IRT.marginal_posterior

IRT.marginal_posterior.din

IRT.marginal_posterior.gdina

IRT.marginal_posterior.mcdina

Computes marginal posterior distributions for fitted models in the
CDM package.

Functions for cognitive diagnosis modeling and multidimensional item response modeling
for dichotomous and polytomous item responses. This package enables the estimation of
the DINA and DINO model (Junker & Sijtsma, 2001, <doi:10.1177/01466210122032064>),
the multiple group (polytomous) GDINA model (de la Torre, 2011,
<doi:10.1007/s11336-011-9207-7>), the multiple choice DINA model (de la Torre, 2009,
<doi:10.1177/0146621608320523>), the general diagnostic model (GDM; von Davier, 2008,
<doi:10.1348/000711007X193957>), the structured latent class model (SLCA; Formann, 1992,
<doi:10.1080/01621459.1992.10475229>) and regularized latent class analysis
(Chen, Li, Liu, & Ying, 2017, <doi:10.1007/s11336-016-9545-6>).
See George, Robitzsch, Kiefer, Gross, and Uenlue (2017) <doi:10.18637/jss.v074.i02>
or Robitzsch and George (2019, <doi:10.1007/978-3-030-05584-4_26>)
for further details on estimation and the package structure.
For tutorials on how to use the CDM package see
George and Robitzsch (2015, <doi:10.20982/tqmp.11.3.p189>) as well as
Ravand and Robitzsch (2015).

Alexander Robitzsch

Cognitive Diagnosis Modeling

IRT.marginal_posterior function

<dl> <dt>object</dt>
<dd>Object of class <code>din</code>, <code>gdina</code>, <code>mcdina</code></dd><dt>dim</dt>
<dd>Numeric or character vector indicating dimensions of posterior distribution
which should be marginalized</dd> <dt>remove_zeroprobs</dt>
<dd>Logical indicating whether classes with zero probabilities should
be removed</dd> <dt>...</dt>
<dd>Further arguments to be passed</dd></dl>

Arguments

S3 Method for Computation of Marginal Posterior Distribution — IRT.marginal_posterior

<dl>

 <dt>object</dt>
<dd>Object of class <code>din</code>, <code>gdina</code>, <code>mcdina</code></dd>

<dt>dim</dt>
<dd>Numeric or character vector indicating dimensions of posterior distribution
which should be marginalized</dd>

 <dt>remove_zeroprobs</dt>
<dd>Logical indicating whether classes with zero probabilities should
be removed</dd>

 <dt>...</dt>
<dd>Further arguments to be passed</dd>

</dl>

IRT.marginal_posterior: S3 Method for Computation of Marginal Posterior Distribution

Description

Usage

Value

Arguments

See Also