extendMPT

Adds more MCMC samples to the fitted MPT model.

User-friendly analysis of hierarchical multinomial processing tree (MPT)
models that are often used in cognitive psychology. Implements the latent-trait
MPT approach (Klauer, 2010) <DOI:10.1007/s11336-009-9141-0> and the beta-MPT
approach (Smith & Batchelder, 2010) <DOI:10.1016/j.jmp.2009.06.007> to model
heterogeneity of participants. MPT models are conveniently specified by an
.eqn-file as used by other MPT software and data are provided by a .csv-file
or directly in R. Models are either fitted by calling JAGS or by an MPT-tailored
Gibbs sampler in C++ (only for nonhierarchical and beta MPT models). Provides
tests of heterogeneity and MPT-tailored summaries and plotting functions.
A detailed documentation is available in Heck, Arnold, & Arnold (2018)
<DOI:10.3758/s13428-017-0869-7> and a tutorial on MPT modeling can be found
in Schmidt, Erdfelder, & Heck (2022) <DOI:10.31234/osf.io/gh8md>.

Daniel W. Heck

TreeBUGS

Hierarchical Multinomial Processing Tree Modeling

Nina R. Arnold

Denis Arnold

Alexander Ly

Marius Barth

extendMPT function

<dl><dt>fittedModel</dt>
<dd>a fitted <code>traitMPT</code> or <code>betaMPT</code></dd>
<dt>n.iter</dt>
<dd>Number of iterations per chain (including burnin samples). See
<code>run.jags</code> for details.</dd>
<dt>n.adapt</dt>
<dd>number of adaption samples to adjust MCMC sampler in JAGS. The
sampler will be more efficient if it is tuned well. However, MCMC sampling
will still give correct results even if the warning appears: "Adaptation
incomplete." (this just means that sampling efficiency could be better).</dd>
<dt>n.burnin</dt>
<dd>Number of samples for burnin (samples will not be stored and
removed from n.iter)</dd>
<dt>...</dt>
<dd>further arguments passed to <code>extend.jags</code> (see arguments
 listed in: run.jags).
When drawing more samples, JAGS requires an additional adaptation phase, in
 which the MCMC sampling procedure is adjusted. Note that the MCMC sampling
 will still give correct results even if the warning appears: "Adaptation
 incomplete." (this just means that sampling efficiency is not optimal).</dd></dl>

Arguments

Extend MCMC Sampling for MPT Model — extendMPT

<dl>

<dt>fittedModel</dt>
<dd>a fitted <code>traitMPT</code> or <code>betaMPT</code></dd>


<dt>n.iter</dt>
<dd>Number of iterations per chain (including burnin samples). See
<code>run.jags</code> for details.</dd>


<dt>n.adapt</dt>
<dd>number of adaption samples to adjust MCMC sampler in JAGS. The
sampler will be more efficient if it is tuned well. However, MCMC sampling
will still give correct results even if the warning appears: "Adaptation
incomplete." (this just means that sampling efficiency could be better).</dd>


<dt>n.burnin</dt>
<dd>Number of samples for burnin (samples will not be stored and
removed from n.iter)</dd>


<dt>...</dt>
<dd>further arguments passed to <code>extend.jags</code> (see arguments
 listed in: run.jags).
When drawing more samples, JAGS requires an additional adaptation phase, in
 which the MCMC sampling procedure is adjusted. Note that the MCMC sampling
 will still give correct results even if the warning appears: "Adaptation
 incomplete." (this just means that sampling efficiency is not optimal).</dd>

</dl>

extendMPT: Extend MCMC Sampling for MPT Model

Description

Usage

Arguments