MixtureClass-class

Defines the object returned from <code>multipleGroup</code> when estimated with
mixture distributions.

classes

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 IRT models, 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

MixtureClass-class function

<dl>
 <dt><code>Call</code>:</dt>
<dd>function call</dd></dl> <dt><code>Data</code>:</dt>
<dd>list of data, sometimes in different forms</dd> <dt><code>Options</code>:</dt>
<dd>list of estimation options</dd> <dt><code>Fit</code>:</dt>
<dd>a list of fit information</dd> <dt><code>Model</code>:</dt>
<dd>a list of model-based information</dd> <dt><code>ParObjects</code>:</dt>
<dd>a list of the S4 objects used during estimation</dd> <dt><code>OptimInfo</code>:</dt>
<dd>a list of arguments from the optimization process</dd> <dt><code>Internals</code>:</dt>
<dd>a list of internal arguments for secondary computations (inspecting this
 object is generally not required)</dd> <dt><code>vcov</code>:</dt>
<dd>a matrix represented the asymptotic covariance matrix of the parameter estimates</dd> <dt><code>time</code>:</dt>
<dd>a data.frame indicating the breakdown of computation times in seconds</dd>

Slots

<dl>
 <dt>coef</dt>
<dd><code>signature(object = "MixtureClass")</code></dd></dl> <dt>print</dt>
<dd><code>signature(x = "MixtureClass")</code></dd> <dt>show</dt>
<dd><code>signature(object = "MixtureClass")</code></dd> <dt>anova</dt>
<dd><code>signature(object = "MixtureClass")</code></dd>

Methods

Phil Chalmers <a href="/link/rphilip.chalmers%40gmail.com?package=mirt&version=1.42" data-mini-rdoc="mirt::rphilip.chalmers@gmail.com">rphilip.chalmers@gmail.com</a>

Author

Class "MixtureClass" — MixtureClass-class

<dl>
 <dt><code>Call</code>:</dt>
<dd>function call</dd>

 <dt><code>Data</code>:</dt>
<dd>list of data, sometimes in different forms</dd>

 <dt><code>Options</code>:</dt>
<dd>list of estimation options</dd>

 <dt><code>Fit</code>:</dt>
<dd>a list of fit information</dd>

 <dt><code>Model</code>:</dt>
<dd>a list of model-based information</dd>

 <dt><code>ParObjects</code>:</dt>
<dd>a list of the S4 objects used during estimation</dd>

 <dt><code>OptimInfo</code>:</dt>
<dd>a list of arguments from the optimization process</dd>

 <dt><code>Internals</code>:</dt>
<dd>a list of internal arguments for secondary computations (inspecting this
 object is generally not required)</dd>

 <dt><code>vcov</code>:</dt>
<dd>a matrix represented the asymptotic covariance matrix of the parameter estimates</dd>

 <dt><code>time</code>:</dt>
<dd>a data.frame indicating the breakdown of computation times in seconds</dd>


</dl>

<dl>
 <dt>coef</dt>
<dd><code>signature(object = "MixtureClass")</code></dd>

 <dt>print</dt>
<dd><code>signature(x = "MixtureClass")</code></dd>

 <dt>show</dt>
<dd><code>signature(object = "MixtureClass")</code></dd>

 <dt>anova</dt>
<dd><code>signature(object = "MixtureClass")</code></dd>


</dl>

Phil Chalmers <a href='mailto:rphilip.chalmers@gmail.com'>rphilip.chalmers@gmail.com</a>

MixtureClass-class: Class "MixtureClass"

Description

Arguments

Slots

Methods

Author

References