Science

A 4 item data set borrowed from <code><a href="/link/ltm?package=mirt&version=0.3.0&to=ltm" rd-options="ltm" data-mini-rdoc="ltm::ltm">ltm</a></code>
  package, first example of the <code><a href="/link/grm?package=mirt&version=0.3.0&to=ltm" rd-options="ltm" data-mini-rdoc="ltm::grm">grm</a></code>
  function. See more complete documentation therein.

datasets

data

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.

Science: Description of Science data

Description

Arguments