boot.mirt

an estimated object from <code>mirt</code>,
  <code>bfactor</code>, or <code>multipleGroup</code>

number of draws to use (passed to the
  <code>boot()</code> function)

logical; return the estimated object
  from the <code>boot</code> package? If <code>FALSE</code> the
  estimated model is returned with the bootstrapped
  standard errors

return.boot

additional arguments to be passed on to
  <code>boot(...)</code>

Given an internal mirt object estimate the bootstrapped
  standard errors. It may be beneficial to run the
  computations using multicore architecture (e.g., the
  <code>parallel</code> package).

bootstrapped

errors

standard

Analysis of dichotomous and polytomous response data using
        latent trait models under the Item Response Theory paradigm.
        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 may include
        polynomial or product constructed latent traits. Multiple group
        analysis and mixed effects designs may be performed for
        unidimensional or multidimensional item response models for
        detecting differential item functioning and modelling item and
        person covariates.

boot.mirt: Calculate bootstrapped standard errors for estimated models

Description

Usage

Arguments

Examples