              imp_rule = imp_rule, post = as.numeric(tail(.spl_context$value, 1)) > 0, avalcat_var = avalcat_var
+            )
+            res <- res_imp[["val"]]
+            na_level <- res_imp[["na_level"]]
+          }
 
           if (is.list(res)) {
             if (length(res) > 1) {
@@ -292,11 +354,14 @@ analyze_vars_in_cols <- function(lyt,
             label = lbl,
             format = formats_v[names(formats_v) == stat][[1]],
             format_na_str = na_level,
-            indent_mod = ifelse(is.null(.indent_mods), 0L, .indent_mods)
+            indent_mod = ifelse(is.null(.indent_mods), 0L, .indent_mods),
+            align = .aligns
           )
         }
       },
-      stat = .stats
+      stat = .stats,
+      use_cache = cache,
+      cache_env = replicate(length(.stats), env)
     )
 
     # Main call to rtables
diff --git a/R/argument_convention.R b/R/argument_convention.R
index c8f0d839d2..1f36def62c 100644
--- a/R/argument_convention.R
+++ b/R/argument_convention.R
@@ -4,6 +4,8 @@
 #' that are used repeatedly to express an analysis.
 #'
 #' @param ... additional arguments for the lower level functions.
+#' @param .aligns (`character`)\cr alignment for table contents (not including labels). When `NULL`, `"center"`
+#'   is applied. See [formatters::list_valid_aligns()] for a list of all currently supported alignments.
 #' @param .all_col_counts (`vector` of `integer`)\cr each value represents a global count for a column. Values are
 #'   taken from `alt_counts_df` if specified (see [rtables::build_table()]).
 #' @param .df_row (`data.frame`)\cr data frame across all of the columns for the given row split.
diff --git a/R/formatting_functions.R b/R/formatting_functions.R
index d98fc16e06..ec39143f0b 100644
--- a/R/formatting_functions.R
+++ b/R/formatting_functions.R
@@ -209,6 +209,33 @@ format_xx <- function(str) {
   return(rtable_format)
 }
 
+#' Formatting Numeric Values By Significant Figures
+#'
+#' Format numeric values to print with a specified number of significant figures.
+#'
+#' @param sigfig (`integer`)\cr number of significant figures to display.
+#'
+#' @return An `rtables` formatting function.
+#'
+#' @examples
+#' fmt_3sf <- format_sigfig(3)
+#' fmt_3sf(1.658)
+#' fmt_3sf(1e1)
+#'
+#' fmt_5sf <- format_sigfig(5)
+#' fmt_5sf(0.57)
+#' fmt_5sf(0.000025645)
+#'
+#' @family formatting functions
+#' @export
+format_sigfig <- function(sigfig) {
+  checkmate::assert_integerish(sigfig)
+  function(x, ...) {
+    if (!is.numeric(x)) stop("`format_sigfig` cannot be used for non-numeric values. Please choose another format.")
+    formatC(signif(x, digits = sigfig), digits = sigfig, format = "fg", flag = "#")
+  }
+}
+
 #' Formatting Fraction with Lower Threshold
 #'
 #' @description `r lifecycle::badge("stable")`
diff --git a/R/imputation_rule.R b/R/imputation_rule.R
new file mode 100644
index 0000000000..2a87b4ae85
--- /dev/null
+++ b/R/imputation_rule.R
@@ -0,0 +1,60 @@
+#' Apply 1/3 or 1/2 Imputation Rule to Data
+#'
+#' @description `r lifecycle::badge("stable")`
+#'
+#' @inheritParams argument_convention
+#' @param x_stats (`named list`)\cr a named list of statistics, typically the results of [s_summary()].
+#' @param stat (`character`)\cr statistic to return the value/NA level of according to the imputation
+#'   rule applied.
+#' @param imp_rule (`character`)\cr imputation rule setting. Set to `"1/3"` to implement 1/3 imputation
+#'   rule or `"1/2"` to implement 1/2 imputation rule.
+#' @param post (`flag`)\cr whether the data corresponds to a post-dose time-point (defaults to `FALSE`).
+#'   This parameter is only used when `imp_rule` is set to `"1/3"`.
+#' @param avalcat_var (`character`)\cr name of variable that indicates whether a row in `df` corresponds
+#'   to an analysis value in category `"BLQ"`, `"LTR"`, `"<PCLLOQ"`, or none of the above
+#'   (defaults to `"AVALCAT1"`). Variable `avalcat_var` must be present in `df`.
+#'
+#' @return A `list` containing statistic value (`val`) and NA level (`na_level`) that should be displayed
+#'   according to the specified imputation rule.
+#'
+#' @seealso [analyze_vars_in_cols()] where this function can be implemented by setting the `imp_rule`
+#'   argument.
+#'
+#' @examples
+#' set.seed(1)
+#' df <- data.frame(
+#'   AVAL = runif(50, 0, 1),
+#'   AVALCAT1 = sample(c(1, "BLQ"), 50, replace = TRUE)
+#' )
+#' x_stats <- s_summary(df$AVAL)
+#' imputation_rule(df, x_stats, "max", "1/3")
+#' imputation_rule(df, x_stats, "geom_mean", "1/3")
+#' imputation_rule(df, x_stats, "mean", "1/2")
+#'
+#' @export
+imputation_rule <- function(df, x_stats, stat, imp_rule, post = FALSE, avalcat_var = "AVALCAT1") {
+  checkmate::assert_choice(avalcat_var, names(df))
+  checkmate::assert_choice(imp_rule, c("1/3", "1/2"))
+  n_blq <- sum(grepl("BLQ|LTR|<[1-9]|<PCLLOQ", df[[avalcat_var]]))
+  ltr_blq_ratio <- n_blq / max(1, nrow(df))
+
+  # defaults
+  val <- x_stats[[stat]]
+  na_level <- "NE"
+
+  if (imp_rule == "1/3") {
+    if (!post && stat == "geom_mean") val <- NA # 1/3_pre_LT, 1/3_pre_GT
+    if (ltr_blq_ratio > 1 / 3) {
+      if (stat != "geom_mean") na_level <- "ND" # 1/3_pre_GT, 1/3_post_GT
+      if (!post && !stat %in% c("median", "max")) val <- NA # 1/3_pre_GT
+      if (post && !stat %in% c("median", "max", "geom_mean")) val <- NA # 1/3_post_GT
+    }
+  } else if (imp_rule == "1/2") {
+    if (ltr_blq_ratio > 1 / 2 && !stat == "max") {
+      val <- NA # 1/2_GT
+      na_level <- "ND" # 1/2_GT
+    }
+  }
+
+  list(val = val, na_level = na_level)
+}
diff --git a/R/utils_rtables.R b/R/utils_rtables.R
index e600dc7f29..5cbcebd6d6 100644
--- a/R/utils_rtables.R
+++ b/R/utils_rtables.R
@@ -89,21 +89,54 @@ cfun_by_flag <- function(analysis_var,
 
 #' Content Row Function to Add Row Total to Labels
 #'
-#' This takes the label of the latest row split level and adds the row total in parentheses.
+#' This takes the label of the latest row split level and adds the row total from `df` in parentheses.
+#' This function differs from [c_label_n_alt()] by taking row counts from `df` rather than
+#' `alt_counts_df`, and is used by [add_rowcounts()] when `alt_counts` is set to `FALSE`.
 #'
 #' @inheritParams argument_convention
 #'
-#' @return A `list` containing "row_count" with the row count value and the correct label.
+#' @return A list with formatted [rtables::CellValue()] with the row count value and the correct label.
 #'
 #' @note It is important here to not use `df` but rather `.N_row` in the implementation, because
 #'   the former is already split by columns and will refer to the first column of the data only.
 #'
+#' @seealso [c_label_n_alt()] which performs the same function but retrieves row counts from
+#'   `alt_counts_df` instead of `df`.
+#'
 #' @keywords internal
 c_label_n <- function(df,
                       labelstr,
                       .N_row) { # nolint
   label <- paste0(labelstr, " (N=", .N_row, ")")
-  list(row_count = formatters::with_label(c(.N_row, .N_row), label))
+  in_rows(
+    .list = list(row_count = formatters::with_label(c(.N_row, .N_row), label)),
+    .formats = c(row_count = function(x, ...) "")
+  )
+}
+
+#' Content Row Function to Add `alt_counts_df` Row Total to Labels
+#'
+#' This takes the label of the latest row split level and adds the row total from `alt_counts_df`
+#' in parentheses. This function differs from [c_label_n()] by taking row counts from `alt_counts_df`
+#' rather than `df`, and is used by [add_rowcounts()] when `alt_counts` is set to `TRUE`.
+#'
+#' @inheritParams argument_convention
+#'
+#' @return A list with formatted [rtables::CellValue()] with the row count value and the correct label.
+#'
+#' @seealso [c_label_n()] which performs the same function but retrieves row counts from `df` instead
+#'   of `alt_counts_df`.
+#'
+#' @keywords internal
+c_label_n_alt <- function(df,
+                          labelstr,
+                          .alt_df_row) {
+  N_row_alt <- nrow(.alt_df_row) # nolint
+  label <- paste0(labelstr, " (N=", N_row_alt, ")")
+  in_rows(
+    .list = list(row_count = formatters::with_label(c(N_row_alt, N_row_alt), label)),
+    .formats = c(row_count = function(x, ...) "")
+  )
 }
 
 #' Layout Creating Function to Add Row Total Counts
@@ -114,6 +147,8 @@ c_label_n <- function(df,
 #'  is a wrapper for [rtables::summarize_row_groups()].
 #'
 #' @inheritParams argument_convention
+#' @param alt_counts (`flag`)\cr whether row counts should be taken from `alt_counts_df` (`TRUE`)
+#'   or from `df` (`FALSE`). Defaults to `FALSE`.
 #'
 #' @return A modified layout where the latest row split labels now have the row-wise
 #'   total counts (i.e. without column-based subsetting) attached in parentheses.
@@ -131,15 +166,10 @@ c_label_n <- function(df,
 #'   build_table(DM)
 #'
 #' @export
-add_rowcounts <- function(lyt) {
-  c_lbl_n_fun <- make_afun(
-    c_label_n,
-    .stats = c("row_count"),
-    .formats = c(row_count = function(x, ...) "")
-  )
+add_rowcounts <- function(lyt, alt_counts = FALSE) {
   summarize_row_groups(
     lyt,
-    cfun = c_lbl_n_fun
+    cfun = if (alt_counts) c_label_n_alt else c_label_n
   )
 }
 
diff --git a/_pkgdown.yml b/_pkgdown.yml
index 2baa80d8ce..e1022acbee 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -68,6 +68,7 @@ reference:
     desc: These functions are useful in defining an analysis.
     contents:
       - starts_with("h_")
+      - imputation_rule
       - starts_with("or_")
       - starts_with("prop_")
       - summary_stats
diff --git a/man/add_rowcounts.Rd b/man/add_rowcounts.Rd
index 6d144b9375..cd69aa94d2 100644
--- a/man/add_rowcounts.Rd
+++ b/man/add_rowcounts.Rd
@@ -4,10 +4,13 @@
 \alias{add_rowcounts}
 \title{Layout Creating Function to Add Row Total Counts}
 \usage{
-add_rowcounts(lyt)
+add_rowcounts(lyt, alt_counts = FALSE)
 }
 \arguments{
 \item{lyt}{(\code{layout})\cr input layout where analyses will be added to.}
+
+\item{alt_counts}{(\code{flag})\cr whether row counts should be taken from \code{alt_counts_df} (\code{TRUE})
+or from \code{df} (\code{FALSE}). Defaults to \code{FALSE}.}
 }
 \value{
 A modified layout where the latest row split labels now have the row-wise
diff --git a/man/analyze_vars_in_cols.Rd b/man/analyze_vars_in_cols.Rd
index 5a6d7eaf3f..7593f1c00d 100644
--- a/man/analyze_vars_in_cols.Rd
+++ b/man/analyze_vars_in_cols.Rd
@@ -14,10 +14,14 @@ analyze_vars_in_cols(
   row_labels = NULL,
   do_summarize_row_groups = FALSE,
   split_col_vars = TRUE,
+  imp_rule = NULL,
+  avalcat_var = "AVALCAT1",
+  cache = FALSE,
   .indent_mods = NULL,
   nested = TRUE,
   na_level = NULL,
-  .formats = NULL
+  .formats = NULL,
+  .aligns = NULL
 )
 }
 \arguments{
@@ -44,6 +48,20 @@ to define row labels. This behavior is not supported as we never need to overloa
 This option allows you to add multiple instances of this functions, also in a nested fashion,
 without adding more splits. This split must happen only one time on a single layout.}
 
+\item{imp_rule}{(\code{character})\cr imputation rule setting. Defaults to \code{NULL} for no imputation rule. Can
+also be \code{"1/3"} to implement 1/3 imputation rule or \code{"1/2"} to implement 1/2 imputation rule. In order
+to use an imputation rule, the \code{avalcat_var} argument must be specified. See \code{\link[=imputation_rule]{imputation_rule()}}
+for more details on imputation.}
+
+\item{avalcat_var}{(\code{character})\cr if \code{imp_rule} is not \code{NULL}, name of variable that indicates whether a
+row in the data corresponds to an analysis value in category \code{"BLQ"}, \code{"LTR"}, \code{"<PCLLOQ"}, or none of
+the above (defaults to \code{"AVALCAT1"}). Variable must be present in the data and should match the variable
+used to calculate the \code{n_blq} statistic (if included in \code{.stats}).}
+
+\item{cache}{(\code{flag})\cr whether to store computed values in a temporary caching environment. This will
+speed up calculations in large tables, but should be set to \code{FALSE} if the same \code{rtable} layout is
+used for multiple tables with different data. Defaults to \code{FALSE}.}
+
 \item{.indent_mods}{(named \code{integer})\cr indent modifiers for the labels. Defaults to 0, which corresponds to the
 unmodified default behavior. Can be negative.}
 
@@ -54,6 +72,9 @@ underneath analyses, which is not allowed.}
 \item{na_level}{(\code{string})\cr string used to replace all \code{NA} or empty values in the output.}
 
 \item{.formats}{(named \code{character} or \code{list})\cr formats for the statistics.}
+
+\item{.aligns}{(\code{character})\cr alignment for table contents (not including labels). When \code{NULL}, \code{"center"}
+is applied. See \code{\link[formatters:list_formats]{formatters::list_valid_aligns()}} for a list of all currently supported alignments.}
 }
 \value{
 A layout object suitable for passing to further layouting functions, or to \code{\link[rtables:build_table]{rtables::build_table()}}.
diff --git a/man/argument_convention.Rd b/man/argument_convention.Rd
index c4ec17e855..9b1584d30e 100644
--- a/man/argument_convention.Rd
+++ b/man/argument_convention.Rd
@@ -6,6 +6,9 @@
 \arguments{
 \item{...}{additional arguments for the lower level functions.}
 
+\item{.aligns}{(\code{character})\cr alignment for table contents (not including labels). When \code{NULL}, \code{"center"}
+is applied. See \code{\link[formatters:list_formats]{formatters::list_valid_aligns()}} for a list of all currently supported alignments.}
+
 \item{.all_col_counts}{(\code{vector} of \code{integer})\cr each value represents a global count for a column. Values are
 taken from \code{alt_counts_df} if specified (see \code{\link[rtables:build_table]{rtables::build_table()}}).}
 
diff --git a/man/c_label_n.Rd b/man/c_label_n.Rd
index 9470832cf2..6c4c73f77e 100644
--- a/man/c_label_n.Rd
+++ b/man/c_label_n.Rd
@@ -17,13 +17,19 @@ for more information.}
 (i.e. with no column-based subsetting) that is typically passed by \code{rtables}.}
 }
 \value{
-A \code{list} containing "row_count" with the row count value and the correct label.
+A list with formatted \code{\link[rtables:CellValue]{rtables::CellValue()}} with the row count value and the correct label.
 }
 \description{
-This takes the label of the latest row split level and adds the row total in parentheses.
+This takes the label of the latest row split level and adds the row total from \code{df} in parentheses.
+This function differs from \code{\link[=c_label_n_alt]{c_label_n_alt()}} by taking row counts from \code{df} rather than
+\code{alt_counts_df}, and is used by \code{\link[=add_rowcounts]{add_rowcounts()}} when \code{alt_counts} is set to \code{FALSE}.
 }
 \note{
 It is important here to not use \code{df} but rather \code{.N_row} in the implementation, because
 the former is already split by columns and will refer to the first column of the data only.
 }
+\seealso{
+\code{\link[=c_label_n_alt]{c_label_n_alt()}} which performs the same function but retrieves row counts from
+\code{alt_counts_df} instead of \code{df}.
+}
 \keyword{internal}
diff --git a/man/c_label_n_alt.Rd b/man/c_label_n_alt.Rd
new file mode 100644
index 0000000000..75010c9d2d
--- /dev/null
+++ b/man/c_label_n_alt.Rd
@@ -0,0 +1,28 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/utils_rtables.R
+\name{c_label_n_alt}
+\alias{c_label_n_alt}
+\title{Content Row Function to Add \code{alt_counts_df} Row Total to Labels}
+\usage{
+c_label_n_alt(df, labelstr, .alt_df_row)
+}
+\arguments{
+\item{df}{(\code{data.frame})\cr data set containing all analysis variables.}
+
+\item{labelstr}{(\code{character})\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.}
+}
+\value{
+A list with formatted \code{\link[rtables:CellValue]{rtables::CellValue()}} with the row count value and the correct label.
+}
+\description{
+This takes the label of the latest row split level and adds the row total from \code{alt_counts_df}
+in parentheses. This function differs from \code{\link[=c_label_n]{c_label_n()}} by taking row counts from \code{alt_counts_df}
+rather than \code{df}, and is used by \code{\link[=add_rowcounts]{add_rowcounts()}} when \code{alt_counts} is set to \code{TRUE}.
+}
+\seealso{
+\code{\link[=c_label_n]{c_label_n()}} which performs the same function but retrieves row counts from \code{df} instead
+of \code{alt_counts_df}.
+}
+\keyword{internal}
diff --git a/man/extreme_format.Rd b/man/extreme_format.Rd
index db8b6c1c3f..6fe7b73830 100644
--- a/man/extreme_format.Rd
+++ b/man/extreme_format.Rd
@@ -62,6 +62,7 @@ Other formatting functions:
 \code{\link{format_fraction_fixed_dp}()},
 \code{\link{format_fraction_threshold}()},
 \code{\link{format_fraction}()},
+\code{\link{format_sigfig}()},
 \code{\link{format_xx}()},
 \code{\link{formatting_functions}}
 }
diff --git a/man/format_count_fraction.Rd b/man/format_count_fraction.Rd
index d4f67af8e3..c64338236a 100644
--- a/man/format_count_fraction.Rd
+++ b/man/format_count_fraction.Rd
@@ -33,6 +33,7 @@ Other formatting functions:
 \code{\link{format_fraction_fixed_dp}()},
 \code{\link{format_fraction_threshold}()},
 \code{\link{format_fraction}()},
+\code{\link{format_sigfig}()},
 \code{\link{format_xx}()},
 \code{\link{formatting_functions}}
 }
diff --git a/man/format_count_fraction_fixed_dp.Rd b/man/format_count_fraction_fixed_dp.Rd
index b625a649d2..4f6e877f0b 100644
--- a/man/format_count_fraction_fixed_dp.Rd
+++ b/man/format_count_fraction_fixed_dp.Rd
@@ -34,6 +34,7 @@ Other formatting functions:
 \code{\link{format_fraction_fixed_dp}()},
 \code{\link{format_fraction_threshold}()},
 \code{\link{format_fraction}()},
+\code{\link{format_sigfig}()},
 \code{\link{format_xx}()},
 \code{\link{formatting_functions}}
 }
diff --git a/man/format_extreme_values.Rd b/man/format_extreme_values.Rd
index 1efddac5b3..55d59077e5 100644
--- a/man/format_extreme_values.Rd
+++ b/man/format_extreme_values.Rd
@@ -34,6 +34,7 @@ Other formatting functions:
 \code{\link{format_fraction_fixed_dp}()},
 \code{\link{format_fraction_threshold}()},
 \code{\link{format_fraction}()},
+\code{\link{format_sigfig}()},
 \code{\link{format_xx}()},
 \code{\link{formatting_functions}}
 }
diff --git a/man/format_extreme_values_ci.Rd b/man/format_extreme_values_ci.Rd
index b12660ccc2..5aea87b518 100644
--- a/man/format_extreme_values_ci.Rd
+++ b/man/format_extreme_values_ci.Rd
@@ -34,6 +34,7 @@ Other formatting functions:
 \code{\link{format_fraction_fixed_dp}()},
 \code{\link{format_fraction_threshold}()},
 \code{\link{format_fraction}()},
+\code{\link{format_sigfig}()},
 \code{\link{format_xx}()},
 \code{\link{formatting_functions}}
 }
diff --git a/man/format_fraction.Rd b/man/format_fraction.Rd
index 2048fbf2b2..355d014a6e 100644
--- a/man/format_fraction.Rd
+++ b/man/format_fraction.Rd
@@ -33,6 +33,7 @@ Other formatting functions:
 \code{\link{format_extreme_values}()},
 \code{\link{format_fraction_fixed_dp}()},
 \code{\link{format_fraction_threshold}()},
+\code{\link{format_sigfig}()},
 \code{\link{format_xx}()},
 \code{\link{formatting_functions}}
 }
diff --git a/man/format_fraction_fixed_dp.Rd b/man/format_fraction_fixed_dp.Rd
index 69a8e30e8b..d49d3f6423 100644
--- a/man/format_fraction_fixed_dp.Rd
+++ b/man/format_fraction_fixed_dp.Rd
@@ -35,6 +35,7 @@ Other formatting functions:
 \code{\link{format_extreme_values}()},
 \code{\link{format_fraction_threshold}()},
 \code{\link{format_fraction}()},
+\code{\link{format_sigfig}()},
 \code{\link{format_xx}()},
 \code{\link{formatting_functions}}
 }
diff --git a/man/format_fraction_threshold.Rd b/man/format_fraction_threshold.Rd
index deabe3702d..eb8b27982c 100644
--- a/man/format_fraction_threshold.Rd
+++ b/man/format_fraction_threshold.Rd
@@ -37,6 +37,7 @@ Other formatting functions:
 \code{\link{format_extreme_values}()},
 \code{\link{format_fraction_fixed_dp}()},
 \code{\link{format_fraction}()},
+\code{\link{format_sigfig}()},
 \code{\link{format_xx}()},
 \code{\link{formatting_functions}}
 }
diff --git a/man/format_sigfig.Rd b/man/format_sigfig.Rd
new file mode 100644
index 0000000000..40227283c1
--- /dev/null
+++ b/man/format_sigfig.Rd
@@ -0,0 +1,41 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/formatting_functions.R
+\name{format_sigfig}
+\alias{format_sigfig}
+\title{Formatting Numeric Values By Significant Figures}
+\usage{
+format_sigfig(sigfig)
+}
+\arguments{
+\item{sigfig}{(\code{integer})\cr number of significant figures to display.}
+}
+\value{
+An \code{rtables} formatting function.
+}
+\description{
+Format numeric values to print with a specified number of significant figures.
+}
+\examples{
+fmt_3sf <- format_sigfig(3)
+fmt_3sf(1.658)
+fmt_3sf(1e1)
+
+fmt_5sf <- format_sigfig(5)
+fmt_5sf(0.57)
+fmt_5sf(0.000025645)
+
+}
+\seealso{
+Other formatting functions: 
+\code{\link{extreme_format}},
+\code{\link{format_count_fraction_fixed_dp}()},
+\code{\link{format_count_fraction}()},
+\code{\link{format_extreme_values_ci}()},
+\code{\link{format_extreme_values}()},
+\code{\link{format_fraction_fixed_dp}()},
+\code{\link{format_fraction_threshold}()},
+\code{\link{format_fraction}()},
+\code{\link{format_xx}()},
+\code{\link{formatting_functions}}
+}
+\concept{formatting functions}
diff --git a/man/format_xx.Rd b/man/format_xx.Rd
index db9b1be013..5da74756b1 100644
--- a/man/format_xx.Rd
+++ b/man/format_xx.Rd
@@ -39,6 +39,7 @@ Other formatting functions:
 \code{\link{format_fraction_fixed_dp}()},
 \code{\link{format_fraction_threshold}()},
 \code{\link{format_fraction}()},
+\code{\link{format_sigfig}()},
 \code{\link{formatting_functions}}
 }
 \concept{formatting functions}
diff --git a/man/formatting_functions.Rd b/man/formatting_functions.Rd
index 253d630cd8..3a31dede96 100644
--- a/man/formatting_functions.Rd
+++ b/man/formatting_functions.Rd
@@ -21,6 +21,7 @@ Other formatting functions:
 \code{\link{format_fraction_fixed_dp}()},
 \code{\link{format_fraction_threshold}()},
 \code{\link{format_fraction}()},
+\code{\link{format_sigfig}()},
 \code{\link{format_xx}()}
 }
 \concept{formatting functions}
diff --git a/man/imputation_rule.Rd b/man/imputation_rule.Rd
new file mode 100644
index 0000000000..73a981c293
--- /dev/null
+++ b/man/imputation_rule.Rd
@@ -0,0 +1,56 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/imputation_rule.R
+\name{imputation_rule}
+\alias{imputation_rule}
+\title{Apply 1/3 or 1/2 Imputation Rule to Data}
+\usage{
+imputation_rule(
+  df,
+  x_stats,
+  stat,
+  imp_rule,
+  post = FALSE,
+  avalcat_var = "AVALCAT1"
+)
+}
+\arguments{
+\item{df}{(\code{data.frame})\cr data set containing all analysis variables.}
+
+\item{x_stats}{(\verb{named list})\cr a named list of statistics, typically the results of \code{\link[=s_summary]{s_summary()}}.}
+
+\item{stat}{(\code{character})\cr statistic to return the value/NA level of according to the imputation
+rule applied.}
+
+\item{imp_rule}{(\code{character})\cr imputation rule setting. Set to \code{"1/3"} to implement 1/3 imputation
+rule or \code{"1/2"} to implement 1/2 imputation rule.}
+
+\item{post}{(\code{flag})\cr whether the data corresponds to a post-dose time-point (defaults to \code{FALSE}).
+This parameter is only used when \code{imp_rule} is set to \code{"1/3"}.}
+
+\item{avalcat_var}{(\code{character})\cr name of variable that indicates whether a row in \code{df} corresponds
+to an analysis value in category \code{"BLQ"}, \code{"LTR"}, \code{"<PCLLOQ"}, or none of the above
+(defaults to \code{"AVALCAT1"}). Variable \code{avalcat_var} must be present in \code{df}.}
+}
+\value{
+A \code{list} containing statistic value (\code{val}) and NA level (\code{na_level}) that should be displayed
+according to the specified imputation rule.
+}
+\description{
+\ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#stable}{\figure{lifecycle-stable.svg}{options: alt='[Stable]'}}}{\strong{[Stable]}}
+}
+\examples{
+set.seed(1)
+df <- data.frame(
+  AVAL = runif(50, 0, 1),
+  AVALCAT1 = sample(c(1, "BLQ"), 50, replace = TRUE)
+)
+x_stats <- s_summary(df$AVAL)
+imputation_rule(df, x_stats, "max", "1/3")
+imputation_rule(df, x_stats, "geom_mean", "1/3")
+imputation_rule(df, x_stats, "mean", "1/2")
+
+}
+\seealso{
+\code{\link[=analyze_vars_in_cols]{analyze_vars_in_cols()}} where this function can be implemented by setting the \code{imp_rule}
+argument.
+}
diff --git a/tests/testthat/_snaps/analyze_vars_in_cols.md b/tests/testthat/_snaps/analyze_vars_in_cols.md
index f6d6bc55ae..a8672d8d7b 100644
--- a/tests/testthat/_snaps/analyze_vars_in_cols.md
+++ b/tests/testthat/_snaps/analyze_vars_in_cols.md
@@ -164,3 +164,79 @@
         F           0           0          117 (22%)   
         M           0           0           72 (14%)   
 
+# analyze_vars_in_cols works with imputation rule
+
+    Code
+      res
+    Output
+                  n    Number of BLQs   Mean    SD    Geometric Mean   Minimum   Maximum
+      ——————————————————————————————————————————————————————————————————————————————————
+      A: Drug X                                                                         
+        Day 1                                                                           
+          0       36         17          ND     ND          NE           ND       92.4  
+          6       18         8           ND     ND         40.2          ND       97.6  
+          12      18         4          65.6   23.3        60.8         21.2      99.2  
+          18      18         12          ND     ND         44.6          ND       99.3  
+        Day 2                                                                           
+          24      18         7           ND     ND         42.0          ND       89.8  
+          30      18         11          ND     ND         35.6          ND       94.5  
+          36      18         11          ND     ND         36.1          ND       96.1  
+          42      18         9           ND     ND         41.8          ND       99.2  
+
+---
+
+    Code
+      res
+    Output
+                  n    Number of BLQs   Mean   SD   Geometric Mean   Minimum   Maximum
+      ————————————————————————————————————————————————————————————————————————————————
+      A: Drug X                                                                       
+        Day 1                                                                         
+          0       36         30          ND    ND         NE           ND       92.4  
+          6       18         14          ND    ND        40.2          ND       97.6  
+          12      18         12          ND    ND        60.8          ND       99.2  
+          18      18         16          ND    ND        44.6          ND       99.3  
+        Day 2                                                                         
+          24      18         9           ND    ND        42.0          ND       89.8  
+          30      18         11          ND    ND        35.6          ND       94.5  
+          36      18         12          ND    ND        36.1          ND       96.1  
+          42      18         13          ND    ND        41.8          ND       99.2  
+
+---
+
+    Code
+      res
+    Output
+                  n    Number of BLQs   Mean    SD    Geometric Mean   Minimum   Maximum
+      ——————————————————————————————————————————————————————————————————————————————————
+      A: Drug X                                                                         
+        Day 1                                                                           
+          0       36         17         43.4   25.6        32.8          2.3      92.4  
+          6       18         8          46.2   24.8        40.2         17.5      97.6  
+          12      18         4          65.6   23.3        60.8         21.2      99.2  
+          18      18         12          ND     ND          ND           ND       99.3  
+        Day 2                                                                           
+          24      18         7          51.4   25.8        42.0          7.7      89.8  
+          30      18         11          ND     ND          ND           ND       94.5  
+          36      18         11          ND     ND          ND           ND       96.1  
+          42      18         9          54.6   28.4        41.8          1.3      99.2  
+
+# analyze_vars_in_cols works with caching
+
+    Code
+      res
+    Output
+                  n    Number of BLQs   Mean    SD    Geometric Mean   Minimum   Maximum
+      ——————————————————————————————————————————————————————————————————————————————————
+      A: Drug X                                                                         
+        Day 1                                                                           
+          0       36         17         43.4   25.6        32.8          2.3      92.4  
+          6       18         8          46.2   24.8        40.2         17.5      97.6  
+          12      18         4          65.6   23.3        60.8         21.2      99.2  
+          18      18         12         54.1   27.1        44.6          7.5      99.3  
+        Day 2                                                                           
+          24      18         7          51.4   25.8        42.0          7.7      89.8  
+          30      18         11         48.2   31.8        35.6          3.6      94.5  
+          36      18         11         47.0   25.6        36.1          1.3      96.1  
+          42      18         9          54.6   28.4        41.8          1.3      99.2  
+
diff --git a/tests/testthat/_snaps/formats.md b/tests/testthat/_snaps/formats.md
index e5d5bbcb89..54d6f94742 100644
--- a/tests/testthat/_snaps/formats.md
+++ b/tests/testthat/_snaps/formats.md
@@ -75,6 +75,13 @@
     Output
       [1] "2 (0.6)"    "10 (785.6)"
 
+# format_sigfig works with easy inputs
+
+    Code
+      res
+    Output
+      [1] "1.66"    "0.576"   "0.100"   "78.6"    "0.00123"
+
 # format_fraction_threshold works with easy inputs
 
     Code
diff --git a/tests/testthat/_snaps/imputation_rule.md b/tests/testthat/_snaps/imputation_rule.md
new file mode 100644
index 0000000000..3b05de04c5
--- /dev/null
+++ b/tests/testthat/_snaps/imputation_rule.md
@@ -0,0 +1,103 @@
+# imputation_rule works correctly for 1/3 imputation rule
+
+    Code
+      result
+    Output
+      $val
+           max 
+      92.40745 
+      
+      $na_level
+      [1] "ND"
+      
+
+---
+
+    Code
+      result
+    Output
+      $val
+      [1] NA
+      
+      $na_level
+      [1] "ND"
+      
+
+---
+
+    Code
+      result
+    Output
+      $val
+      geom_mean 
+       40.22144 
+      
+      $na_level
+      [1] "NE"
+      
+
+---
+
+    Code
+      result
+    Output
+      $val
+           max 
+      99.26841 
+      
+      $na_level
+      [1] "ND"
+      
+
+# imputation_rule works correctly for 1/2 imputation rule
+
+    Code
+      result
+    Output
+      $val
+           max 
+      92.40745 
+      
+      $na_level
+      [1] "NE"
+      
+
+---
+
+    Code
+      result
+    Output
+      $val
+          mean 
+      43.38858 
+      
+      $na_level
+      [1] "NE"
+      
+
+---
+
+    Code
+      result
+    Output
+      $val
+      geom_mean 
+       40.22144 
+      
+      $na_level
+      [1] "NE"
+      
+
+---
+
+    Code
+      result
+    Output
+      $val
+           max 
+      99.26841 
+      
+      $na_level
+      [1] "NE"
+      
+
diff --git a/tests/testthat/_snaps/utils_rtables.md b/tests/testthat/_snaps/utils_rtables.md
index d7268c0a8e..80ad82cf17 100644
--- a/tests/testthat/_snaps/utils_rtables.md
+++ b/tests/testthat/_snaps/utils_rtables.md
@@ -174,11 +174,20 @@
     Code
       res
     Output
-      $row_count
-      [1] 4 4
-      attr(,"label")
-      [1] "female (N=4)"
-      
+      RowsVerticalSection (in_rows) object print method:
+      ----------------------------
+         row_name formatted_cell indent_mod    row_label
+      1 row_count                         0 female (N=4)
+
+# c_label_n_alt works as expected
+
+    Code
+      res
+    Output
+      RowsVerticalSection (in_rows) object print method:
+      ----------------------------
+         row_name formatted_cell indent_mod     row_label
+      1 row_count                         0 female (N=10)
 
 # add_rowcounts works with one row split
 
@@ -272,6 +281,22 @@
         BLACK OR AFRICAN AMERICAN      18           12             13      
         WHITE                           8           7              8       
 
+# add_rowcounts works with alt_counts = TRUE
+
+    Code
+      res
+    Output
+                                    A: Drug X   B: Placebo   C: Combination
+      —————————————————————————————————————————————————————————————————————
+      F (N=52)                                                             
+        ASIAN                          44           37             40      
+        BLACK OR AFRICAN AMERICAN      18           12             13      
+        WHITE                           8           7              8       
+      M (N=48)                                                             
+        ASIAN                          35           31             44      
+        BLACK OR AFRICAN AMERICAN      10           12             14      
+        WHITE                           6           7              10      
+
 # h_col_indices works as expected
 
     Code
diff --git a/tests/testthat/test-analyze_vars_in_cols.R b/tests/testthat/test-analyze_vars_in_cols.R
index 7985b6fb11..73d07357a5 100644
--- a/tests/testthat/test-analyze_vars_in_cols.R
+++ b/tests/testthat/test-analyze_vars_in_cols.R
@@ -270,3 +270,146 @@ testthat::test_that("analyze_vars_in_cols works well with categorical data", {
     append_topleft("  SEX") %>%
     build_table(adpp))
 })
+
+testthat::test_that("analyze_vars_in_cols works with imputation rule", {
+  set.seed(1)
+  df <- data.frame(
+    ARM = with_label(rep("A: Drug X", 162), "Arm"),
+    AVAL = runif(162, 0, 100),
+    AVALCAT1 = as.factor(sample(c(1, "BLQ"), 162, replace = TRUE)),
+    AVALCAT2 = as.factor(sample(c(1, "BLQ"), 162, replace = TRUE, prob = c(0.25, 0.75))),
+    VISIT = with_label(as.factor(rep(c(rep("Day 1", 5), rep("Day 2", 4)), 18)), "Visit"),
+    NFRLT = with_label(as.factor(rep(c(0, seq(0, 42, 6)), 18)), "Nominal Time")
+  )
+
+  # 1/3 imputation rule
+  lyt <- basic_table() %>%
+    split_rows_by(
+      var = "ARM",
+      split_fun = drop_split_levels
+    ) %>%
+    split_rows_by(
+      var = "VISIT",
+      split_fun = drop_split_levels
+    ) %>%
+    split_rows_by(
+      var = "NFRLT",
+      split_fun = drop_split_levels,
+      child_labels = "hidden"
+    ) %>%
+    analyze_vars_in_cols(
+      vars = c("AVAL", "AVALCAT1", rep("AVAL", 5)),
+      .stats = c("n", "n_blq", "mean", "sd", "geom_mean", "min", "max"),
+      .labels = c(
+        n = "n", n_blq = "Number of BLQs", mean = "Mean", sd = "SD",
+        geom_mean = "Geometric Mean", min = "Minimum", max = "Maximum"
+      ),
+      imp_rule = "1/3"
+    )
+
+  result <- build_table(lyt = lyt, df = df)
+
+  res <- testthat::expect_silent(result)
+  testthat::expect_snapshot(res)
+
+  # 1/3 imputation rule, custom avalcat_var
+  lyt <- basic_table() %>%
+    split_rows_by(
+      var = "ARM",
+      split_fun = drop_split_levels
+    ) %>%
+    split_rows_by(
+      var = "VISIT",
+      split_fun = drop_split_levels
+    ) %>%
+    split_rows_by(
+      var = "NFRLT",
+      split_fun = drop_split_levels,
+      child_labels = "hidden"
+    ) %>%
+    analyze_vars_in_cols(
+      vars = c("AVAL", "AVALCAT2", rep("AVAL", 5)),
+      .stats = c("n", "n_blq", "mean", "sd", "geom_mean", "min", "max"),
+      .labels = c(
+        n = "n", n_blq = "Number of BLQs", mean = "Mean", sd = "SD",
+        geom_mean = "Geometric Mean", min = "Minimum", max = "Maximum"
+      ),
+      imp_rule = "1/3",
+      avalcat_var = "AVALCAT2"
+    )
+
+  result <- build_table(lyt = lyt, df = df)
+
+  res <- testthat::expect_silent(result)
+  testthat::expect_snapshot(res)
+
+  # 1/2 imputation rule
+  lyt <- basic_table() %>%
+    split_rows_by(
+      var = "ARM",
+      split_fun = drop_split_levels
+    ) %>%
+    split_rows_by(
+      var = "VISIT",
+      split_fun = drop_split_levels
+    ) %>%
+    split_rows_by(
+      var = "NFRLT",
+      split_fun = drop_split_levels,
+      child_labels = "hidden"
+    ) %>%
+    analyze_vars_in_cols(
+      vars = c("AVAL", "AVALCAT1", rep("AVAL", 5)),
+      .stats = c("n", "n_blq", "mean", "sd", "geom_mean", "min", "max"),
+      .labels = c(
+        n = "n", n_blq = "Number of BLQs", mean = "Mean", sd = "SD",
+        geom_mean = "Geometric Mean", min = "Minimum", max = "Maximum"
+      ),
+      imp_rule = "1/2"
+    )
+
+  result <- build_table(lyt = lyt, df = df)
+
+  res <- testthat::expect_silent(result)
+  testthat::expect_snapshot(res)
+})
+
+testthat::test_that("analyze_vars_in_cols works with caching", {
+  set.seed(1)
+  df <- data.frame(
+    ARM = with_label(rep("A: Drug X", 162), "Arm"),
+    AVAL = runif(162, 0, 100),
+    AVALCAT1 = as.factor(sample(c(1, "BLQ"), 162, replace = TRUE)),
+    VISIT = with_label(as.factor(rep(c(rep("Day 1", 5), rep("Day 2", 4)), 18)), "Visit"),
+    NFRLT = with_label(as.factor(rep(c(0, seq(0, 42, 6)), 18)), "Nominal Time")
+  )
+
+  lyt <- basic_table() %>%
+    split_rows_by(
+      var = "ARM",
+      split_fun = drop_split_levels
+    ) %>%
+    split_rows_by(
+      var = "VISIT",
+      split_fun = drop_split_levels
+    ) %>%
+    split_rows_by(
+      var = "NFRLT",
+      split_fun = drop_split_levels,
+      child_labels = "hidden"
+    ) %>%
+    analyze_vars_in_cols(
+      vars = c("AVAL", "AVALCAT1", rep("AVAL", 5)),
+      .stats = c("n", "n_blq", "mean", "sd", "geom_mean", "min", "max"),
+      .labels = c(
+        n = "n", n_blq = "Number of BLQs", mean = "Mean", sd = "SD",
+        geom_mean = "Geometric Mean", min = "Minimum", max = "Maximum"
+      ),
+      cache = TRUE
+    )
+
+  result <- build_table(lyt = lyt, df = df)
+
+  res <- testthat::expect_silent(result)
+  testthat::expect_snapshot(res)
+})
diff --git a/tests/testthat/test-formats.R b/tests/testthat/test-formats.R
index ff66572576..4fc1ea1c9c 100644
--- a/tests/testthat/test-formats.R
+++ b/tests/testthat/test-formats.R
@@ -92,6 +92,15 @@ testthat::test_that("format_xx works with easy inputs", {
   testthat::expect_snapshot(res)
 })
 
+testthat::test_that("format_sigfig works with easy inputs", {
+  test <- list(1.658, 0.5761, 1e-1, 78.6, 1234e-6)
+  z <- format_sigfig(3)
+  result <- sapply(test, z)
+
+  res <- testthat::expect_silent(result)
+  testthat::expect_snapshot(res)
+})
+
 testthat::test_that("format_fraction_threshold works with easy inputs", {
   test <- list(c(100, 0.1), c(10, 0.01), c(0, 0))
   format_fun <- format_fraction_threshold(0.02)
diff --git a/tests/testthat/test-imputation_rule.R b/tests/testthat/test-imputation_rule.R
new file mode 100644
index 0000000000..81003526ab
--- /dev/null
+++ b/tests/testthat/test-imputation_rule.R
@@ -0,0 +1,44 @@
+set.seed(1)
+df <- data.frame(
+  ARM = with_label(rep("A: Drug X", 162), "Arm"),
+  AVAL = runif(162, 0, 100),
+  AVALCAT1 = as.factor(sample(c(1, "BLQ"), 162, replace = TRUE)),
+  VISIT = with_label(as.factor(rep(c(rep("Day 1", 5), rep("Day 2", 4)), 18)), "Visit"),
+  NFRLT = with_label(as.factor(rep(c(0, seq(0, 42, 6)), 18)), "Nominal Time")
+)
+
+testthat::test_that("imputation_rule works correctly for 1/3 imputation rule", {
+  x_stats <- s_summary(df$AVAL[df$NFRLT == 0])
+  result <- imputation_rule(df, x_stats, "max", "1/3")
+  res <- testthat::expect_snapshot(result)
+
+  x_stats <- s_summary(df$AVAL[df$NFRLT == 0])
+  result <- imputation_rule(df, x_stats, "mean", "1/3")
+  res <- testthat::expect_snapshot(result)
+
+  x_stats <- s_summary(df$AVAL[df$NFRLT == 6])
+  result <- imputation_rule(df, x_stats, "geom_mean", "1/3", post = TRUE)
+  res <- testthat::expect_snapshot(result)
+
+  x_stats <- s_summary(df$AVAL[df$NFRLT == 18])
+  result <- imputation_rule(df, x_stats, "max", "1/3", post = TRUE)
+  res <- testthat::expect_snapshot(result)
+})
+
+testthat::test_that("imputation_rule works correctly for 1/2 imputation rule", {
+  x_stats <- s_summary(df$AVAL[df$NFRLT == 0])
+  result <- imputation_rule(df, x_stats, "max", "1/2")
+  res <- testthat::expect_snapshot(result)
+
+  x_stats <- s_summary(df$AVAL[df$NFRLT == 0])
+  result <- imputation_rule(df, x_stats, "mean", "1/2")
+  res <- testthat::expect_snapshot(result)
+
+  x_stats <- s_summary(df$AVAL[df$NFRLT == 6])
+  result <- imputation_rule(df, x_stats, "geom_mean", "1/2", post = TRUE)
+  res <- testthat::expect_snapshot(result)
+
+  x_stats <- s_summary(df$AVAL[df$NFRLT == 18])
+  result <- imputation_rule(df, x_stats, "max", "1/2", post = TRUE)
+  res <- testthat::expect_snapshot(result)
+})
diff --git a/tests/testthat/test-utils_rtables.R b/tests/testthat/test-utils_rtables.R
index 7a82b465bc..5e5300816e 100644
--- a/tests/testthat/test-utils_rtables.R
+++ b/tests/testthat/test-utils_rtables.R
@@ -87,6 +87,13 @@ testthat::test_that("c_label_n works as expected", {
   testthat::expect_snapshot(res)
 })
 
+testthat::test_that("c_label_n_alt works as expected", {
+  result <- c_label_n_alt(data.frame(a = c(1, 2)), "female", .alt_df_row = data.frame(a = 1:10))
+
+  res <- testthat::expect_silent(result)
+  testthat::expect_snapshot(res)
+})
+
 testthat::test_that("add_rowcounts works with one row split", {
   result <- basic_table() %>%
     split_rows_by("SEX", split_fun = drop_split_levels) %>%
@@ -137,6 +144,21 @@ testthat::test_that("add_rowcounts works with pruning", {
   testthat::expect_snapshot(res)
 })
 
+testthat::test_that("add_rowcounts works with alt_counts = TRUE", {
+  DM_alt <- DM[1:100, ] # nolint
+
+  result <- basic_table() %>%
+    split_cols_by("ARM") %>%
+    split_rows_by("SEX", split_fun = drop_split_levels) %>%
+    add_rowcounts(alt_counts = TRUE) %>%
+    analyze("RACE") %>%
+    build_table(DM, alt_counts_df = DM_alt) %>%
+    prune_table()
+
+  res <- testthat::expect_silent(result)
+  testthat::expect_snapshot(res)
+})
+
 testthat::test_that("h_col_indices works as expected", {
   tab <- basic_table() %>%
     split_cols_by("ARM") %>%