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#' Plot Regression Coefficients
#'
#' The `plot()` function extracts `x$table_body` and passes the it to
#' `ggstats::ggcoef_plot()` along with formatting options.
#'
#' \lifecycle{experimental}
#' @param x (`tbl_regression`, `tbl_uvregression`)\cr
#' A 'tbl_regression' or 'tbl_uvregression' object
#' @param remove_header_rows (scalar `logical`)\cr
#' logical indicating whether to remove header rows
#' for categorical variables. Default is `TRUE`
#' @param remove_reference_rows (scalar `logical`)\cr
#' logical indicating whether to remove reference rows
#' for categorical variables. Default is `FALSE`.
#' @param ... arguments passed to `ggstats::ggcoef_plot(...)`
#'
#' @return a ggplot
#' @name plot
#'
#' @examplesIf gtsummary:::is_pkg_installed("ggstats", reference_pkg = "gtsummary")
#' glm(response ~ marker + grade, trial, family = binomial) |>
#' tbl_regression(
#' add_estimate_to_reference_rows = TRUE,
#' exponentiate = TRUE
#' ) |>
#' plot()
NULL
#' @rdname plot
#' @export
plot.tbl_regression <- function(x,
remove_header_rows = TRUE,
remove_reference_rows = FALSE, ...) {
check_dots_empty()
check_pkg_installed("ggstats", reference_pkg = "gtsummary")
check_not_missing(x)
check_scalar_logical(remove_header_rows)
check_scalar_logical(remove_reference_rows)
df_coefs <- x$table_body
if (isTRUE(remove_header_rows)) {
df_coefs <- df_coefs |> dplyr::filter(!.data$header_row %in% TRUE)
}
if (isTRUE(remove_reference_rows)) {
df_coefs <- df_coefs |> dplyr::filter(!.data$reference_row %in% TRUE)
}
df_coefs %>%
ggstats::ggcoef_plot(exponentiate = x$inputs$exponentiate, ...)
}
#' @rdname plot
#' @export
plot.tbl_uvregression <- plot.tbl_regression
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