From b773d35954ba5c3a7dddc0ec3c113d25e104c2ca Mon Sep 17 00:00:00 2001
From: Gabe Becker <gabembecker@gmail.com>
Date: Thu, 23 Oct 2025 14:13:55 -0700
Subject: [PATCH 1/7] vignette on translating shells to layouts

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+---
+title: "Intermediate rtables - Translating Shells To Layouts"
+subtitle: Contributed by Johnson & Johnson Innovative Medicine
+date: "2025-06-17"
+author:
+- Gabriel Becker
+- Dan Hofstaedter
+output:
+    rmarkdown::html_document:
+        theme: "spacelab"
+        highlight: "kate"
+        toc: true
+        toc_float: true
+vignette: >
+  %\VignetteIndexEntry{Intermediate rtables - Translating Shells To Layouts}
+  %\VignetteEngine{knitr::rmarkdown}
+  %\VignetteEncoding{UTF-8}
+editor_options:
+  markdown:
+      wrap: 72
+  chunk_output_type: console
+---
+
+# Introduction
+
+The first - and often largest - hurdle to creating a table via
+`rtables` is translating the desired table structure (typically in the
+form of a *table shell*) into an `rtables` *layout*. We will cover
+this translation step here.
+
+## A Table Shell
+
+Table shells can come in various forms. We will begin with a table
+shell which is essentially the entire table with desired formatting
+indicated instead of values:
+
+```{r init, echo = FALSE, results = "hidden"}
+library(rtables)
+library(dplyr)
+
+fixed_shell <- function(tt) {
+  mystr <- table_shell_str(tt)
+  regex_hits <- gregexpr("[(]N=[[:digit:]]+[)]", mystr)[[1]]
+  hit_lens <- attr(regex_hits, "match.length")
+  if (regex_hits[1] > 0) {
+    for (i in seq_along(regex_hits)) {
+      start <- regex_hits[i]
+      len <- hit_lens[i]
+      substr(mystr, start, start + len - 1) <- padstr("(N=xx)", len, just = "center")
+    }
+  }
+  cat(mystr)
+}
+
+knitr::opts_chunk$set(comment = "")
+```
+
+
+```{r, eval = TRUE, echo = FALSE, result = "asis"}
+adsl <- ex_adsl %>%
+  filter(SEX %in% c("M", "F") & RACE %in% c("ASIAN", "BLACK OR AFRICAN AMERICAN", "WHITE")) %>%
+  mutate(
+    BMEASIFL = factor(as.character(BMEASIFL),
+      levels = c("Y", "N"),
+      labels = c("Yes", "No")
+    ),
+    SEX = factor(as.character(SEX),
+      levels = c("M", "F", "UNDIFFERENTIATED", "U"),
+      labels = c("Male", "Female", "Undifferentiated", "Unknown")
+    ),
+    RACE = factor(as.character(RACE),
+      levels = c("ASIAN", "BLACK OR AFRICAN AMERICAN", "WHITE"),
+      labels = c("Asian", "Black", "White")
+    )
+  )
+
+
+lyt <- basic_table(
+  title = "Subject Response by Race and Sex; Treated Subjects",
+  show_colcounts = TRUE
+) %>%
+  split_cols_by("STRATA1", split_fun = keep_split_levels(only = c("A", "B"))) %>%
+  split_cols_by("ARM", split_fun = keep_split_levels(only = c("A: Drug X", "B: Placebo"))) %>%
+  analyze("BMEASIFL", afun = counts_wpcts, var_labels = "All Patients", show_labels = "visible") %>%
+  split_rows_by(
+    var = "RACE",
+    label_pos = "topleft",
+    split_fun = keep_split_levels(only = c("Asian", "Black", "White"))
+  ) %>%
+  split_rows_by(
+    var = "SEX",
+    label_pos = "topleft",
+    split_fun = keep_split_levels(only = c("Male", "Female"))
+  ) %>%
+  summarize_row_groups(
+    var = "SEX",
+    format = "xx"
+  ) %>%
+  analyze(
+    vars = "BMEASIFL",
+    afun = counts_wpcts
+  )
+
+result <- build_table(lyt, adsl)
+fixed_shell(result)
+```
+
+We will use this shell to illustrate the translation process to an
+rtables layout, and thus ultimately a table output.
+
+## A *Brief* Review Of `rtables` Layouts
+
+For an in-depth discussion of how constructing a layout works we refer
+the reader to other documentation. That said, there are a couple
+things to remember as we consider translating shells into layouts:
+
+1. Individual rows are declared by `analyze*` calls
+2. Individual columns are the result of column faceting
+3. New faceting will be nested within existing faceting in the same dimension (row/col) by default
+4. All row faceting structures must be terminated with at least one analysis (`analyze`)
+5. Row faceting which occurs directly after an `analyze` will *not* be nested
+
+With those in mind, we will now discuss how to translate shells into layouts.
+
+# Translating
+
+There are three aspects to a shell that we must translate:
+
+1. Column faceting structure
+2. Row faceting structure
+3. Cell contents
+   - Marginal content for row facet structure
+   - Individual facet content
+ 
+We will explore each portion of the translation process separately.
+
+## Translating Column Structure
+
+Our first task, translating column structure, revolves around
+identifying faceting in the column dimension of a shell or desired
+table.
+
+Our shell gives us the following to indicate column structure:
+
+```{r, eval = TRUE, echo = FALSE, result="asis"}
+fixed_shell(result[0, ])
+```
+
+The easiest way to identify faceting is to look at column- or
+row-labels and determine the scope (i.e., the set of individual
+columns or rows) they apply to.
+
+For example, we see that the `"A"` column label applies to a group of
+multiple columns each of which represent an individual arm:
+
+```{r}
+fixed_shell(result[0, c("A", "*")])
+```
+
+Thus we have strata faceting with arm faceting nested within it.
+
+Faceting most commonly represents partitioning the data being
+tabulated by the values of a categorical variable, though `rtables`
+supports a generalized concept of faceting where the data group can
+overlap and need not be exhaustive.
+
+For our table, the faceting is nested faceting by the `"STRATA1"`, and
+`"ARM"` variables. We achieve this by repeated calls to
+`split_cols_by` (with the default `nested = TRUE`), with the call declaring
+the outermost faceting first:
+
+
+```{r}
+lyt_cols <- basic_table() |>
+  split_cols_by("STRATA1", split_fun = keep_split_levels(only = c("A", "B"))) %>%
+  split_cols_by("ARM", split_fun = keep_split_levels(only = c("A: Drug X", "B: Placebo")))
+
+build_table(lyt_cols, adsl)
+```
+
+This is almost correct. To fully achieve our shell we need the column
+counts to show up, which we do via the `show_colcounts` argument in
+the relevant `split_cols_by` call:
+
+```{r}
+lyt_cols <- basic_table() |>
+  split_cols_by("STRATA1", split_fun = keep_split_levels(only = c("A", "B"))) %>%
+  split_cols_by("ARM",
+    split_fun = keep_split_levels(only = c("A: Drug X", "B: Placebo")),
+    show_colcounts = TRUE
+  )
+
+build_table(lyt_cols, adsl)
+```
+
+
+This is a relatively straightforward column structure. We will cover
+more complex ones later. Nevertheless we have translated our shell's
+column space into `rtables` layouting instructions.
+
+
+## Translating Row Structure
+
+Moving to the second aspect of translation, we will now translate the
+row structure of our shell. Interpreting row structure is similar to
+interpreting column structure with the caveat that individual rows do
+not come from faceting, but rather from analysis (which is in charge
+of populating the contents of the table's primary, non-marginal
+cells).
+
+Our row structure is slightly less trivial than our column
+structure. We can see two sections in our shell, one that displays the
+response (`"BMEASIFL"`) of all patients collectively (by the column
+structure):
+
+
+```{r, echo = FALSE}
+fixed_shell(tt_at_path(result, "BMEASIFL"))
+```
+
+and one that subsets the patients before displaying the response
+within each subset, and with some marginal rows for context.
+
+```{r, echo = FALSE}
+fixed_shell(tt_at_path(result, "RACE"))
+```
+
+Because none of the labels or cell-values from the all patients
+portion of the table apply directly to the subset analysis portion -
+and vice versa - we can treat these separately.
+
+In point of fact, the first portion does not require any structure
+beyond an analysis of the `"BMEASIFL" variable with a label, so we can
+leave that for the third translation step.
+
+We can illustrate this using a dummy analyze as follows:
+
+```{r}
+dummy_afun <- function(x, ...) in_rows("Analysis" = "-")
+lyt_a <- basic_table() |>
+  analyze("BMEASIFL",
+    afun = dummy_afun,
+    var_labels = "All Patients",
+    show_labels = "visible"
+  )
+
+build_table(lyt_a, adsl)
+```
+
+While we do not have the individual rows we desired, as that is left
+to step 3 of translation, we can see that we have successfully created
+the first portion of the row *structure*.
+
+Note that in most tables the column and row structure are orthogonal
+and so we do not need to worry about columns when we are translating
+the row structure.
+
+Also note we *could* say that there is a facet there which contains all the
+patients and has the name/label `"All Patients"`; this would result in
+an equivalent table from an output perspective but there isn't really
+any benefit to the added layouting instructions that would be
+required, so we will not do so here.
+
+The second portion of the table contains labels and rows which *do*
+apply to multiple individual rows.
+
+We see that the `"Asian"` label, for example, applies across the
+corresponding `"Male"` and `"Female"` labels/marginal rows, each of
+which in turn applies to a group of individual rows (`"Yes"`, and
+`"No"`).
+
+Thus we can recreate this section via nested faceting, this time with 
+
+```{r}
+lyt_b <- basic_table() |>
+  split_rows_by("RACE") |>
+  split_rows_by("SEX") |>
+  analyze("BMEASIFL", afun = dummy_afun)
+
+head(build_table(lyt_b, adsl), 30)
+```
+
+We are almost there, but we see extra `"SEX"` values that weren't in
+our shell. We can prevent this with the `keep_split_levels` function
+provided by `rtables`:
+
+```{r}
+lyt_b2 <- basic_table() |>
+  split_rows_by("RACE") |>
+  split_rows_by("SEX", split_fun = keep_split_levels(only = c("Male", "Female"))) |>
+  analyze("BMEASIFL", afun = dummy_afun)
+
+
+build_table(lyt_b2, adsl)
+```
+
+Finally, we can combine the two sections by simply combining the relevant layout instructions:
+
+
+```{r}
+lyt_b3 <- basic_table() |>
+  analyze("BMEASIFL",
+    afun = dummy_afun,
+    var_labels = "All Patients",
+    show_labels = "visible"
+  ) |>
+  split_rows_by("RACE") |>
+  split_rows_by("SEX", split_fun = keep_split_levels(only = c("Male", "Female"))) |>
+  analyze("BMEASIFL", afun = dummy_afun)
+
+build_table(lyt_b3, adsl)
+```
+
+Note here that row split instructions which directly follow an
+`analyze` call will automatically be non-nested, so we do not need to
+specify `nested = FALSE` in the `"RACE"` split, though doing so would
+not harm anything.
+
+We can convince ourselves that treating the column and row structure
+separately by combining the layouting instructions for both to receive
+something equivalent in structure (i.e., up individual rows and marginal cell contents) to our
+shell:
+
+
+```{r}
+lyt_struct <- basic_table() |>
+  split_cols_by("STRATA1", split_fun = keep_split_levels(only = c("A", "B"))) |>
+  split_cols_by("ARM",
+    split_fun = keep_split_levels(only = c("A: Drug X", "B: Placebo")),
+    show_colcounts = TRUE
+  ) |>
+  analyze("BMEASIFL",
+    afun = dummy_afun,
+    var_labels = "All Patients",
+    show_labels = "visible"
+  ) |>
+  split_rows_by("RACE") |>
+  split_rows_by("SEX", split_fun = keep_split_levels(only = c("Male", "Female"))) |>
+  analyze("BMEASIFL", afun = dummy_afun)
+
+build_table(lyt_struct, adsl)
+```
+
+We can see that the marginal cells for `"Male"` and `"Female"` within
+each race are not present, but we will handle those in the third
+translation step.
+
+
+## Translating Cell Contents
+
+Finally, we will finish our translation with the third step:
+translating cell contents.
+
+Tables can contain up to two types of rows with non-empty cells as
+reckoned by the `rtables` conceptual model: individual analysis rows,
+and marginal group summary rows (called *content* rows by the
+`rtables` internals).
+
+Analysis rows are declared via `analyze` during layout construction;
+an analysis function (the `afun` argument) specifying how *all cells
+within a single facet pane should be simultaneously created*.
+
+We see in our shell that we want two rows whenever we analyze
+`BMEASIFL` response: one for `"Yes"` and one for `"No"`.
+
+Most analysis functions provided by `rtables` or extensions like
+`tern` or `junco` will automatically generate multiple rows when
+analyzing a categorical variable (i.e., factor):
+
+
+```{r}
+rw_lyt <- basic_table() |>
+  analyze("BMEASIFL",
+    var_labels = "All Patients",
+    show_labels = "visible"
+  )
+
+build_table(rw_lyt, adsl)
+```
+
+Further, recall that the faceting does the work of identifying subsets
+and applying our analyses within those facets/subsets
+automatically. Thus by applying the *structural* layout instructions
+we translated above, we get something that is getting pretty close to
+our desired table:
+
+
+```{r}
+rw_lyt_struct <- basic_table() |>
+  split_cols_by("STRATA1", split_fun = keep_split_levels(only = c("A", "B"))) |>
+  split_cols_by("ARM",
+    split_fun = keep_split_levels(only = c("A: Drug X", "B: Placebo")),
+    show_colcounts = TRUE
+  ) |>
+  analyze("BMEASIFL",
+    var_labels = "All Patients",
+    show_labels = "visible"
+  ) |>
+  split_rows_by("RACE") |>
+  split_rows_by("SEX", split_fun = keep_split_levels(only = c("Male", "Female"))) |>
+  analyze("BMEASIFL")
+
+build_table(rw_lyt_struct, adsl)
+```
+
+Two aspects remain before we have matched our desired shell: our
+marginal counts in the the individual gender rows within each race are
+missing, and our analysis rows contain only counts rather than
+matching the desired `"xx (xx.x%)"` format of count and percent.
+
+`rtables` provides a (*very*) simple afun to calculate count percent
+values (`counts_wpcts`) which we can use for illustration purposes
+here.  We will see later that it is not flexible enough to meet a
+study team's full set of needs and more complex afuns will be used in
+practice in production.
+
+```{r}
+rw_lyt_structb <- basic_table() |>
+  split_cols_by("STRATA1", split_fun = keep_split_levels(only = c("A", "B"))) |>
+  split_cols_by("ARM",
+    split_fun = keep_split_levels(only = c("A: Drug X", "B: Placebo")),
+    show_colcounts = TRUE
+  ) |>
+  analyze("BMEASIFL",
+    afun = counts_wpcts,
+    var_labels = "All Patients",
+    show_labels = "visible"
+  ) |>
+  split_rows_by("RACE") |>
+  split_rows_by("SEX", split_fun = keep_split_levels(only = c("Male", "Female"))) |>
+  analyze("BMEASIFL", afun = counts_wpcts)
+
+build_table(rw_lyt_structb, adsl)
+```
+
+Now, all we need is the marginal gender counts. We do this by adding
+`summarize_row_groups` *directly after* the relevant row faceting
+(`split_rows_by`) instruction in the layout. This function can accept
+a fully custom function (the `cfun` argument), but for our purposes,
+we can control whether the percent is included in the default group
+summary with the `format` argument.
+
+```{r}
+lyt_final <- basic_table() |>
+  split_cols_by("STRATA1", split_fun = keep_split_levels(only = c("A", "B"))) |>
+  split_cols_by("ARM",
+    split_fun = keep_split_levels(only = c("A: Drug X", "B: Placebo")),
+    show_colcounts = TRUE
+  ) |>
+  analyze("BMEASIFL",
+    afun = counts_wpcts,
+    var_labels = "All Patients",
+    show_labels = "visible"
+  ) |>
+  split_rows_by("RACE") |>
+  split_rows_by("SEX", split_fun = keep_split_levels(only = c("Male", "Female"))) |>
+  summarize_row_groups(format = "xx") |>
+  analyze("BMEASIFL", afun = counts_wpcts)
+
+build_table(lyt_final, adsl)
+```
+
+Thus, we have fully translated our shell into an `rtables` declarative
+layout and realized our desired table output.
+
+In the remainder of this vignette we will walk through a number of
+shells with more complex structural elements and how to translate them
+into `rtables` layouts.
+
+# Spanning Column Headers
+
+Some shells will call for spanning labels in column space which do not
+directly reflect a categorical variable in the raw data, but rather
+represent groups of levels in a variable, e.g., trial arms.
+
+For example, we might have the following column structure in a shell:
+
+
+```{r, echo = FALSE}
+span_map <- data.frame(
+  ARM = c("A: Drug X", "B: Placebo", "C: Combination"),
+  span_label = c("Active Treatment", " ", "Active Treatment")
+)
+
+lyt_span <- basic_table() |>
+  split_cols_by("span_label", split_fun = trim_levels_to_map(span_map)) |>
+  split_cols_by("ARM", show_colcounts = TRUE)
+
+adsl2 <- adsl
+adsl2$span_label <- "Active Treatment"
+adsl2$span_label[adsl2$ARM == "B: Placebo"] <- " "
+
+tbl_colspans <- build_table(lyt_span, adsl2)
+fixed_shell(tbl_colspans)
+```
+
+Here we see the "Active Treatment" label spanning arms A and C, while
+no label appears above the column for arm B. There are a couple things
+to decode here that will collapse this column structure into a nested
+faceting structure as we saw above.
+
+Most importantly, while uneven splitting *is* possible with `rtables`,
+including in column space, we can get our desired output by allowing
+the B arm to have an invisible spanning label which is simply a single
+space (`" "`). Viewing the structure this way, we can see that we have
+two levels of faceting, one which splits between so called active
+treatments and the remaining arms, and within that, we facet on
+individual arm.
+
+This brings us to our second issue: we don't have a variable for
+active vs non-active treatments. There are a few ways to address this,
+but the most user-friendly way is simply to create one as a
+preprocessing step on the data before we make our table:
+
+```{r}
+adsl_forspans <- adsl
+adsl_forspans$span_label <- "Active Treatment"
+adsl_forspans$span_label[adsl_forspans$ARM == "B: Placebo"] <- " "
+
+qtable(adsl_forspans, "ARM", "span_label")
+```
+
+With that we can build a table with the desired nested splitting:
+
+```{r}
+lyt_cspan <- basic_table() |>
+  split_cols_by("span_label") |>
+  split_cols_by("ARM", show_colcounts = TRUE)
+
+build_table(lyt_cspan, adsl_forspans)
+```
+
+So we are getting close, but our individual arm columns are not only
+showing up under their correct spanning label (though we see that the
+*data* are being siphoned under the correct labels by the column
+counts).
+
+This type of non-full-factorial nesting is common; we often only want
+facets that *make logical sense* within a nested faceting structure,
+while wanting to omit any that don't (e.g., in our table, the Active
+Treatment - Placebo facet).
+
+`rtables` provides multiple ways to declare this behavior in the form
+of both full *split functions* and *split function behavior building
+blocks*, the latter being for use within `make_split_fun`. For now, we
+will use a built-in full split function as we will be covering
+`make_split_fun` in a different vignette.
+
+Our two options for split functions are `trim_levels_in_group` and
+`trim_levels_to_map`; the former is empirical and will keep all
+combinations which are *observed in the data*, omitting any that
+aren't. The latter requires us to provide a map of all combinations to
+be displayed, but is more robust to sparse data (e.g., a data snapshot
+from an in-flight trial) and allows for displaying zero counts for
+unobserved but desired combinations.
+
+Other than being empirical and declarative, respectively,
+`trim_levels_in_group` and `trim_levels_to_map` behave similarly: when
+used while splitting on a variable (the "outer variable"), the
+observations and factor levels of of another ("inner") variable are
+restricted independently within each facet for the outer variable.
+
+In our case, our outer variable is `"span_label"`, while our inner
+variable would be `"ARM"`. Thus we want to restrict the levels of
+`"ARM"` within each facet of `"span_label"`. For our toy example here,
+the two split functions will be equivalent, but we will use
+`trim_levels_to_map` as it is more robust and appropriate for more
+cases of production use.
+
+Thus we need to create our map, a `data.frame` that contains the two
+variables with each desired combination as a separate row:
+
+```{R}
+span_label_map <- tribble(
+  ~span_label, ~ARM,
+  "Active Treatment", "A: Drug X",
+  "Active Treatment", "C: Combination",
+  " ", "B: Placebo",
+)
+
+lyt_cspan_final <- basic_table() |>
+  split_cols_by("span_label",
+    split_fun = trim_levels_to_map(span_label_map)
+  ) |>
+  split_cols_by("ARM", show_colcounts = TRUE)
+
+build_table(lyt_cspan_final, adsl_forspans)
+```
+
+Thus we have again achieved a "table" matching our desired shell. We
+can consider only the column structure because in this case as
+previously the column structure, row structure, and analysis are all
+orthogonal. We will see an example where that isn't fully the case below
+
+**Note:** in the general case, the level map used in
+`trim_levels_to_map` will be a function of the data dictionaries for
+the relevant variables within your study, thus for combinations of
+actual variables these maps should not require manual construction as
+we did above.
+
+# Heterogeneous Column Structures (e.g., Risk Difference Columns)
+
+In our previous examples, the column structure was simple nested
+faceting, both in the case of faceting on two variables from the data,
+and in the case we wanted spanning labels.
+
+While this simple nesting structure is relatively common,
+particularly for column structure, it does not fit the shells for all
+tables we might need to create. One example of this is risk difference
+columns, as found in modern FDA guidance for Adverse Event (AE)
+tables.
+
+In this section we will translate a shell with both spanning headers
+and risk difference columns into a layout. To avoid subtleties about
+counting we will analyze the `BMRKR2` variable in our synthetic
+`ADSL` dataset rather than going for a realistic AE table. These
+counting issues and realistic AE tables will be addressed elsewhere in
+this series of vignettes.
+
+## Risk Difference Columns
+
+Many tables call for "risk difference", or comparison columns, in
+addition to those used for the primary counts. When combined with
+spanning labels, the column structure of our shell would look
+something like:
+
+```{r, echo = FALSE}
+adsl2$rr_header <- "Risk Differences"
+adsl2$rr_label <- paste(adsl2$ARM, "vs B: Placebo")
+lyt_rr <- basic_table() |>
+  split_cols_by("span_label", split_fun = trim_levels_to_map(span_map)) |>
+  split_cols_by("ARM", show_colcounts = TRUE) |>
+  split_cols_by("rr_header", nested = FALSE) |>
+  split_cols_by("ARM", labels_var = "rr_label", split_fun = remove_split_levels("B: Placebo"))
+
+
+tbl_rr_shell <- build_table(lyt_rr, adsl2)
+fixed_shell(tbl_rr_shell)
+```
+
+We see that the first portion of the column structure is the same, but
+we now have the risk difference structure in addition. There are a
+number of different ways to model risk difference columns but we will
+do so as a separate nested substructure. Thus as we did with the
+"Active Treatment" spanning label, we will create and then facet on a
+variable that gives us the "Risk Differences" label.
+
+We can build up this substructure separately and then combine it with
+the structure we created above to match the full shell.
+
+
+```{r}
+adsl_rr <- adsl_forspans
+adsl_rr$rr_header <- "Risk Differences"
+
+lyt_only_rr <- basic_table() |>
+  split_cols_by("rr_header") |>
+  split_cols_by("ARM")
+
+build_table(lyt_only_rr, adsl_rr)
+```
+
+This is getting close there are two issues: first, we don't want a
+placebo column (which would nonsensically compare placebo against
+itself), and the labels are simply the individual arms rather than the
+pair of arms being compared as in our shell.
+
+We can restrict the facets generated using the `remove_split_levels`
+(or sibling `keep_split_levels`) split function provided by
+`rtables`. In addition the `split_*_by` functions accept the
+`labels_var` argument which specifies an additional variable which
+should be used for the *labels* (not names) of the facets
+generated. With preprocessing to create such a variable, and combining
+these two approaches, we can achieve the risk difference structure:
+
+```{r}
+adsl_rr$rr_label <- paste(adsl_rr$ARM, "vs B: Placebo")
+
+lyt_only_rr2 <- basic_table() |>
+  split_cols_by("rr_header") |>
+  split_cols_by("ARM",
+    split_fun = remove_split_levels("B: Placebo"),
+    labels_var = "rr_label"
+  )
+
+build_table(lyt_only_rr2, adsl_rr)
+```
+
+To combine our two sections of column structure, we simply combine the
+sets of layouting instructions and add `nested = FALSE` to our split
+on `"rr_header"`:
+
+
+```{r}
+lyt_rr_cols <- basic_table() |>
+  split_cols_by("span_label",
+    split_fun = trim_levels_to_map(span_label_map)
+  ) |>
+  split_cols_by("ARM", show_colcounts = TRUE) |>
+  split_cols_by("rr_header", nested = FALSE) |>
+  split_cols_by("ARM",
+    split_fun = remove_split_levels("B: Placebo"),
+    labels_var = "rr_label"
+  )
+
+build_table(lyt_rr_cols, adsl_rr)
+```
+
+Note that because we used `show_colcounts` in our `split_cols_by` call
+for `"ARM"`, rather than in `build_table`, we have counts for our main
+arm columns but not for our comparison columns, as desired.
+
+One caveat here, however, is that we will need a more sophisticated
+analysis function because its behavior is no longer independent of
+which facet it is in: it might generate e.g., counts for the primary
+arm columns and then confidence intervals for our risk difference
+columns.
+
+Typically trial teams will be using pre-existing analysis functions
+for this, but we will illustrate these can be constructed now.
+
+## Column-structure Aware Analysis Functions
+
+Our analysis function needs two "modes": the primary arm column mode
+and the risk difference mode, and it needs to be able to distinguish
+between them.
+
+Analysis (and content, i.e., row group summary) functions can accept
+the optional `.spl_context` argument to receive information where in
+the faceting structure the facet they are currently populating is. We
+will leave a detailed discussion of the full contents of the split
+context to other documentation and simply use the portions we need
+here.
+
+In particular, we will use the `cur_col_id` column of `.spl_context`
+to determine which section of the column structure we are under. Note
+that due to the vagaries of the current implementation, this is
+constructed of the *labels* for the column facets rather than their
+names. This is the split/value pairs of each column split in order
+concatenated together, so it suffices to define
+
+```{r}
+in_risk_diff <- function(spl_context) grepl("Risk Differences", spl_context$cur_col_id[1])
+```
+
+
+For simplicity, we will not worry about *calculating* risk differences
+here, and simply write an analysis function that emits something
+different to show that it can tell it is in "risk difference mode".
+
+Thus a very simplistic afun is as follows:
+
+```{r}
+rr_afun <- function(x, .N_col, .spl_context) {
+  xtbl <- table(x)
+  if (in_risk_diff(.spl_context)) {
+    armlabel <- tail(.spl_context$cur_col_split_val[[1]], 1) # last split value, ie arm
+    armletter <- substr(armlabel, 1, 1)
+    vals <- as.list(rep(paste(armletter, "vs B"), length(xtbl)))
+    fmts <- rep("xx", length(xtbl))
+  } else {
+    vals <- lapply(xtbl, function(x) x * c(1, 1 / .N_col)) ## count and pct
+    fmts <- rep("xx.x (xx.x%)", length(xtbl))
+  }
+  names(vals) <- names(xtbl)
+  names(fmts) <- names(vals)
+  in_rows(.list = vals, .formats = fmts)
+}
+```
+
+With this we can create a table. We will analyze `BMRKR2` (biomarker
+2) for the sake of brevity. This is an oversimplifaction, as typically
+this would be, e.g., `AEDECOD` in an `adae` dataset, but this requires
+more sophisticated calculation of counts and/or percents that is
+important but not germane to this specific issue.
+
+```{r}
+lyt_rr_full <- basic_table() |>
+  split_cols_by("span_label",
+    split_fun = trim_levels_to_map(span_label_map)
+  ) |>
+  split_cols_by("ARM", show_colcounts = TRUE) |>
+  split_cols_by("rr_header", nested = FALSE) |>
+  split_cols_by("ARM",
+    split_fun = remove_split_levels("B: Placebo"),
+    labels_var = "rr_label"
+  ) |>
+  analyze("BMRKR2", afun = rr_afun)
+
+build_table(lyt_rr_full, adsl_rr)
+```
+
+The blank space above the column counts is a known issue which we
+expect to be resolved in a future release due to the fact that the
+header construction/wrapping behavior is not accounting for the fact
+that the two sections of the column structure are independent.
+
+Note that while our analysis function was dependent on where in the
+*column* structure we are, it remains independent of where in the
+*row* faceting structure we are. Thus we can use our analysis function
+within row faceting without changes:
+
+
+```{r}
+lyt_rr_full2 <- basic_table() |>
+  split_cols_by("span_label",
+    split_fun = trim_levels_to_map(span_label_map)
+  ) |>
+  split_cols_by("ARM", show_colcounts = TRUE) |>
+  split_cols_by("rr_header", nested = FALSE) |>
+  split_cols_by("ARM",
+    split_fun = remove_split_levels("B: Placebo"),
+    labels_var = "rr_label"
+  ) |>
+  split_rows_by("STRATA1") |>
+  split_rows_by("SEX", split_fun = keep_split_levels(c("Female", "Male"))) |>
+  analyze("BMRKR2", afun = rr_afun)
+
+tbl <- build_table(lyt_rr_full2, adsl_rr)
+
+cwidths <- propose_column_widths(tbl)
+cwidths[cwidths > 15] <- 15
+cat(export_as_txt(tbl, colwidths = cwidths)) ## for wrapping
+```
+
+A more complete exploration of creating production ready analysis
+functions will be presented elsewhere in this vignette series.
+
+# Mixed Nesting Levels
+
+In practice, the row structure in most shells can be translated to a
+layout using combinations of the methods shown above. Some shells,
+however, essentially call for group summaries for all levels of a
+categorical variable, but additionally call for analysis within those
+groups *for only some levels of the variable*.
+
+In clinical trial outputs we have seen this most commonly in
+disposition tables, the shells of which might look something like:
+
+```{r, echo = FALSE}
+simple_two_tier_init <- function(df, .var, .N_col, inner_var, drill_down_levs) {
+  outer_tbl <- table(df[[.var]])
+
+  cells <- lapply(
+    names(outer_tbl),
+    function(nm) {
+      cont_cell <- rcell(outer_tbl[nm] * c(1, 1 / .N_col), format = "xx (xx.x%)")
+      if (nm %in% drill_down_levs) {
+        inner_tbl <- table(df[[inner_var]])
+        detail_cells <- lapply(
+          names(inner_tbl),
+          function(innm) rcell(inner_tbl[innm] * c(1, 1 / .N_col), format = "xx (xx.x%)", indent_mod = 1L)
+        )
+        names(detail_cells) <- names(inner_tbl)
+      } else {
+        detail_cells <- NULL
+      }
+      c(setNames(list(cont_cell), nm), detail_cells)
+    }
+  )
+
+  in_rows(.list = unlist(cells, recursive = FALSE))
+}
+
+two_tier_shell_lyt <- basic_table() |>
+  split_cols_by("span_label",
+    split_fun = trim_levels_to_map(span_label_map)
+  ) |>
+  split_cols_by("ARM", show_colcounts = TRUE) |>
+  split_rows_by("RACE", split_fun = keep_split_levels(c("Asian", "Black"))) |>
+  analyze("EOSSTT",
+    afun = simple_two_tier_init,
+    extra_args = list(
+      inner_var = "DCSREAS",
+      drill_down_levs = "DISCONTINUED"
+    )
+  )
+
+two_tier_shell <- build_table(two_tier_shell_lyt, adsl_rr) ## don't need the rr bits
+fixed_shell(two_tier_shell)
+```
+
+In this shell, the `COMPLETED`, `DISCONTINUED` and `ONGOING` rows are
+siblings (derived from the `EOSSTT` variable), however only the
+`DISCONTINUED` row acts as a group summary row for a facet containing
+further analysis; the other two essentially act as individual rows.
+
+This type of structure where individual analysis rows and facets/group
+summary rows are direct siblings is not currently supported by the
+`rtables` layouting and tabulation engines, and is *somewhat*
+supported when created via, e.g., trimming rows of a created table.
+
+The above said, we can arrive at a table which renders as desired
+using the *two-tier analysis function* strategy. A
+[vignette](variable_nesting_depth.html) discussing this is in detail
+is included with `rtables`; for completeness of the training
+curriculum we will briefly reiterate here.
+
+The key to the two-tier analysis function strategy is to generate both
+levels of row in the same analysis function and simply use indent
+modifiers to differentiate them.
+
+Below is a simple `afun` that implements this strategy. For the
+purposes of this lesson readers can ignore the details of what this
+function does if desired; analysis function design and implementation
+will be covered in another vignette in the advanced section.
+
+
+```{R}
+simple_two_tier <- function(df, .var, .N_col, inner_var, drill_down_levs) {
+  ## group EOSSTT counts
+  outer_tbl <- table(df[[.var]])
+
+  cells <- lapply(
+    names(outer_tbl),
+    function(nm) {
+      ## simulated group summary rows
+      cont_cell <- rcell(outer_tbl[nm] * c(1, 1 / .N_col),
+        format = "xx (xx.x%)"
+      )
+      if (nm %in% drill_down_levs) {
+        ## detail (DCSREAS) counts
+        inner_tbl <- table(df[[inner_var]])
+        ## note indent_mod
+        detail_cells <- lapply(
+          names(inner_tbl),
+          function(innm) {
+            rcell(inner_tbl[innm] * c(1, 1 / .N_col),
+              format = "xx (xx.x%)",
+              ## appearance of "detail drill-down"
+              indent_mod = 1L
+            )
+          }
+        )
+        names(detail_cells) <- names(inner_tbl)
+      } else {
+        detail_cells <- NULL
+      }
+      c(setNames(list(cont_cell), nm), detail_cells)
+    }
+  )
+
+  in_rows(.list = unlist(cells, recursive = FALSE))
+}
+
+lyt_two_tier <- basic_table() |>
+  analyze("EOSSTT",
+    afun = simple_two_tier,
+    extra_args = list(inner_var = "DCSREAS", drill_down_levs = "DISCONTINUED")
+  )
+
+build_table(lyt_two_tier, adsl_rr)
+```
+
+As in other cases, we can add the row- and column- structure
+orthogonally (provided the analysis behavior is truly orthogonal to
+the faceting, as it is in this shell):
+
+```{r}
+lyt_two_tier_full <- basic_table() |>
+  split_cols_by("span_label",
+    split_fun = trim_levels_to_map(span_label_map)
+  ) |>
+  split_cols_by("ARM", show_colcounts = TRUE) |>
+  split_rows_by("RACE", split_fun = keep_split_levels(c("Asian", "Black"))) |>
+  analyze("EOSSTT",
+    afun = simple_two_tier,
+    extra_args = list(inner_var = "DCSREAS", drill_down_levs = "DISCONTINUED")
+  )
+
+build_table(lyt_two_tier_full, adsl_rr)
+```
+
+Thus we have created our desired output.

From f98cad94d24519fec166e31e638d1c8a74145085 Mon Sep 17 00:00:00 2001
From: github-actions <41898282+github-actions[bot]@users.noreply.github.com>
Date: Thu, 23 Oct 2025 21:17:56 +0000
Subject: [PATCH 2/7] [skip roxygen] [skip vbump] Roxygen Man Pages Auto Update

---
 DESCRIPTION                          | 2 +-
 man/add_overall_level.Rd             | 2 +-
 man/analyze_colvars.Rd               | 2 +-
 man/append_topleft.Rd                | 2 +-
 man/cell_values.Rd                   | 2 +-
 man/gfc.Rd                           | 2 +-
 man/int_methods.Rd                   | 2 +-
 man/matrix_form-VTableTree-method.Rd | 2 +-
 man/row_paths_summary.Rd             | 2 +-
 man/split_cols_by.Rd                 | 2 +-
 man/split_cols_by_multivar.Rd        | 2 +-
 man/split_rows_by.Rd                 | 2 +-
 man/table_shell.Rd                   | 2 +-
 man/table_structure.Rd               | 2 +-
 man/tostring.Rd                      | 2 +-
 man/varcuts.Rd                       | 2 +-
 16 files changed, 16 insertions(+), 16 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index d289f6d5c7..99ec219a4b 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -71,7 +71,7 @@ Encoding: UTF-8
 Language: en-US
 LazyData: true
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.2
+RoxygenNote: 7.3.3
 Collate:
     '00tabletrees.R'
     'Viewer.R'
diff --git a/man/add_overall_level.Rd b/man/add_overall_level.Rd
index ce22160cab..a388e24988 100644
--- a/man/add_overall_level.Rd
+++ b/man/add_overall_level.Rd
@@ -78,7 +78,7 @@ lyt2
 tbl2 <- build_table(lyt2, DM)
 tbl2
 
-\dontshow{if (require(tibble)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(tibble)) withAutoprint(\{ # examplesIf}
 
 library(tibble)
 combodf <- tribble(
diff --git a/man/analyze_colvars.Rd b/man/analyze_colvars.Rd
index d30bf48390..af9a73de94 100644
--- a/man/analyze_colvars.Rd
+++ b/man/analyze_colvars.Rd
@@ -57,7 +57,7 @@ A \code{PreDataTableLayouts} object suitable for passing to further layouting fu
 Generate rows analyzing different variables across columns
 }
 \examples{
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr)
 
 ANL <- DM \%>\% mutate(value = rnorm(n()), pctdiff = runif(n()))
diff --git a/man/append_topleft.Rd b/man/append_topleft.Rd
index 0db6195067..90f61aa060 100644
--- a/man/append_topleft.Rd
+++ b/man/append_topleft.Rd
@@ -31,7 +31,7 @@ the actual splitting keywords. This may change in the future.
 This function is experimental, its name and the details of its behavior are subject to change in future versions.
 }
 \examples{
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr)
 
 DM2 <- DM \%>\% mutate(RACE = factor(RACE), SEX = factor(SEX))
diff --git a/man/cell_values.Rd b/man/cell_values.Rd
index 1082f52f3f..55151dceb5 100644
--- a/man/cell_values.Rd
+++ b/man/cell_values.Rd
@@ -47,7 +47,7 @@ lyt <- basic_table() \%>\%
   split_rows_by("STRATA1") \%>\%
   analyze("AGE")
 
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr) ## for mutate
 tbl <- build_table(lyt, DM \%>\%
   mutate(SEX = droplevels(SEX), RACE = droplevels(RACE)))
diff --git a/man/gfc.Rd b/man/gfc.Rd
index 19c01c1155..70b2dea16d 100644
--- a/man/gfc.Rd
+++ b/man/gfc.Rd
@@ -50,7 +50,7 @@ The formatted print-strings for all (body) cells in \code{obj}.
 Get formatted cells
 }
 \examples{
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr)
 
 iris2 <- iris \%>\%
diff --git a/man/int_methods.Rd b/man/int_methods.Rd
index e19c04cbfd..0a662b3de7 100644
--- a/man/int_methods.Rd
+++ b/man/int_methods.Rd
@@ -1302,7 +1302,7 @@ These are internal methods that are documented only to satisfy \verb{R CMD check
 attention to this documentation.
 }
 \examples{
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr)
 
 iris2 <- iris \%>\%
diff --git a/man/matrix_form-VTableTree-method.Rd b/man/matrix_form-VTableTree-method.Rd
index 27a488bb84..20bfd790ab 100644
--- a/man/matrix_form-VTableTree-method.Rd
+++ b/man/matrix_form-VTableTree-method.Rd
@@ -60,7 +60,7 @@ values are determined using \code{get_formatted_cells}. (Column labels are calcu
 function.
 }
 \examples{
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr)
 
 iris2 <- iris \%>\%
diff --git a/man/row_paths_summary.Rd b/man/row_paths_summary.Rd
index 5a2ec27fc3..1835aea04a 100644
--- a/man/row_paths_summary.Rd
+++ b/man/row_paths_summary.Rd
@@ -19,7 +19,7 @@ A data frame summarizing the row- or column-structure of \code{x}.
 Print row/column paths summary
 }
 \examples{
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 ex_adsl_MF <- ex_adsl \%>\% dplyr::filter(SEX \%in\% c("M", "F"))
 
 lyt <- basic_table() \%>\%
diff --git a/man/split_cols_by.Rd b/man/split_cols_by.Rd
index b36e31bfb2..30c2c97e25 100644
--- a/man/split_cols_by.Rd
+++ b/man/split_cols_by.Rd
@@ -120,7 +120,7 @@ lyt2
 tbl2 <- build_table(lyt2, DM)
 tbl2
 
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 # By default sequentially adding layouts results in nesting
 library(dplyr)
 
diff --git a/man/split_cols_by_multivar.Rd b/man/split_cols_by_multivar.Rd
index 75fd2a752e..7aca062757 100644
--- a/man/split_cols_by_multivar.Rd
+++ b/man/split_cols_by_multivar.Rd
@@ -53,7 +53,7 @@ When we need columns to reflect different variables entirely, rather than differ
 variable, we use \code{split_cols_by_multivar}.
 }
 \examples{
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr)
 
 ANL <- DM \%>\% mutate(value = rnorm(n()), pctdiff = runif(n()))
diff --git a/man/split_rows_by.Rd b/man/split_rows_by.Rd
index 232c46bdbd..70919aee62 100644
--- a/man/split_rows_by.Rd
+++ b/man/split_rows_by.Rd
@@ -146,7 +146,7 @@ lyt3 <- basic_table() \%>\%
 
 lyt3
 
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr)
 
 DM2 <- DM \%>\%
diff --git a/man/table_shell.Rd b/man/table_shell.Rd
index 17734b69c7..bd310700c5 100644
--- a/man/table_shell.Rd
+++ b/man/table_shell.Rd
@@ -54,7 +54,7 @@ A table shell is a rendering of the table which maintains the structure, but doe
 displaying the formatting instructions for each cell.
 }
 \examples{
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr)
 
 iris2 <- iris \%>\%
diff --git a/man/table_structure.Rd b/man/table_structure.Rd
index f241b36e04..1940cd0371 100644
--- a/man/table_structure.Rd
+++ b/man/table_structure.Rd
@@ -18,7 +18,7 @@ No return value. Called for the side-effect of printing a row- or subtable-struc
 Summarize table
 }
 \examples{
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr)
 
 iris2 <- iris \%>\%
diff --git a/man/tostring.Rd b/man/tostring.Rd
index 9d9e517f49..0e567e3370 100644
--- a/man/tostring.Rd
+++ b/man/tostring.Rd
@@ -69,7 +69,7 @@ undefined wrapping behavior. Passing vectors of already split strings remains su
 case each string is word-wrapped separately with the behavior described above.
 }
 \examples{
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr)
 
 iris2 <- iris \%>\%
diff --git a/man/varcuts.Rd b/man/varcuts.Rd
index 877401bb26..360bdd549f 100644
--- a/man/varcuts.Rd
+++ b/man/varcuts.Rd
@@ -168,7 +168,7 @@ before proceeding. Thus even when nested within another split in column/row spac
 the overall values (e.g., quartiles) in the dataset, NOT the values for subset it is nested under.
 }
 \examples{
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr)
 
 # split_cols_by_cuts

From 09fe32b36a901e76e6a6a73e408f858ae47ab6e8 Mon Sep 17 00:00:00 2001
From: Gabe Becker <gabembecker@gmail.com>
Date: Fri, 24 Oct 2025 14:22:29 -0700
Subject: [PATCH 3/7] fix roxygen version mismatch issue

---
 DESCRIPTION                          | 2 +-
 man/add_overall_level.Rd             | 2 +-
 man/analyze_colvars.Rd               | 2 +-
 man/append_topleft.Rd                | 2 +-
 man/cell_values.Rd                   | 2 +-
 man/gfc.Rd                           | 2 +-
 man/int_methods.Rd                   | 2 +-
 man/matrix_form-VTableTree-method.Rd | 2 +-
 man/row_paths_summary.Rd             | 2 +-
 man/split_cols_by.Rd                 | 2 +-
 man/split_cols_by_multivar.Rd        | 2 +-
 man/split_rows_by.Rd                 | 2 +-
 man/table_shell.Rd                   | 2 +-
 man/table_structure.Rd               | 2 +-
 man/tostring.Rd                      | 2 +-
 man/varcuts.Rd                       | 2 +-
 16 files changed, 16 insertions(+), 16 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index 99ec219a4b..d289f6d5c7 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -71,7 +71,7 @@ Encoding: UTF-8
 Language: en-US
 LazyData: true
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.3
+RoxygenNote: 7.3.2
 Collate:
     '00tabletrees.R'
     'Viewer.R'
diff --git a/man/add_overall_level.Rd b/man/add_overall_level.Rd
index a388e24988..ce22160cab 100644
--- a/man/add_overall_level.Rd
+++ b/man/add_overall_level.Rd
@@ -78,7 +78,7 @@ lyt2
 tbl2 <- build_table(lyt2, DM)
 tbl2
 
-\dontshow{if (require(tibble)) withAutoprint(\{ # examplesIf}
+\dontshow{if (require(tibble)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 
 library(tibble)
 combodf <- tribble(
diff --git a/man/analyze_colvars.Rd b/man/analyze_colvars.Rd
index af9a73de94..d30bf48390 100644
--- a/man/analyze_colvars.Rd
+++ b/man/analyze_colvars.Rd
@@ -57,7 +57,7 @@ A \code{PreDataTableLayouts} object suitable for passing to further layouting fu
 Generate rows analyzing different variables across columns
 }
 \examples{
-\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
+\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 library(dplyr)
 
 ANL <- DM \%>\% mutate(value = rnorm(n()), pctdiff = runif(n()))
diff --git a/man/append_topleft.Rd b/man/append_topleft.Rd
index 90f61aa060..0db6195067 100644
--- a/man/append_topleft.Rd
+++ b/man/append_topleft.Rd
@@ -31,7 +31,7 @@ the actual splitting keywords. This may change in the future.
 This function is experimental, its name and the details of its behavior are subject to change in future versions.
 }
 \examples{
-\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
+\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 library(dplyr)
 
 DM2 <- DM \%>\% mutate(RACE = factor(RACE), SEX = factor(SEX))
diff --git a/man/cell_values.Rd b/man/cell_values.Rd
index 55151dceb5..1082f52f3f 100644
--- a/man/cell_values.Rd
+++ b/man/cell_values.Rd
@@ -47,7 +47,7 @@ lyt <- basic_table() \%>\%
   split_rows_by("STRATA1") \%>\%
   analyze("AGE")
 
-\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
+\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 library(dplyr) ## for mutate
 tbl <- build_table(lyt, DM \%>\%
   mutate(SEX = droplevels(SEX), RACE = droplevels(RACE)))
diff --git a/man/gfc.Rd b/man/gfc.Rd
index 70b2dea16d..19c01c1155 100644
--- a/man/gfc.Rd
+++ b/man/gfc.Rd
@@ -50,7 +50,7 @@ The formatted print-strings for all (body) cells in \code{obj}.
 Get formatted cells
 }
 \examples{
-\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
+\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 library(dplyr)
 
 iris2 <- iris \%>\%
diff --git a/man/int_methods.Rd b/man/int_methods.Rd
index 0a662b3de7..e19c04cbfd 100644
--- a/man/int_methods.Rd
+++ b/man/int_methods.Rd
@@ -1302,7 +1302,7 @@ These are internal methods that are documented only to satisfy \verb{R CMD check
 attention to this documentation.
 }
 \examples{
-\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
+\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 library(dplyr)
 
 iris2 <- iris \%>\%
diff --git a/man/matrix_form-VTableTree-method.Rd b/man/matrix_form-VTableTree-method.Rd
index 20bfd790ab..27a488bb84 100644
--- a/man/matrix_form-VTableTree-method.Rd
+++ b/man/matrix_form-VTableTree-method.Rd
@@ -60,7 +60,7 @@ values are determined using \code{get_formatted_cells}. (Column labels are calcu
 function.
 }
 \examples{
-\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
+\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 library(dplyr)
 
 iris2 <- iris \%>\%
diff --git a/man/row_paths_summary.Rd b/man/row_paths_summary.Rd
index 1835aea04a..5a2ec27fc3 100644
--- a/man/row_paths_summary.Rd
+++ b/man/row_paths_summary.Rd
@@ -19,7 +19,7 @@ A data frame summarizing the row- or column-structure of \code{x}.
 Print row/column paths summary
 }
 \examples{
-\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
+\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 ex_adsl_MF <- ex_adsl \%>\% dplyr::filter(SEX \%in\% c("M", "F"))
 
 lyt <- basic_table() \%>\%
diff --git a/man/split_cols_by.Rd b/man/split_cols_by.Rd
index 30c2c97e25..b36e31bfb2 100644
--- a/man/split_cols_by.Rd
+++ b/man/split_cols_by.Rd
@@ -120,7 +120,7 @@ lyt2
 tbl2 <- build_table(lyt2, DM)
 tbl2
 
-\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
+\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 # By default sequentially adding layouts results in nesting
 library(dplyr)
 
diff --git a/man/split_cols_by_multivar.Rd b/man/split_cols_by_multivar.Rd
index 7aca062757..75fd2a752e 100644
--- a/man/split_cols_by_multivar.Rd
+++ b/man/split_cols_by_multivar.Rd
@@ -53,7 +53,7 @@ When we need columns to reflect different variables entirely, rather than differ
 variable, we use \code{split_cols_by_multivar}.
 }
 \examples{
-\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
+\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 library(dplyr)
 
 ANL <- DM \%>\% mutate(value = rnorm(n()), pctdiff = runif(n()))
diff --git a/man/split_rows_by.Rd b/man/split_rows_by.Rd
index 70919aee62..232c46bdbd 100644
--- a/man/split_rows_by.Rd
+++ b/man/split_rows_by.Rd
@@ -146,7 +146,7 @@ lyt3 <- basic_table() \%>\%
 
 lyt3
 
-\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
+\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 library(dplyr)
 
 DM2 <- DM \%>\%
diff --git a/man/table_shell.Rd b/man/table_shell.Rd
index bd310700c5..17734b69c7 100644
--- a/man/table_shell.Rd
+++ b/man/table_shell.Rd
@@ -54,7 +54,7 @@ A table shell is a rendering of the table which maintains the structure, but doe
 displaying the formatting instructions for each cell.
 }
 \examples{
-\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
+\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 library(dplyr)
 
 iris2 <- iris \%>\%
diff --git a/man/table_structure.Rd b/man/table_structure.Rd
index 1940cd0371..f241b36e04 100644
--- a/man/table_structure.Rd
+++ b/man/table_structure.Rd
@@ -18,7 +18,7 @@ No return value. Called for the side-effect of printing a row- or subtable-struc
 Summarize table
 }
 \examples{
-\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
+\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 library(dplyr)
 
 iris2 <- iris \%>\%
diff --git a/man/tostring.Rd b/man/tostring.Rd
index 0e567e3370..9d9e517f49 100644
--- a/man/tostring.Rd
+++ b/man/tostring.Rd
@@ -69,7 +69,7 @@ undefined wrapping behavior. Passing vectors of already split strings remains su
 case each string is word-wrapped separately with the behavior described above.
 }
 \examples{
-\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
+\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 library(dplyr)
 
 iris2 <- iris \%>\%
diff --git a/man/varcuts.Rd b/man/varcuts.Rd
index 360bdd549f..877401bb26 100644
--- a/man/varcuts.Rd
+++ b/man/varcuts.Rd
@@ -168,7 +168,7 @@ before proceeding. Thus even when nested within another split in column/row spac
 the overall values (e.g., quartiles) in the dataset, NOT the values for subset it is nested under.
 }
 \examples{
-\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
+\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 library(dplyr)
 
 # split_cols_by_cuts

From 969f43926fd381e31173dd3f37890516caf7e046 Mon Sep 17 00:00:00 2001
From: github-actions <41898282+github-actions[bot]@users.noreply.github.com>
Date: Fri, 24 Oct 2025 21:25:55 +0000
Subject: [PATCH 4/7] [skip roxygen] [skip vbump] Roxygen Man Pages Auto Update

---
 DESCRIPTION                          | 2 +-
 man/add_overall_level.Rd             | 2 +-
 man/analyze_colvars.Rd               | 2 +-
 man/append_topleft.Rd                | 2 +-
 man/cell_values.Rd                   | 2 +-
 man/gfc.Rd                           | 2 +-
 man/int_methods.Rd                   | 2 +-
 man/matrix_form-VTableTree-method.Rd | 2 +-
 man/row_paths_summary.Rd             | 2 +-
 man/split_cols_by.Rd                 | 2 +-
 man/split_cols_by_multivar.Rd        | 2 +-
 man/split_rows_by.Rd                 | 2 +-
 man/table_shell.Rd                   | 2 +-
 man/table_structure.Rd               | 2 +-
 man/tostring.Rd                      | 2 +-
 man/varcuts.Rd                       | 2 +-
 16 files changed, 16 insertions(+), 16 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index d289f6d5c7..99ec219a4b 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -71,7 +71,7 @@ Encoding: UTF-8
 Language: en-US
 LazyData: true
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.2
+RoxygenNote: 7.3.3
 Collate:
     '00tabletrees.R'
     'Viewer.R'
diff --git a/man/add_overall_level.Rd b/man/add_overall_level.Rd
index ce22160cab..a388e24988 100644
--- a/man/add_overall_level.Rd
+++ b/man/add_overall_level.Rd
@@ -78,7 +78,7 @@ lyt2
 tbl2 <- build_table(lyt2, DM)
 tbl2
 
-\dontshow{if (require(tibble)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(tibble)) withAutoprint(\{ # examplesIf}
 
 library(tibble)
 combodf <- tribble(
diff --git a/man/analyze_colvars.Rd b/man/analyze_colvars.Rd
index d30bf48390..af9a73de94 100644
--- a/man/analyze_colvars.Rd
+++ b/man/analyze_colvars.Rd
@@ -57,7 +57,7 @@ A \code{PreDataTableLayouts} object suitable for passing to further layouting fu
 Generate rows analyzing different variables across columns
 }
 \examples{
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr)
 
 ANL <- DM \%>\% mutate(value = rnorm(n()), pctdiff = runif(n()))
diff --git a/man/append_topleft.Rd b/man/append_topleft.Rd
index 0db6195067..90f61aa060 100644
--- a/man/append_topleft.Rd
+++ b/man/append_topleft.Rd
@@ -31,7 +31,7 @@ the actual splitting keywords. This may change in the future.
 This function is experimental, its name and the details of its behavior are subject to change in future versions.
 }
 \examples{
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr)
 
 DM2 <- DM \%>\% mutate(RACE = factor(RACE), SEX = factor(SEX))
diff --git a/man/cell_values.Rd b/man/cell_values.Rd
index 1082f52f3f..55151dceb5 100644
--- a/man/cell_values.Rd
+++ b/man/cell_values.Rd
@@ -47,7 +47,7 @@ lyt <- basic_table() \%>\%
   split_rows_by("STRATA1") \%>\%
   analyze("AGE")
 
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr) ## for mutate
 tbl <- build_table(lyt, DM \%>\%
   mutate(SEX = droplevels(SEX), RACE = droplevels(RACE)))
diff --git a/man/gfc.Rd b/man/gfc.Rd
index 19c01c1155..70b2dea16d 100644
--- a/man/gfc.Rd
+++ b/man/gfc.Rd
@@ -50,7 +50,7 @@ The formatted print-strings for all (body) cells in \code{obj}.
 Get formatted cells
 }
 \examples{
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr)
 
 iris2 <- iris \%>\%
diff --git a/man/int_methods.Rd b/man/int_methods.Rd
index e19c04cbfd..0a662b3de7 100644
--- a/man/int_methods.Rd
+++ b/man/int_methods.Rd
@@ -1302,7 +1302,7 @@ These are internal methods that are documented only to satisfy \verb{R CMD check
 attention to this documentation.
 }
 \examples{
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr)
 
 iris2 <- iris \%>\%
diff --git a/man/matrix_form-VTableTree-method.Rd b/man/matrix_form-VTableTree-method.Rd
index 27a488bb84..20bfd790ab 100644
--- a/man/matrix_form-VTableTree-method.Rd
+++ b/man/matrix_form-VTableTree-method.Rd
@@ -60,7 +60,7 @@ values are determined using \code{get_formatted_cells}. (Column labels are calcu
 function.
 }
 \examples{
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr)
 
 iris2 <- iris \%>\%
diff --git a/man/row_paths_summary.Rd b/man/row_paths_summary.Rd
index 5a2ec27fc3..1835aea04a 100644
--- a/man/row_paths_summary.Rd
+++ b/man/row_paths_summary.Rd
@@ -19,7 +19,7 @@ A data frame summarizing the row- or column-structure of \code{x}.
 Print row/column paths summary
 }
 \examples{
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 ex_adsl_MF <- ex_adsl \%>\% dplyr::filter(SEX \%in\% c("M", "F"))
 
 lyt <- basic_table() \%>\%
diff --git a/man/split_cols_by.Rd b/man/split_cols_by.Rd
index b36e31bfb2..30c2c97e25 100644
--- a/man/split_cols_by.Rd
+++ b/man/split_cols_by.Rd
@@ -120,7 +120,7 @@ lyt2
 tbl2 <- build_table(lyt2, DM)
 tbl2
 
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 # By default sequentially adding layouts results in nesting
 library(dplyr)
 
diff --git a/man/split_cols_by_multivar.Rd b/man/split_cols_by_multivar.Rd
index 75fd2a752e..7aca062757 100644
--- a/man/split_cols_by_multivar.Rd
+++ b/man/split_cols_by_multivar.Rd
@@ -53,7 +53,7 @@ When we need columns to reflect different variables entirely, rather than differ
 variable, we use \code{split_cols_by_multivar}.
 }
 \examples{
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr)
 
 ANL <- DM \%>\% mutate(value = rnorm(n()), pctdiff = runif(n()))
diff --git a/man/split_rows_by.Rd b/man/split_rows_by.Rd
index 232c46bdbd..70919aee62 100644
--- a/man/split_rows_by.Rd
+++ b/man/split_rows_by.Rd
@@ -146,7 +146,7 @@ lyt3 <- basic_table() \%>\%
 
 lyt3
 
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr)
 
 DM2 <- DM \%>\%
diff --git a/man/table_shell.Rd b/man/table_shell.Rd
index 17734b69c7..bd310700c5 100644
--- a/man/table_shell.Rd
+++ b/man/table_shell.Rd
@@ -54,7 +54,7 @@ A table shell is a rendering of the table which maintains the structure, but doe
 displaying the formatting instructions for each cell.
 }
 \examples{
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr)
 
 iris2 <- iris \%>\%
diff --git a/man/table_structure.Rd b/man/table_structure.Rd
index f241b36e04..1940cd0371 100644
--- a/man/table_structure.Rd
+++ b/man/table_structure.Rd
@@ -18,7 +18,7 @@ No return value. Called for the side-effect of printing a row- or subtable-struc
 Summarize table
 }
 \examples{
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr)
 
 iris2 <- iris \%>\%
diff --git a/man/tostring.Rd b/man/tostring.Rd
index 9d9e517f49..0e567e3370 100644
--- a/man/tostring.Rd
+++ b/man/tostring.Rd
@@ -69,7 +69,7 @@ undefined wrapping behavior. Passing vectors of already split strings remains su
 case each string is word-wrapped separately with the behavior described above.
 }
 \examples{
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr)
 
 iris2 <- iris \%>\%
diff --git a/man/varcuts.Rd b/man/varcuts.Rd
index 877401bb26..360bdd549f 100644
--- a/man/varcuts.Rd
+++ b/man/varcuts.Rd
@@ -168,7 +168,7 @@ before proceeding. Thus even when nested within another split in column/row spac
 the overall values (e.g., quartiles) in the dataset, NOT the values for subset it is nested under.
 }
 \examples{
-\dontshow{if (require(dplyr)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require(dplyr)) withAutoprint(\{ # examplesIf}
 library(dplyr)
 
 # split_cols_by_cuts

From 9d5e19f814321e6ff2a2b3a749caefaed72ac15c Mon Sep 17 00:00:00 2001
From: Gabe Becker <gabembecker@gmail.com>
Date: Fri, 24 Oct 2025 14:41:21 -0700
Subject: [PATCH 5/7] hopefully fix spellcheck

---
 inst/WORDLIST                                 | 80 ++++++++++---------
 ...guided_intermediate_translating_shells.Rmd |  2 +-
 2 files changed, 44 insertions(+), 38 deletions(-)

diff --git a/inst/WORDLIST b/inst/WORDLIST
index c9635f358d..8fbd5cdb80 100644
--- a/inst/WORDLIST
+++ b/inst/WORDLIST
@@ -1,47 +1,19 @@
+AE
+afun
+amongst
 ARD
+ard
 ARDs
-Bové
-CRAN's
+biomarker
+BMEASIFL
+Bov<U+00E9>
 Carreras
+charset
 Cheatsheet
 Chohan
-FFFL
-Godwin
-Heng
-Hoffmann
-IEC
-Kelkhoff
-Layouting
-Lewandowski
-Maximo
-Modelling
-NSE
-ORCID
-Paszty
-Pathing
-Pharma
-Phuse
-Pre
-Qi
-RStudio
-Resync
-Rua
-STUDYID
-Sabanés
-Saibah
-Stoilova
-Subtable
-Subtables
-Tadeusz
-Unstratified
-ValueWrapper
-Yung
-afun
-amongst
-ard
-charset
 colcount
 combinatorial
+CRAN's
 customizations
 de
 decrementing
@@ -53,45 +25,76 @@ elemtable
 emph
 facetted
 facetting
+FFFL
 formatter
 forseeable
 funder
 getter
 getters
+Godwin
+Heng
+Hoffmann
 ie
+IEC
 iec
 indicies
 ing
 initializer
+Kelkhoff
 labelled
+Layouting
 layouting
+Lewandowski
 mandatorily
+Maximo
 modelled
+Modelling
 monospace
 multivariable
+NSE
+ORCID
 orderable
+orthogonally
+oversimplifaction
+Paszty
 pathability
 pathable
 pathed
+Pathing
 pathing
 peforms
+Pharma
+Phuse
 postfix
 postprocessing
+Pre
 pre
+Qi
 reindexed
 repped
 responder
+Resync
 reusability
 roadmap
+RStudio
+rtables
+Rua
+Saban<U+00E9>s
+Saibah
 sas
 sortable
 spl
+Stoilova
+STUDYID
 subsplits
+Subtable
 subtable
 subtable's
+Subtables
 subtables
 summarization
 tableone
+Tadeusz
 todo
 traversable
 truetype
@@ -102,8 +105,11 @@ uniquification
 univariable
 unnested
 unpruned
+Unstratified
 unstratified
 useR
+ValueWrapper
 visibilities
 visibilty
 xtable
+Yung
diff --git a/vignettes/guided_intermediate_translating_shells.Rmd b/vignettes/guided_intermediate_translating_shells.Rmd
index 27104994f1..4d47080fee 100644
--- a/vignettes/guided_intermediate_translating_shells.Rmd
+++ b/vignettes/guided_intermediate_translating_shells.Rmd
@@ -26,7 +26,7 @@ editor_options:
 The first - and often largest - hurdle to creating a table via
 `rtables` is translating the desired table structure (typically in the
 form of a *table shell*) into an `rtables` *layout*. We will cover
-this translation step here.
+that translation process in this vignette.
 
 ## A Table Shell
 

From 760aafe950385c3e3e52e6483153a199bed8a8fb Mon Sep 17 00:00:00 2001
From: Gabe Becker <gabembecker@gmail.com>
Date: Fri, 24 Oct 2025 15:44:18 -0700
Subject: [PATCH 6/7] add vignette to pkgdown  [skip spelling]

---
 _pkgdown.yml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/_pkgdown.yml b/_pkgdown.yml
index db013a22f9..0c25ef8ac8 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -60,6 +60,7 @@ articles:
     contents:
     - rtables
     - exploratory_analysis
+    - guided_intermediate_translating_shells
 
   - title: Clinical Trials
     navbar: Clinical Trials

From da8c6d07584b1dfbf9136406134d105befda446a Mon Sep 17 00:00:00 2001
From: Joe Zhu <sha.joe.zhu@gmail.com>
Date: Mon, 27 Oct 2025 14:53:29 +0800
Subject: [PATCH 7/7] update wordlist

---
 inst/WORDLIST | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/inst/WORDLIST b/inst/WORDLIST
index 8fbd5cdb80..1f8e55bff4 100644
--- a/inst/WORDLIST
+++ b/inst/WORDLIST
@@ -7,6 +7,7 @@ ARDs
 biomarker
 BMEASIFL
 Bov<U+00E9>
+Bové
 Carreras
 charset
 Cheatsheet
@@ -80,6 +81,7 @@ RStudio
 rtables
 Rua
 Saban<U+00E9>s
+Sabanés
 Saibah
 sas
 sortable