Plot Item Category Reference Profile from exametrika

This function takes exametrika LRAordinal or LRArated output as input and generates an Item Category Reference Profile (ICRP) plot using ggplot2. The plot shows response probability curves for each category across latent ranks. For each item, multiple lines represent the probability of selecting each response category.

Usage

plotICRP_gg(
  data,
  items = NULL,
  title = TRUE,
  colors = NULL,
  linetype = NULL,
  show_legend = TRUE,
  legend_position = "right"
)

Arguments

data: An object of class c("exametrika", "LRAordinal") or c("exametrika", "LRArated") from exametrika::LRA().
items: Integer vector specifying which items to plot. Default is all items.
title: Logical or character. If TRUE (default), display item labels as subplot titles. If FALSE, no titles. If a character string, use it as the main plot title.
colors: Character vector. Colors for category lines. If NULL (default), uses the package default palette.
linetype: Character or numeric vector. Line types for categories. If NULL (default), uses automatic line type assignment.
show_legend: Logical. If TRUE, display the legend showing category labels. Default is TRUE.
legend_position: Character. Position of the legend. One of "right" (default), "top", "bottom", "left", "none".

Value

A single ggplot object with faceted subplots for each item.

Details

The Item Category Reference Profile (ICRP) visualizes how the response probability for each category changes across latent ranks. Unlike ICBR which shows cumulative probabilities, ICRP shows the raw probability of selecting each specific category.

For an item with \(K\) categories (0, 1, ..., K-1), the ICRP shows:

Line for Cat0: P(response = 0 | rank)
Line for Cat1: P(response = 1 | rank)
...
Line for CatK: P(response = K | rank)

The sum of all probabilities at each rank equals 1.0, as they represent mutually exclusive response options.

Typically, higher ranks (higher ability) show higher probabilities for higher categories and lower probabilities for lower categories.

Examples

library(exametrika)
# \donttest{
result <- LRA(J15S3810, nrank = 4, dataType = "ordinal")

# Plot first 4 items
plot <- plotICRP_gg(result, items = 1:4)
plot


# Custom colors and title
plot <- plotICRP_gg(result,
  items = 1:6,
  title = "Item Category Reference Profile",
  colors = c("red", "blue", "green", "purple")
)
plot

# }