diff --git a/DESCRIPTION b/DESCRIPTION
index 81b956155..6fd8355cd 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: gtsummary
 Title: Presentation-Ready Data Summary and Analytic Result Tables
-Version: 2.0.1.9008
+Version: 2.0.1.9009
 Authors@R: c(
     person("Daniel D.", "Sjoberg", , "danield.sjoberg@gmail.com", role = c("aut", "cre"),
            comment = c(ORCID = "0000-0003-0862-2018")),
diff --git a/NAMESPACE b/NAMESPACE
index 423766794..b88ea53c4 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -6,6 +6,7 @@ S3method(add_difference,tbl_summary)
 S3method(add_difference,tbl_svysummary)
 S3method(add_global_p,tbl_regression)
 S3method(add_global_p,tbl_uvregression)
+S3method(add_n,tbl_likert)
 S3method(add_n,tbl_regression)
 S3method(add_n,tbl_summary)
 S3method(add_n,tbl_survfit)
@@ -195,6 +196,7 @@ export(tbl_butcher)
 export(tbl_continuous)
 export(tbl_cross)
 export(tbl_custom_summary)
+export(tbl_likert)
 export(tbl_merge)
 export(tbl_regression)
 export(tbl_split)
diff --git a/NEWS.md b/NEWS.md
index 72f4dae5a..669a4c7cb 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -21,6 +21,8 @@ Updates to address regressions in the v2.0.0 release:
 
 * The `add_glance*(glance_fun)` argument's default value has been updated to an S3 generic, allowing bespoke handling for some regression classes. (#1822)
 
+* Added function `tbl_likert()` for summarizing ordered categorical (or Likert scales) data as well as the associated `add_n.tbl_likert()` S3 method. (#1660)
+
 # gtsummary 2.0.1
 
 Updates to address regressions in the v2.0.0 release:
diff --git a/R/add_n.R b/R/add_n.R
index 0e2078971..e41cbdcbd 100644
--- a/R/add_n.R
+++ b/R/add_n.R
@@ -222,3 +222,7 @@ add_n.tbl_summary <- function(x, statistic = "{N_nonmiss}", col_label = "**N**",
 #' @name add_n_summary
 #' @export
 add_n.tbl_svysummary <- add_n.tbl_summary
+
+#' @name add_n_summary
+#' @export
+add_n.tbl_likert <- add_n.tbl_summary
diff --git a/R/tbl_likert.R b/R/tbl_likert.R
new file mode 100644
index 000000000..2017ae36f
--- /dev/null
+++ b/R/tbl_likert.R
@@ -0,0 +1,254 @@
+#' Likert Summary
+#'
+#' `r lifecycle::badge("experimental")`\cr
+#' Create a table of ordered categorical variables in a wide format.
+#'
+#' @inheritParams tbl_summary
+#' @param statistic ([`formula-list-selector`][syntax])\cr
+#'   Used to specify the summary statistics for each variable.
+#'   The default is `everything() ~ "{n} ({p}%)"`.
+#' @param digits ([`formula-list-selector`][syntax])\cr
+#'  Specifies how summary statistics are rounded. Values may be either integer(s)
+#'   or function(s). If not specified, default formatting is assigned
+#'   via `assign_summary_digits()`.
+#' @param sort (`string`)\cr
+#'   indicates whether levels of variables should be placed in
+#'   ascending order (the default) or descending.
+#'
+#' @return a 'tbl_likert' gtsummary table
+#' @export
+#'
+#' @examples
+#' levels <- c("Strongly Disagree", "Disagree", "Agree", "Strongly Agree")
+#' df_likert <- data.frame(
+#'   recommend_friend = sample(levels, size = 20, replace = TRUE) |> factor(levels = levels),
+#'   regret_purchase = sample(levels, size = 20, replace = TRUE) |> factor(levels = levels)
+#' )
+#'
+#' # Example 1 ----------------------------------
+#' tbl_likert_ex1 <-
+#'   df_likert |>
+#'   tbl_likert(include = c(recommend_friend, regret_purchase)) |>
+#'   add_n()
+#' tbl_likert_ex1
+#'
+#' # Example 2 ----------------------------------
+#' # Add continuous summary of the likert scores
+#' list(
+#'   tbl_likert_ex1,
+#'   tbl_wide_summary(
+#'     df_likert |> dplyr::mutate(dplyr::across(everything(), as.numeric)),
+#'     statistic = c("{mean}", "{sd}"),
+#'     type = ~"continuous",
+#'     include = c(recommend_friend, regret_purchase)
+#'   )
+#' ) |>
+#'   tbl_merge(tab_spanner = FALSE)
+tbl_likert <- function(data,
+                       statistic = ~"{n} ({p}%)",
+                       label = NULL,
+                       digits = NULL,
+                       include = everything(),
+                       sort = c("ascending", "descending")) {
+  set_cli_abort_call()
+
+  # process inputs -------------------------------------------------------------
+  check_not_missing(data)
+  check_data_frame(data)
+  sort <- arg_match(sort)
+
+  cards::process_selectors(data, include = {{ include }})
+
+  cards::process_formula_selectors(data[include], label = label, statistic = statistic, digits = digits)
+  cards::check_list_elements(
+    x = label,
+    predicate = \(x) is_string(x),
+    error_msg = "Values pass in {.arg label} argument must be strings."
+  )
+  cards::check_list_elements(
+    x = statistic,
+    predicate = \(x) is_string(x),
+    error_msg = "Values pass in {.arg statistic} argument must be strings."
+  )
+
+  # fill in unspecified variables
+  cards::fill_formula_selectors(
+    data[include],
+    statistic = eval(formals(gtsummary::tbl_likert)[["statistic"]])
+  )
+
+  # fill each element of digits argument
+  if (!missing(digits)) {
+    digits <-
+      assign_summary_digits(data[include], statistic, type = rep_named(include, list("categorical")), digits = digits)
+  }
+
+  .check_haven_labelled(data[include])
+  .check_tbl_summary_args(
+    data = data, label = label, statistic = statistic,
+    digits = digits, type = rep_named(include, list("categorical")), value = NULL
+  )
+
+  # save processed function inputs ---------------------------------------------
+  tbl_likert_inputs <- as.list(environment())
+  call <- match.call()
+
+  # check all variables are factors --------------------------------------------
+  if (some(include, ~!inherits(data[[.x]], "factor"))) {
+    not_fct <- map_chr(include, ~ifelse(!inherits(data[[.x]], "factor"), .x, NA_character_)) |> discard(is.na)
+    cli::cli_abort(
+      c("All variables in the {.arg include} argument must be {.cls factor}.",
+        i = "Variables {.val {not_fct}} are not class {.cls factor}.")
+    )
+  }
+
+  # check all factors have the same levels -------------------------------------
+  walk(
+    include[-1],
+    \(x) {
+      if (!identical(levels(data[[include[1]]]), levels(data[[x]]))) {
+        cli::cli_abort(
+          c("All variables in the {.arg include} argument must have the same factor levels.",
+            i = "Variable {.val {include[1]}} has levels {.val {levels(data[[include[1]]])}}.",
+            i = "Variable {.val {x}} has levels {.val {levels(data[[x]])}}.",
+            i = "Use {.fun forcats::fct_unify} to unify levels."),
+          call = get_cli_abort_call()
+        )
+      }
+    }
+  )
+
+  # reverse the order of the levels if indicated -------------------------------
+  if (sort == "descending") {
+    data <- data |> dplyr::mutate(across(all_of(include), fct_rev))
+  }
+
+  # tabulate results -----------------------------------------------------------
+  cards <-
+    dplyr::bind_rows(
+      cards::ard_attributes(
+        data = data,
+        variables = all_of(include),
+        label = label
+      ),
+      cards::ard_missing(data, variables = all_of(include)),
+      cards::ard_categorical(
+        data = data,
+        variables = all_of(include),
+        fmt_fn = digits,
+        denominator = "column",
+        stat_label = ~ default_stat_labels()
+      )
+    ) |>
+    cards::replace_null_statistic()
+
+  # print all warnings and errors that occurred while calculating requested stats
+  cards::print_ard_conditions(cards)
+
+  # translate statistic labels -------------------------------------------------
+  cards$stat_label <- translate_vector(cards$stat_label)
+
+  # add the gtsummary column names to ARD data frame ---------------------------
+  cards <-
+    cards |>
+    dplyr::left_join(
+      dplyr::tibble(
+        variable_level = factor(levels(data[[include[1]]]), levels = levels(data[[include[1]]])) |> as.list(),
+        gts_column = paste0("stat_", seq_along(levels(data[[include[1]]])))
+      ),
+      by = "variable_level"
+    )
+
+  x <-
+    brdg_likert(cards = cards, variables = include, statistic = statistic) |>
+    append(
+      list(
+        cards = list(tbl_likert = cards),
+        inputs = tbl_likert_inputs
+      )
+    ) |>
+    structure(class = c("tbl_likert", "gtsummary"))
+
+  # adding styling -------------------------------------------------------------
+  x <- x |>
+    # updating the headers for the stats columns
+    modify_header(all_stat_cols() ~ "**{level}**")
+
+  # return tbl_summary table ---------------------------------------------------
+  x$call_list <- list(tbl_likert = call)
+
+  x
+
+}
+
+brdg_likert <- function(cards,
+                        variables,
+                        statistic) {
+  set_cli_abort_call()
+
+  # check the ARD has all the requested statistics -----------------------------
+  walk(
+    variables,
+    \(variable) {
+      specified_stats <- .extract_glue_elements(statistic[[variable]])
+      available_stats <- dplyr::filter(cards, .data$variable %in% .env$variable, !is.na(.data$gts_column))$stat_name |> unique()
+
+      if (is_empty(specified_stats)) {
+        cli::cli_abort("The {.arg statistic} argument string does not contain any
+                        glue element for variable {.val {variable}}, e.g. {.val {{n}} ({{p}}%)}.",
+                       call = get_cli_abort_call())
+      }
+      if (any(!specified_stats %in% available_stats)) {
+        not_valid_stat <- specified_stats[!specified_stats %in% available_stats]
+        cli::cli_abort(c("Statistic(s) {.val {not_valid_stat}} are not valid.",
+                         i = "Select one or more of {.val {available_stats}}"),
+                       call = get_cli_abort_call())
+      }
+    }
+  )
+
+  # create table_body ----------------------------------------------------------
+  table_body <-
+    pier_likert(cards = cards, variables = variables, statistic = statistic)
+
+  # construct default table_styling --------------------------------------------
+  x <- .create_gtsummary_object(table_body)
+
+  # add info to x$table_styling$header for dynamic headers ---------------------
+  x$table_styling$header <-
+    x$table_styling$header |>
+    dplyr::left_join(
+      cards |>
+        dplyr::filter(!is.na(.data$gts_column)) |>
+        dplyr::select(column = "gts_column", modify_stat_level = "variable_level") |>
+        unique() |>
+        dplyr::mutate(modify_stat_level = unlist(.data$modify_stat_level) |> as.character()),
+      by = "column"
+    )
+
+
+  # adding styling -------------------------------------------------------------
+  x <- x |>
+    # add header to label column and add default indentation
+    modify_table_styling(
+      columns = "label",
+      label = glue("**{translate_string('Characteristic')}**")
+    )
+
+  x |>
+    structure(class = "gtsummary") |>
+    modify_column_unhide(columns = all_stat_cols())
+}
+
+pier_likert <- function(cards, variables, statistic) {
+  set_cli_abort_call()
+
+  pier_summary_continuous(
+    cards =
+      cards |>
+      dplyr::filter(!is.na(.data$gts_column) | .data$context %in% "attributes") |>
+      dplyr::mutate(group1 = .data$variable, group1_level = .data$variable_level),
+    variables = variables,
+    statistic = statistic
+  )
+}
diff --git a/man/add_n_summary.Rd b/man/add_n_summary.Rd
index d131e79c9..2bcbad140 100644
--- a/man/add_n_summary.Rd
+++ b/man/add_n_summary.Rd
@@ -4,6 +4,7 @@
 \alias{add_n_summary}
 \alias{add_n.tbl_summary}
 \alias{add_n.tbl_svysummary}
+\alias{add_n.tbl_likert}
 \title{Add column with N}
 \usage{
 \method{add_n}{tbl_summary}(
@@ -23,6 +24,15 @@
   last = FALSE,
   ...
 )
+
+\method{add_n}{tbl_likert}(
+  x,
+  statistic = "{N_nonmiss}",
+  col_label = "**N**",
+  footnote = FALSE,
+  last = FALSE,
+  ...
+)
 }
 \arguments{
 \item{x}{(\code{tbl_summary})\cr
diff --git a/man/tbl_likert.Rd b/man/tbl_likert.Rd
new file mode 100644
index 000000000..4de14971e
--- /dev/null
+++ b/man/tbl_likert.Rd
@@ -0,0 +1,73 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/tbl_likert.R
+\name{tbl_likert}
+\alias{tbl_likert}
+\title{Likert Summary}
+\usage{
+tbl_likert(
+  data,
+  statistic = ~"{n} ({p}\%)",
+  label = NULL,
+  digits = NULL,
+  include = everything(),
+  sort = c("ascending", "descending")
+)
+}
+\arguments{
+\item{data}{(\code{data.frame})\cr A data frame.}
+
+\item{statistic}{(\code{\link[=syntax]{formula-list-selector}})\cr
+Used to specify the summary statistics for each variable.
+The default is \code{everything() ~ "{n} ({p}\%)"}.}
+
+\item{label}{(\code{\link[=syntax]{formula-list-selector}})\cr
+Used to override default labels in summary table, e.g. \code{list(age = "Age, years")}.
+The default for each variable is the column label attribute, \code{attr(., 'label')}.
+If no label has been set, the column name is used.}
+
+\item{digits}{(\code{\link[=syntax]{formula-list-selector}})\cr
+Specifies how summary statistics are rounded. Values may be either integer(s)
+or function(s). If not specified, default formatting is assigned
+via \code{assign_summary_digits()}.}
+
+\item{include}{(\code{\link[dplyr:dplyr_tidy_select]{tidy-select}})\cr
+Variables to include in the summary table. Default is \code{everything()}.}
+
+\item{sort}{(\code{string})\cr
+indicates whether levels of variables should be placed in
+ascending order (the default) or descending.}
+}
+\value{
+a 'tbl_likert' gtsummary table
+}
+\description{
+\ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#experimental}{\figure{lifecycle-experimental.svg}{options: alt='[Experimental]'}}}{\strong{[Experimental]}}\cr
+Create a table of ordered categorical variables in a wide format.
+}
+\examples{
+levels <- c("Strongly Disagree", "Disagree", "Agree", "Strongly Agree")
+df_likert <- data.frame(
+  recommend_friend = sample(levels, size = 20, replace = TRUE) |> factor(levels = levels),
+  regret_purchase = sample(levels, size = 20, replace = TRUE) |> factor(levels = levels)
+)
+
+# Example 1 ----------------------------------
+tbl_likert_ex1 <-
+  df_likert |>
+  tbl_likert(include = c(recommend_friend, regret_purchase)) |>
+  add_n()
+tbl_likert_ex1
+
+# Example 2 ----------------------------------
+# Add continuous summary of the likert scores
+list(
+  tbl_likert_ex1,
+  tbl_wide_summary(
+    df_likert |> dplyr::mutate(dplyr::across(everything(), as.numeric)),
+    statistic = c("{mean}", "{sd}"),
+    type = ~"continuous",
+    include = c(recommend_friend, regret_purchase)
+  )
+) |>
+  tbl_merge(tab_spanner = FALSE)
+}
diff --git a/pkgdown/_pkgdown.yml b/pkgdown/_pkgdown.yml
index e900c6477..8b5f94aff 100644
--- a/pkgdown/_pkgdown.yml
+++ b/pkgdown/_pkgdown.yml
@@ -70,9 +70,6 @@ reference:
       - add_stat_label
       - add_stat
       - separate_p_footnotes
-  - subtitle: Wide Summary Tables
-  - contents:
-      - tbl_wide_summary
   - subtitle: Cross Tables
   - contents:
       - tbl_cross
@@ -83,6 +80,13 @@ reference:
       - add_overall.tbl_continuous
       - add_p.tbl_continuous
       - add_stat
+  - subtitle: Wide Summary Tables
+  - contents:
+      - tbl_wide_summary
+  - subtitle: Likert Summary Tables
+  - contents:
+      - tbl_likert
+      - add_n.tbl_likert
   - subtitle: Time-to-event Summary Tables
   - contents:
       - tbl_survfit
diff --git a/tests/testthat/_snaps/tbl_likert.md b/tests/testthat/_snaps/tbl_likert.md
new file mode 100644
index 000000000..719d51cb6
--- /dev/null
+++ b/tests/testthat/_snaps/tbl_likert.md
@@ -0,0 +1,49 @@
+# tbl_likert(data)
+
+    Code
+      as.data.frame(add_n(tbl_likert(df_likert)))
+    Output
+        **Characteristic** **N** **Strongly Disagree** **Disagree** **Agree**
+      1   recommend_friend    20               7 (35%)      3 (15%)   7 (35%)
+      2    regret_purchase    20               7 (35%)     1 (5.0%)   8 (40%)
+        **Strongly Agree**
+      1            3 (15%)
+      2            4 (20%)
+
+# tbl_likert(statistic)
+
+    Code
+      as.data.frame(tbl_likert(df_likert, statistic = ~"{n} / {N} ({p}%)"))
+    Output
+        **Characteristic** **Strongly Disagree**  **Disagree**    **Agree**
+      1   recommend_friend          7 / 20 (35%)  3 / 20 (15%) 7 / 20 (35%)
+      2    regret_purchase          7 / 20 (35%) 1 / 20 (5.0%) 8 / 20 (40%)
+        **Strongly Agree**
+      1       3 / 20 (15%)
+      2       4 / 20 (20%)
+
+# tbl_likert(digits)
+
+    Code
+      as.data.frame(tbl_likert(df_likert, digits = ~ list(p = label_style_sigfig(
+        digits = 3, scale = 100))))
+    Output
+        **Characteristic** **Strongly Disagree** **Disagree** **Agree**
+      1   recommend_friend             7 (35.0%)    3 (15.0%) 7 (35.0%)
+      2    regret_purchase             7 (35.0%)    1 (5.00%) 8 (40.0%)
+        **Strongly Agree**
+      1          3 (15.0%)
+      2          4 (20.0%)
+
+# tbl_likert(sort)
+
+    Code
+      as.data.frame(tbl_likert(df_likert, sort = "descending"))
+    Output
+        **Characteristic** **Strongly Agree** **Agree** **Disagree**
+      1   recommend_friend            3 (15%)   7 (35%)      3 (15%)
+      2    regret_purchase            4 (20%)   8 (40%)     1 (5.0%)
+        **Strongly Disagree**
+      1               7 (35%)
+      2               7 (35%)
+
diff --git a/tests/testthat/test-tbl_likert.R b/tests/testthat/test-tbl_likert.R
new file mode 100644
index 000000000..d9d1d4273
--- /dev/null
+++ b/tests/testthat/test-tbl_likert.R
@@ -0,0 +1,116 @@
+skip_if_not(is_pkg_installed("withr", reference_pkg = "gtsummary"))
+
+levels <- c("Strongly Disagree", "Disagree", "Agree", "Strongly Agree")
+df_likert <-
+  withr::with_seed(
+    seed = 11235,
+    data.frame(
+      recommend_friend = sample(levels, size = 20, replace = TRUE) |> factor(levels = levels),
+      regret_purchase = sample(levels, size = 20, replace = TRUE) |> factor(levels = levels)
+    )
+  )
+
+test_that("tbl_likert(data)", {
+  # standard use works well
+  expect_snapshot(
+    df_likert |>
+      tbl_likert() |>
+      add_n() |>
+      as.data.frame()
+  )
+
+  # errors with bad input
+  expect_error(
+    tbl_likert(letters),
+    "The `data` argument must be class"
+  )
+})
+
+test_that("tbl_likert(statistic)", {
+  # standard use works well
+  expect_snapshot(
+    df_likert |>
+      tbl_likert(statistic = ~"{n} / {N} ({p}%)") |>
+      as.data.frame()
+  )
+
+  # errors with bad inputs
+  expect_error(
+    df_likert |>
+      tbl_likert(statistic = ~letters),
+    "Values pass in `statistic` argument must be strings"
+  )
+
+  # statistic doesn't have any glue syntax
+  expect_error(
+    df_likert |>
+      tbl_likert(statistic = ~"n / N"),
+    "The `statistic` argument string does not contain any glue element"
+  )
+
+  # statistic has stats that are not available
+  expect_error(
+    df_likert |>
+      tbl_likert(statistic = ~"{n} ({sd})"),
+    "are not valid"
+  )
+})
+
+test_that("tbl_likert(label)", {
+  expect_equal(
+    df_likert |>
+      tbl_likert(label = list(recommend_friend = "I Would Recommend to a Friend")) |>
+      getElement("table_body") |>
+      getElement("label") |>
+      head(1L),
+    "I Would Recommend to a Friend"
+  )
+
+  expect_error(
+    df_likert |>
+      tbl_likert(label = list(recommend_friend = letters)),
+    "Values pass in `label` argument must be strings."
+  )
+})
+
+
+test_that("tbl_likert(digits)", {
+  # standard use works well
+  expect_snapshot(
+    df_likert |>
+      tbl_likert(digits = ~list(p = label_style_sigfig(digits = 3, scale = 100))) |>
+      as.data.frame()
+  )
+
+  # errors with bad inputs
+  expect_error(
+    df_likert |>
+      tbl_likert(digits = ~letters),
+    "Error in `digits` argument for variable"
+  )
+})
+
+test_that("tbl_likert(include)", {
+  expect_error(
+    mtcars |>
+      tbl_likert(include = mpg),
+    "All variables in the `include` argument must be"
+  )
+
+  expect_error(
+    df_likert |>
+      dplyr::mutate(
+        bad_fct = recommend_friend |> fct_expand("anoter_level")
+      ) |>
+      tbl_likert(include = everything()),
+    "All variables in the `include` argument must have the same factor levels"
+  )
+})
+
+test_that("tbl_likert(sort)", {
+  expect_snapshot(
+    df_likert |>
+      tbl_likert(sort = "descending") |>
+      as.data.frame()
+  )
+})