Title: Multidimensional Item Response Theory
Description: Analysis of dichotomous and polychotomous response data
paradigm. Includes the multivariate two- and three-parameter
logistic models, confirmatory bifactor analysis, and polytomous
confirmatory and exploratory item response models.
Depends: R (>= 2.10), methods, psych, GPArotation, mvtnorm

logistic models, confirmatory bifactor analysis, polytomous
confirmatory and exploratory item response models, and
paritally compensatory item response modeling in conjunction
Depends: R (>= 2.10), methods, lattice, psych, GPArotation, mvtnorm

partially-compensatory item response modeling in conjunction

paradigm.  Includes the multivariate two- and three-parameter

Description: Analysis of dichotomous and polychotomous response data using latent
trait models under the Item Response Theory paradigm.
Includes the multivariate two- and three-parameter logistic
models, confirmatory bifactor analysis, polytomous confirmatory
and exploratory item response models, and partially-compensatory item response
modeling in conjunction with other IRT models.
Depends: R (>= 2.10), methods, lattice, psych, GPArotation, mvtnorm,

Depends: R (>= 2.10), methods, lattice, psych, MASS, GPArotation,
Collate: 'bfactor.R' 'expand.table.R' 'itemplot.R' 'key2binary.R'
'misc.R' 'logLik.R' 'fscores.R' 'mirt-package.R' 'confmirt.R'

exploratory and confirmatory item response models which may
include polynomial or product constructed factors, and
'mirt.R' 'polymirt.R' 'simdata.R' 'confmirt.model.R' 'LSAT7.R'

Imports: lattice, psych, MASS, GPArotation, mvtnorm, Matrix

Depends: R (>= 2.14), stats4, lattice, MASS, methods
Imports: stats4, psych, GPArotation, mvtnorm, Rcpp, plink, Matrix

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
Imports: stats4, psych, GPArotation, mvtnorm, Rcpp, Matrix
'fscores.R' 'mirt-package.R' 'confmirt.R' 'mirt.R' 'polymirt.R'