Visualizations for item response models with Makie.jl
Author JuliaPsychometrics
3 Stars
Updated Last
5 Months Ago
Started In
October 2022


Stable Dev Build Status Coverage

This package provides plotting capabilities for item response models implementing the AbstractItemResponseModels.jl interface.

ItemResponsePlots.jl leverages the Makie.jl ecosystem, making it easy to extend basic figures and combine them in complex plots.


To install this package simply use julias package management system.

] add ItemResponsePlots

Getting started

After sucessfull installation you can start plotting results of your item response model. Prerequisite is a fitted ItemResponseModel, e.g. via RaschModels.jl.

using RaschModels

data = rand(0:1, 100, 5)
rasch = fit(RaschModel, data, CML())

Once the parameters are estimated, simply call your desired plotting function.

For example, item characteristic curves are implemented by the item_characteristic_curve function. To plot the item characteristic curve for the first item, call

item_characteristic_curve(rasch, 1)

All plotting functions in ItemResponsePlots.jl implement a variety of customization options. For details see the relevant plotting functions help page (e.g. ?item_characteristic_curve).

Available plots

Currently ItemResponsePlots supports low-level plotting recipes for

  • Item characteristic curves
  • Item information curves
  • Test characteristic / expected score curves
  • Test information curves

as well as high-level figures for

  • items (item characteristic curve + item information curve)
  • (sub)tests (expected scores + test information curve)

Used By Packages

No packages found.