R/ggWrightMap.R

In ShinyItemAnalysis: Test and Item Analysis via Shiny

#' Plot person-item map (Wright map) using `ggplot2`
#'
#' @aliases ggWrightMap
#'
#' @description This function allows to generate Wright map (also called
#'   person-item map) using `ggplot()` function from the \pkg{ggplot2}
#'   package. Wright map is used to jointly display histogram of abilities
#'   (or other measured trait) and item difficulty parameters.
#'   Function takes pre-estimated parameter estimates, such as those obtained
#'   from an IRT model.
#'
#' @param theta numeric: vector of ability estimates.
#' @param b numeric: vector of difficulty estimates.
#' @param binwidth numeric: the width of the bins of histogram.
#' @param color character: color of histogram.
#' @param size text size in pts.
#' @param item.names names of items to be displayed.
#' @param ylab.theta character: description of y-axis for the histogram.
#' @param ylab.b character: description of y-axis for the plot of difficulty
#'   estimates.
#' @param rel_widths numeric: vector of length 2 specifying ratio of "facet's"
#'   widths.
#'
#' @importFrom ggplot2 ggplotGrob unit
#' @importFrom grid grid.newpage gTree grid.draw
#' @importFrom mirt fscores
#'
#' @author
#' Adela Hladka \cr
#' Institute of Computer Science of the Czech Academy of Sciences \cr
#' \email{hladka@@cs.cas.cz}
#'
#' Jan Netik \cr
#' Institute of Computer Science of the Czech Academy of Sciences \cr
#' \email{netik@@cs.cas.cz}
#'
#' Patricia Martinkova \cr
#' Institute of Computer Science of the Czech Academy of Sciences \cr
#' \email{martinkova@@cs.cas.cz}
#'
#' @references
#' Wright, B. & Stone, M. (1979). Best test design. MESA Press: Chicago, IL
#'
#' @examples
#' library(mirt)
#'
#' # fit Rasch model with the mirt package
#' fit <- mirt(HCI[, 1:20], model = 1, itemtype = "Rasch")
#' # factor scores
#' theta <- as.vector(fscores(fit))
#' # difficulty estimates using IRT parametrization
#' b <- coef(fit, simplify = TRUE, IRTpars = TRUE)$items[, "b"]
#'
#' # Wright map
#' ggWrightMap(theta, b)
#'
#' # Wright map with modified item names
#' item.names <- paste("Item", 1:20)
#' ggWrightMap(theta, b, item.names = item.names)
#'
#' # Wright map with modified descriptions of y-axis and relative widths of plots
#' ggWrightMap(theta, b,
#'   ylab.theta = "Latent trait", ylab.b = "Difficulty estimates",
#'   rel_widths = c(2, 1)
#' )
#' @export

ggWrightMap <- function(
  theta,
  b,
  binwidth = 0.5,
  color = "blue",
  size = 15,
  item.names,
  ylab.theta = "Respondent latent trait",
  ylab.b = "Item difficulty",
  rel_widths = c(1, 1)
) {
  plts <- gg_wright_internal(
    theta,
    b,
    binwidth,
    color,
    size,
    item.names,
    ylab.theta,
    ylab.b,
    rel_widths
  )

  # arrange plots using bare grid
  grid.newpage()

  grobs <- lapply(plts, ggplotGrob)

  new_layout <- data.frame(list(
    t = c(1, 1),
    l = c(1, 2),
    b = c(1, 1),
    r = c(1, 2),
    z = c(1, 2),
    clip = rep("off", 2),
    name = rep("arrange", 2)
  ))

  # make gtable
  g <- gTree(
    grobs = grobs,
    layout = new_layout,
    widths = unit(rel_widths, "null"),
    heights = unit(1, "null"),
    respect = FALSE,
    name = "arrange",
    rownames = NULL,
    colnames = NULL,
    vp = NULL,
    cl = "gtable"
  )

  grid.draw(g)
  invisible(g)
}


#' ggWrightMap internals
#'
#' @keywords internal
#'
#' @importFrom ggplot2 unit geom_histogram xlim ylab coord_flip scale_y_reverse geom_text scale_y_continuous
#'
#' @noRd
gg_wright_internal <- function(
  theta,
  b,
  binwidth = 0.5,
  color = "blue",
  size = 15,
  item.names,
  ylab.theta = "Respondent latent trait",
  ylab.b = "Item difficulty",
  rel_widths = c(1, 1)
) {
  if (missing(theta)) {
    stop("'theta' needs to be specified", call. = FALSE)
  }
  if (missing(b)) {
    stop("'theta' needs to be specified", call. = FALSE)
  }
  if (length(rel_widths) != 2) {
    stop(
      "'rel_widths' needs to be a numeric vector of length 2, e.g., 'c(1, 2)'.",
      call. = FALSE
    )
  }
  if (missing(item.names)) {
    ITEM.NAMES <- 1:length(b)
  } else {
    ITEM.NAMES <- item.names
  }

  df.theta <- data.frame(theta = theta)

  theta.cut.points <- seq(
    min(c(theta, b), na.rm = TRUE) - binwidth / 2,
    max(c(theta, b), na.rm = TRUE) + binwidth / 2,
    binwidth / 2
  )
  b.cut.points <- cut(b, theta.cut.points, include.lowest = TRUE)
  levels(b.cut.points) <- theta.cut.points[-length(theta.cut.points)] +
    diff(theta.cut.points) / 2
  b.cut.points <- as.numeric(paste(b.cut.points))

  df.b <- data.frame(item = as.character(ITEM.NAMES), b = b, y = b.cut.points)
  df.b$x <- 0
  for (i in unique(df.b$y)) {
    n <- nrow(df.b[df.b$y == i, ])
    df.b[df.b$y == i, "x"] <- 1:n
  }

  df.b$item <- as.character(df.b$item)
  maxn <- max(nchar(df.b$item))

  if (missing(item.names)) {
    while (any(nchar(df.b$item) < maxn)) {
      df.b$item <- ifelse(
        nchar(df.b$item) < maxn,
        paste0("0", df.b$item),
        df.b$item
      )
    }
  } else {
    df.b$item <- as.character(df.b$item)
    while (any(nchar(df.b$item) < maxn)) {
      df.b$item <- ifelse(
        nchar(df.b$item) < maxn,
        paste0(df.b$item, " "),
        df.b$item
      )
    }
  }

  df.b$item[df.b$x > 1] <- paste("|", df.b$item[df.b$x > 1])

  lim.x.min <- min(c(theta, b), na.rm = TRUE) - binwidth
  lim.x.max <- max(c(theta, b), na.rm = TRUE) + binwidth

  g1 <- ggplot(df.theta, aes(x = .data$theta)) +
    geom_histogram(
      binwidth = binwidth,
      fill = color,
      col = "black",
      na.rm = TRUE
    ) +
    xlim(lim.x.min, lim.x.max) +
    coord_flip() +
    scale_y_reverse() +
    xlab(ylab.theta) +
    theme_app(base_size = size) +
    theme(
      axis.title.x = element_blank(),
      axis.text.x = element_blank(),
      axis.ticks.x = element_blank()
    )

  g2 <- ggplot(df.b, aes(x = .data$x, y = .data$y, label = .data$item)) +
    geom_text(hjust = 0, vjust = 0.5, na.rm = TRUE) +
    scale_y_continuous(position = "right", limits = c(lim.x.min, lim.x.max)) +
    scale_x_continuous(limits = c(min(df.b$x), max(df.b$x) + 0.75)) +
    ylab(ylab.b) +
    theme_app(base_size = size) +
    theme(
      axis.title.x = element_blank(),
      axis.text.x = element_blank(),
      axis.ticks.x = element_blank()
    )

  list(g1, g2)
}