R/mellenbergh.test.R

In neuropsychology/psycho.R: Efficient and Publishing-Oriented Workflow for Psychological Science

#' Mellenbergh & van den Brink (1998) test for pre-post comparison.
#'
#' Test for comparing post-test to baseline for a single participant.
#'
#' @param t0 Single value (pretest or baseline score).
#' @param t1 Single value (posttest score).
#' @param controls Vector of scores of the control group OR single value corresponding to the control SD of the score.
#'
#' @return Returns a data frame containing the z-value and p-value. If significant, the difference between pre and post tests is significant.
#'
#' @examples
#' library(psycho)
#'
#' mellenbergh.test(t0 = 4, t1 = 12, controls = c(0, -2, 5, 2, 1, 3, -4, -2))
#' mellenbergh.test(t0 = 8, t1 = 2, controls = 2.6)
#' @author Dominique Makowski
#'
#' @importFrom stats pnorm sd
#' @export
mellenbergh.test <- function(t0, t1, controls) {
  if (length(controls) > 1) {
    sd <- sd(controls) * sqrt(2)
  } else {
    sd <- controls * sqrt(2)
  }

  diff <- t1 - t0

  diff_CI_bottom <- diff - 1.65 * sd
  diff_CI_top <- diff + 1.65 * sd

  z <- diff / sd
  pval <- 2 * pnorm(-abs(z))

  # One-tailed p value
  if (pval > .05 & pval / 2 < .05) {
    one_tailed <- paste0(
      " However, the null hypothesis of no change can be rejected at a one-tailed 5% significance level (one-tailed p ",
      insight::format_p(pval / 2),
      ")."
    )
  } else {
    one_tailed <- ""
  }



  p_interpretation <- ifelse(pval < 0.05, " ", " not ")
  text <- paste0(
    "The Mellenbergh & van den Brink (1998) test suggests that the change is",
    p_interpretation,
    "significant (d = ",
    insight::format_value(diff),
    ", 90% CI [",
    insight::format_value(diff_CI_bottom),
    ", ",
    insight::format_value(diff_CI_top),
    "], z = ",
    insight::format_value(z),
    ", p ",
    insight::format_p(pval),
    ").",
    one_tailed
  )


  values <- list(
    text = text,
    diff = diff,
    diff_90_CI_lower = diff_CI_bottom,
    diff_90_CI_higher = diff_CI_top,
    z = z,
    p = pval
  )
  summary <- data.frame(diff = diff, diff_90_CI_lower = diff_CI_bottom, diff_90_CI_higher = diff_CI_top, z = z, p = pval)
  plot <- "Not available yet"


  output <- list(text = text, plot = plot, summary = summary, values = values)
  class(output) <- c("psychobject", "list")
  return(output)
  #   return("The method for no-controls is not implemented yet.")
}