Science

A 4 item data set borrowed from <code><a href="/link/ltm?package=mirt&version=0.4.1&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=0.4.1&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, rating
        scale 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.

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Science: Description of Science data

Description

Arguments