R/build_limits_lookup.R

In FunnelPlotR: Funnel Plots for Comparing Institutional Performance

#' Function to build funnel limits
#' @description Internal function for funnel plot to build the control limits
#' prior to plotting.
#' @param min_x Minimum predicted value for range of x-axis
#' @param max_x Maximum predicted value for range of x-axis
#' @param min_y Minimum ratio value for range of y-axis
#' @param max_y Maximum ratio value for range of y-axis
#' @param draw_adjusted TRUE/FALSE Use overdispersion adjustment
#' @param tau2 If using draw_adjusted, what is the tau2 ("between" standard
#' error) to use?
#' @param data_type SR, PR or RC. Used to set target reference
#' @param sr_method Which adjustment method is being used, SHMI or CQC?
#' @param target target to be used to set centre line
#' @param multiplier Multiply ratio value by an amount.  Default is 1,
#' but some mortality ratios use 100, for example.
#' @keywords internal
#' @return A data.frame with an index column and various control limits based
#' on the index as an x-axis value.
#'
#' @importFrom stats qchisq quantile
build_limits_lookup <- function(min_x, max_x, min_y, max_y
                                , draw_adjusted, tau2, data_type, sr_method
                                , target, multiplier, denominators) {


  # general limits + tau2 limits table
  set.seed(1)


  if (data_type == "SR") {
    number_seq <- seq(1.1, as.numeric(max_x), length.out = 1000)
  } else {
    number_seq <- seq(3, as.numeric(max_x), length.out = 1000)
  }

  if (!missing(denominators)) {
    number_seq <- sort(unique(c(number_seq, denominators)))
  }

  df_ci <- data.frame(
    number_seq
  )

  df_ci <- calculate_limits(df_ci, data_type, sr_method, multiplier, tau2
                            , target, draw_adjusted = TRUE)
  df_ci <- calculate_limits(df_ci, data_type, sr_method, multiplier, tau2
                            , target, draw_adjusted = FALSE)

  df_ci
}