Multidimensional Item Response Theory
Description
Analysis of dichotomous and polytomous response data using
latent trait models under the Item Response Theory paradigm.
Includes univariate and multivariate one-, two-, three-, and
four-parameter logistic models, graded response models, rating
scale graded response models, generalized partial credit
models, nominal models, multiple choice models, and
multivariate partially-compensatory models. These can be used
in an exploratory or confirmatory manner with optional user
defined linear constraints. Exploratory models can be estimated
via quadrature or stochastic methods, a generalized
confirmatory bi-factor analysis is included, and confirmatory
models can be fit with a Metropolis-Hastings Robbins-Monro
algorithm which can include polynomial or product constructed
latent traits. Additionally, multiple group analysis may be
performed for unidimensional or multidimensional item response
models for detecting differential item functioning.