polymirt

arguments to be passed to the
  <code><a href="/link/confmirt?package=mirt&version=0.3.0" rd-options="" data-mini-rdoc="mirt::confmirt">confmirt</a></code> estimation engine

<code>polymirt</code> fits an unconditional (exploratory)
  full-information maximum-likelihood factor analysis model
  to dichotomous and polychotomous data under the item
  response theory paradigm using Cai's (2010)
  Metropolis-Hastings Robbins-Monro algorithm. The function
  is currently depreciated and instead should be run by
  using the <code><a href="/link/confmirt?package=mirt&version=0.3.0" rd-options="" data-mini-rdoc="mirt::confmirt">confmirt</a></code> function.

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.

polymirt: Full-Information Item Factor Analysis for Mixed Data Formats

Description

Usage

Arguments

See Also