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,
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.