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
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
).
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)