ItemResponseFunctions.jl implements basic functions for Item Response Theory models. It is built based on the interface designed in AbstractItemResponseModels.jl.
You can install ItemResponseFunctions.jl from the General package registry:
] add ItemResponseFunctions
ItemResponseFunctions.jl exports the following functions for Item Response Theory models:
irf
: The item response functioniif
: The item information functionexpected_score
: The expected score / test response functioninformation
: The test information function
Calling the function requires a model type M
, a person ability theta
and item parameters beta
.
For a simple 1-Parameter Logistic model,
using ItemResponseFunctions
beta = (; b = 0.5)
irf(OnePL, 0.0, beta, 1)
iif(OnePL, 0.0, beta, 1)
evaluates the item response function and item information function for response y
at ability value 0.0
for an item with difficulty 0.5
.
Given an array of item parameters (a test) and an ability value, the test response function and test information can be calculated by
betas = [
(; b = -0.3),
(; b = 0.25),
(; b = 1.0),
]
expected_score(OnePL, 0.0, betas)
information(OnePL, 0.0, betas)