#' Print a flexible baseline characteristics table
#'
#' @param data data set
#' @param fun.args list of arguments passed to
#' @param fun function to
#' @param vars character vector of variables to include
#'
#' @return object of standard class for fun
#' @export
#'
#' @examples
#' mtcars |> baseline_table()
#' mtcars |> baseline_table(fun.args = list(by = "gear"))
baseline_table <- function(data, fun.args = NULL, fun = gtsummary::tbl_summary, vars = NULL) {
  if (!is.null(vars)) {
    data <- data |> dplyr::select(dplyr::all_of(vars))
  }

  out <- do.call(fun, c(list(data = data), fun.args))
  return(out)
}



#' Create a baseline table
#'
#' @param data data
#' @param ... passed as fun.arg to baseline_table()
#' @param strat.var grouping/strat variable
#' @param add.p add comparison/p-value
#' @param add.overall add overall column
#'
#' @returns gtsummary table list object
#' @export
#'
#' @examples
#' mtcars |> create_baseline(by.var = "gear", add.p="yes"=="yes")
create_baseline <- function(data,...,by.var,add.p=FALSE,add.overall=FALSE){
  if (by.var == "none" | !by.var %in% names(data)) {
    by.var <- NULL
  }

  ## These steps are to handle logicals/booleans, that messes up the order of columns
  ## Has been reported

  if (!is.null(by.var)) {
    if (identical("logical",class(data[[by.var]]))){
      data[by.var] <- as.character(data[[by.var]])
    }
  }

  out <- data |>
    baseline_table(
      fun.args =
        list(
          by = by.var,
          ...
        )
    )

  if (!is.null(by.var)) {
    if (isTRUE(add.overall)){
  out <- out |> gtsummary::add_overall()
    }
    if (isTRUE(add.p)) {
      out <- out |>
        gtsummary::add_p() |>
        gtsummary::bold_p()
    }

    }

  out
}