vcov-method

vcov,SingleGroupClass-method

vcov,MixtureClass-method

vcov,MultipleGroupClass-method

vcov,MixedClass-method

vcov,DiscreteClass-method

Extract parameter variance covariance matrix

Analysis of discrete response data using
unidimensional and multidimensional item analysis models under the Item
Response Theory paradigm (Chalmers (2012) <doi:10.18637/jss.v048.i06>).
Exploratory and confirmatory item factor analysis models
are estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory
bi-factor and two-tier models are available for modeling item testlets using
dimension reduction EM algorithms, while multiple group analyses and
mixed effects designs are included for detecting differential item, bundle,
and test functioning, and for modeling item and person covariates.
Finally, latent class models such as the DINA, DINO, multidimensional latent class,
mixture, and zero-inflated response models are supported.

Phil Chalmers

mirt

Multidimensional Item Response Theory

Joshua Pritikin

Alexander Robitzsch

Mateusz Zoltak

KwonHyun Kim

Carl F. Falk

Adam Meade

Lennart Schneider

David King

Chen-Wei Liu

Ogreden Oguzhan

vcov-method function

<dl><dt>object</dt>
<dd>an object of class <code>SingleGroupClass</code>,
<code>MultipleGroupClass</code>, or <code>MixedClass</code></dd></dl>

Arguments

Extract parameter variance covariance matrix — vcov-method

<dl>

<dt>object</dt>
<dd>an object of class <code>SingleGroupClass</code>,
<code>MultipleGroupClass</code>, or <code>MixedClass</code></dd>

</dl>

Extract parameter variance covariance matrix

vcov-method: Extract parameter variance covariance matrix

Description

Usage

Arguments

References

Examples