R/modSE.R

In simMetric: Metrics (with Uncertainty) for Simulation Studies that Evaluate Statistical Methods

#' Calculates the average model standard error
#'
#' Calculates the average model standard error and the Monte Carlo standard error of this estimate.
#'
#' @param se A numeric vector containing the standard errors from the model(s).
#' @param get A character vector containing the values returned by the function.
#' @param na.rm A logical value indicating whether NA values for `se` should be removed before modSE calculation.
#' @param ... Additional arguments to be ignored.
#'
#' @return A named vector containing the estimate and the Monte Carlo standard error for the average model standard error.
#' @export
#'
#' @examples modSE(se = runif(n = 20, min = 1, max = 1.5))
modSE <- function(se, get = c("modSE", "modSE_mcse"), na.rm = FALSE, ...) {
  assertthat::assert_that(length(!is.na(se)) > 0)
  assertthat::assert_that(all(se[!is.na(se)] > 0))

  x <- c()
  if (na.rm) {
    se <- se[!is.na(se)]
  }

  if (any(is.na(se))) {
    x["modSE"] <- NA
    x["modSE_mcse"] <- NA
    return(x[get])
  }

  n <- length(se)
  x["modSE"] <- sqrt(sum(se^2) / n)
  numerator <- (1 / (n - 1)) * sum((se^2 - x["modSE"]^2)^2)
  x["modSE_mcse"] <- sqrt(numerator / (4 * n * (x["modSE"]^2)))
  return(x[get])
}