Learn R Programming

⚠️There's a newer version (1.44.0) of this package.Take me there.

mirt (version 0.3.0)

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.

Copy Link

Version

Install

install.packages('mirt')

Monthly Downloads

7,762

Version

0.3.0

License

GPL (>= 2)

Issues

Pull Requests

Stars

Forks

Maintainer

Phil Chalmers

Last Published

August 23rd, 2012

Functions in mirt (0.3.0)

SAT12

Description of SAT12 data
LSAT7

Description of LSAT7 data
confmirt

Confirmatory Full-Information Item Factor Analysis
bfactorClass-class

Class "bfactorClass"
bfactor

Full-Information Item Bi-factor Analysis
fscores

Methods for Function fscores
polymirt

Full-Information Item Factor Analysis for Mixed Data Formats
confmirtClass-class

Class "confmirtClass"
key2binary

Convert response patterns to binary data
confmirt.model

Specify model loadings
calcLogLik

Monte Carlo Log-Likelihood Calculation
Science

Description of Science data
mirt

Full-Information Item Factor Analysis (Multidimensional Item Response Theory)
simdata

Simulate response patterns
itemplot

Displays item surface and information plots
mirtClass-class

Class "mirtClass"
expand.table

Expand summary table of patterns and frequencies
mirt-package

Full information maximum likelihood estimation of IRT models.