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#' Adds column with N to gtsummary table
#'
#' @param x Object created from a gtsummary function
#' @param ... Additional arguments passed to other methods.
#' @author Daniel D. Sjoberg
#'
#' @keywords internal
#' @seealso [add_n.tbl_summary()], [add_n.tbl_svysummary()], [add_n.tbl_survfit()],
#' [add_n.tbl_regression], [add_n.tbl_uvregression]
#' @export
add_n <- function(x, ...) {
UseMethod("add_n")
}
#' Add column with N
#'
#' For each variable in a `tbl_summary` table, the `add_n` function adds a column with the
#' total number of non-missing (or missing) observations
#'
#' @param x Object with class `tbl_summary` from the [tbl_summary] function or
#' with class `tbl_svysummary` from the [tbl_svysummary] function
#' @param statistic String indicating the statistic to report. Default is the
#' number of non-missing observation for each variable, `statistic = "{n}"`.
#' Other statistics available to report include:
#' * `"{N_obs}"` total number of observations,
#' * `"{N_nonmiss}"` number of non-missing observations,
#' * `"{N_miss}"` number of missing observations,
#' * `"{p_nonmiss}"` percent non-missing data,
#' * `"{p_miss}"` percent missing data
#' * survey summaries also have the following unweighted statistics available:
#' `"N_obs_unweighted"`, `"N_miss_unweighted"`, `"N_nonmiss_unweighted"`, `"p_miss_unweighted"`, `"p_nonmiss_unweighted"`
#'
#' The argument uses [glue::glue] syntax and multiple statistics may be reported,
#' e.g. `statistic = "{N_nonmiss} / {N_obs} ({p_nonmiss}%)"`
#' @param col_label String indicating the column label. Default is `"**N**"`
#' @param footnote Logical argument indicating whether to print a footnote
#' clarifying the statistics presented. Default is `FALSE`
#' @param last Logical indicator to include N column last in table.
#' Default is `FALSE`, which will display N column first.
#' @param ... Not used
#' @family tbl_summary tools
#' @family tbl_svysummary tools
#' @author Daniel D. Sjoberg
#' @export
#' @seealso Review [list, formula, and selector syntax][syntax] used throughout gtsummary
#' @rdname add_n.tbl_summary
#' @return A `tbl_summary` or `tbl_svysummary` object
#' @examples
#' # Example 1 ----------------------------------
#' tbl_n_ex <-
#' trial[c("trt", "age", "grade", "response")] %>%
#' tbl_summary(by = trt) %>%
#' add_n()
#' @section Example Output:
#'
#' \if{html}{Example 1}
#'
#' \if{html}{\out{
#' `r man_create_image_tag(file = "tbl_n_ex.png", width = "50")`
#' }}
add_n.tbl_summary <- function(x, statistic = "{n}", col_label = "**N**", footnote = FALSE,
last = FALSE, ...) {
check_dots_empty(error = function(e) inform(c(e$message, e$body)))
updated_call_list <- c(x$call_list, list(add_n = match.call()))
# checking that input is class tbl_summary
if (!(inherits(x, "tbl_summary") | inherits(x, "tbl_svysummary"))) {
stop("`x` must be class 'tbl_summary' or 'tbl_svysummary'")
}
# grabbing summary counts ----------------------------------------------------
df_stats <-
x$meta_data$df_stats %>%
map_dfr(
function(.x) {
df_stats <-
# remove overall row, if it has been added with `add_overall()`
.purrr_when(
"by" %in% names(.x) ~ filter(.x, !is.na(.data$by)),
TRUE ~ .x
) %>%
select(any_of(c(
"variable", "by", "N_obs", "N_miss", "N_nonmiss", "p_miss",
"p_nonmiss", "N_obs_unweighted", "N_miss_unweighted",
"N_nonmiss_unweighted", "p_miss_unweighted",
"p_nonmiss_unweighted"
))) %>%
distinct() %>%
# summing counts within by variable within by levels
dplyr::group_by_at(c("variable", "by") %>% intersect(names(.))) %>%
mutate_at(vars(-any_of(c("variable", "by"))), sum) %>%
select(-any_of("by")) %>%
distinct()
# correcting percentages -----------------------------------------------
if ("p_miss" %in% names(df_stats)) {
df_stats <- mutate(df_stats, p_miss = .data$N_miss / .data$N_obs)
}
if ("p_nonmiss" %in% names(df_stats)) {
df_stats <- mutate(df_stats, p_nonmiss = .data$N_nonmiss / .data$N_obs)
}
if ("p_miss_unweighted" %in% names(df_stats)) {
df_stats <- mutate(df_stats, p_miss_unweighted = .data$N_miss_unweighted / .data$N_obs_unweighted)
}
if ("p_nonmiss_unweighted" %in% names(df_stats)) {
df_stats <- mutate(df_stats, p_nonmiss_unweighted = .data$N_nonmiss_unweighted / .data$N_obs_unweighted)
}
# styling the statistics -----------------------------------------------
for (v in (names(df_stats) %>% setdiff("variable"))) {
df_stats[[v]] <- df_stats[[v]] %>% attr(.x[[v]], "fmt_fun")()
}
# returning formatted df -----------------------------------------------
df_stats %>%
# adding these cols for backwards compatibility (documentation of these names was dropped on 2022-04-03)
mutate(
N = .data$N_obs,
n = .data$N_nonmiss,
n_miss = .data$N_miss,
p = .data$p_nonmiss
)
}
) %>%
# making the row that will be merged into table_body -----------------------
mutate(
statistic = glue(.env$statistic) %>% as.character(),
row_type = "label"
) %>%
select("variable", "row_type", n = "statistic")
# merging result with existing tbl_summary -----------------------------------
x$table_body <-
left_join(x$table_body, df_stats, by = c("variable", "row_type"))
if (last == FALSE) {
x$table_body <-
select(x$table_body, any_of(c("variable", "row_type", "label", "n")), everything())
}
# updating table_styling -----------------------------------------------------
x <-
.update_table_styling(x) %>%
modify_header(n = col_label)
# Adding footnote if requested -----------------------------------------------
if (footnote == TRUE) {
x <- modify_footnote(x, n ~ stat_to_label(statistic))
}
# fill in the Ns in the header table modify_stat_* columns
x <- .fill_table_header_modify_stats(x)
# adding indicator to output that add_n was run on this data
x$call_list <- updated_call_list
# returning tbl_summary object
x
}
stat_to_label <- function(x) {
language <- get_theme_element("pkgwide-str:language", default = "en")
df_statistic_names <-
tibble::tribble(
~stat, ~name,
"{N}", "Total N",
"{n}", "N not Missing",
"{n_miss}", "N Missing",
"{p}%", "% not Missing",
"{p}", "% not Missing",
"{p_miss}%", "% Missing",
"{p_miss}", "% Missing",
"{N_obs}", "Total N",
"{N_miss}", "N Missing",
"{N_nonmiss}", "N not Missing",
"{p_nonmiss}", "% not Missing",
"{N_obs_unweighted}", "Total N (unweighted)",
"{N_miss_unweighted}", "N Missing (unweighted)",
"{N_nonmiss_unweighted}", "N not Missing (unweighted)",
"{p_miss_unweighted}", "% Missing (unweighted)",
"{p_nonmiss_unweighted}", "% not Missing (unweighted)"
) %>%
mutate(name = map_chr(.data$name, ~ translate_text(.x, language)))
for (i in seq_len(nrow(df_statistic_names))) {
x <- stringr::str_replace_all(
x,
fixed(df_statistic_names$stat[i]),
fixed(df_statistic_names$name[i])
)
}
x
}
#' @export
#' @rdname add_n.tbl_summary
add_n.tbl_svysummary <- add_n.tbl_summary
#' Add column with number of observations
#'
#' \lifecycle{maturing}
#' For each `survfit()` object summarized with `tbl_survfit()` this function
#' will add the total number of observations in a new column.
#'
#' @param x object of class "`tbl_survfit`"
#' @param ... Not used
#' @export
#' @seealso Review [list, formula, and selector syntax][syntax] used throughout gtsummary
#' @family tbl_survfit tools
#' @examplesIf broom.helpers::.assert_package("survival", pkg_search = "gtsummary", boolean = TRUE)
#' \donttest{
#' library(survival)
#' fit1 <- survfit(Surv(ttdeath, death) ~ 1, trial)
#' fit2 <- survfit(Surv(ttdeath, death) ~ trt, trial)
#'
#' # Example 1 ----------------------------------
#' add_n.tbl_survfit_ex1 <-
#' list(fit1, fit2) %>%
#' tbl_survfit(times = c(12, 24)) %>%
#' add_n()
#' }
#' @section Example Output:
#' \if{html}{Example 1}
#'
#' \if{html}{\out{
#' `r man_create_image_tag(file = "add_n.tbl_survfit_ex1.png", width = "64")`
#' }}
add_n.tbl_survfit <- function(x, ...) {
check_dots_empty(error = function(e) inform(c(e$message, e$body)))
updated_call_list <- c(x$call_list, list(add_n = match.call()))
# adding N to the table_body -------------------------------------------------
x$table_body <-
purrr::map2_dfr(
x$meta_data$survfit,
x$meta_data$variable,
function(suvfit, variable) {
# extracting survfit call
survfit_call <- suvfit$call %>% as.list()
# index of formula and data
call_index <- names(survfit_call) %in% c("formula", "data") %>% which()
# converting call into a survdiff call
model.frame_call <- rlang::call2(rlang::expr(stats::model.frame), !!!survfit_call[call_index], ...)
# returning number of rows in data frame
tibble(
variable = variable,
row_type = "label",
N = safe_survfit_eval(model.frame_call) %>% nrow()
)
}
) %>%
{
left_join(
x$table_body, .,
by = c("variable", "row_type")
)
} %>%
select(any_of(c("variable", "row_type", "label", "N")), everything())
# adding styling data for N column -------------------------------------------
x <-
modify_table_styling(
x,
columns = "N",
label = "**N**",
fmt_fun = style_number,
hide = FALSE
)
# fill in the Ns in the header table modify_stat_* columns
x <- .fill_table_header_modify_stats(x)
# adding indicator to output that add_n was run on this data
x$call_list <- updated_call_list
x
}
#' Add N to regression table
#'
#' @param x a `tbl_regression` or `tbl_uvregression` table
#' @param location location to place Ns. When `"label"` total Ns are placed
#' on each variable's label row. When `"level"` level counts are placed on the
#' variable level for categorical variables, and total N on the variable's label
#' row for continuous.
#' @param ... Not used
#'
#' @name add_n_regression
#' @examples
#' \donttest{
#' # Example 1 ----------------------------------
#' add_n.tbl_regression_ex1 <-
#' trial %>%
#' select(response, age, grade) %>%
#' tbl_uvregression(
#' y = response,
#' method = glm,
#' method.args = list(family = binomial),
#' hide_n = TRUE
#' ) %>%
#' add_n(location = "label")
#'
#' # Example 2 ----------------------------------
#' add_n.tbl_regression_ex2 <-
#' glm(response ~ age + grade, trial, family = binomial) %>%
#' tbl_regression(exponentiate = TRUE) %>%
#' add_n(location = "level")
#' }
#' @section Example Output:
#' \if{html}{Example 1}
#'
#' \if{html}{\out{
#' `r man_create_image_tag(file = "add_n.tbl_regression_ex1.png", width = "64")`
#' }}
#'
#' \if{html}{Example 2}
#'
#' \if{html}{\out{
#' `r man_create_image_tag(file = "add_n.tbl_regression_ex2.png", width = "64")`
#' }}
NULL
#' @rdname add_n_regression
#' @export
add_n.tbl_regression <- function(x, location = NULL, ...) {
check_dots_empty(error = function(e) inform(c(e$message, e$body)))
updated_call_list <- c(x$call_list, list(add_n = match.call()))
location <- match.arg(location, choices = c("label", "level"), several.ok = TRUE)
if ("level" %in% location && !"n_obs" %in% x$table_styling$header$column) {
abort("Reporting N on level rows is not available for this model type.")
}
if ("label" %in% location && !"N_obs" %in% x$table_styling$header$column) {
abort("Reporting N on label rows is not available for this model type.")
}
x$table_body$stat_n <- NA_integer_
if ("N_obs" %in% names(x$table_body)) {
x$table_body$stat_n <- ifelse(x$table_body$row_type == "label",
x$table_body$N_obs %>% as.integer(),
x$table_body$stat_n
)
}
if ("n_obs" %in% names(x$table_body)) {
x$table_body$stat_n <- ifelse(x$table_body$row_type == "level",
x$table_body$n_obs %>% as.integer(),
x$table_body$stat_n
)
}
x <-
x %>%
modify_table_body(
mutate,
stat_n =
case_when(
!"level" %in% .env$location & .data$row_type %in% "level" ~ NA_integer_,
!"label" %in% .env$location & .data$row_type %in% "label" &
.data$var_type %in% c("categorical", "dichotomous") ~ NA_integer_,
TRUE ~ .data$stat_n
)
) %>%
modify_table_body(
dplyr::relocate,
"stat_n",
.after = "label"
) %>%
modify_table_styling(
columns = all_of("stat_n"),
label = "**N**",
hide = FALSE,
fmt_fun = style_number
)
# fill in the Ns in the header table modify_stat_* columns
x <- .fill_table_header_modify_stats(x)
x$call_list <- updated_call_list
x
}
#' @export
#' @rdname add_n_regression
add_n.tbl_uvregression <- add_n.tbl_regression
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