In item response theory models , tests can be modelled through different models, in IRTpp each test calibrated parameters are in a simple data structure that is passed around the IRTpp functions.

UIRT models

In UIRT models, typically Rasch , 2PL and 3PL, in IRTpp the item parameters are usually these :

IRTpp functions must accept these parameters and transform them accordingly in the functions.

The UIRT model types accepted by IRTpp are :


Therefore functions are required to :

Simulation functions :


Model checking and transformation functions :

model.transform // Transform a model parameters ?
model.check // Check if a model is valid or not.
model.extract // Extract a named parameter from a parameter list.
as.model // Makes a irtpp model from whatever you try to throw at it.

Model and parameter list examples :

$a $b $c $model $dims

Generic Probability functions :

In spite of generalism , the probability function is completely flexible for all models. To calculate a probability we need the model, the parameters and the abilities.

Functions for estimation

irtpp : estimate item parameters
latent.traits : estimate individual parameters

SICSresearch/IRTpp documentation built on May 9, 2019, 11:11 a.m.