prior_tibble

When specifying prior distributions, it is often useful to see which
parameters are included in a given model. Using the Q-matrix and type of
diagnostic model to estimated, we can create a list of all included
parameters for which a prior can be specified.

Diagnostic classification models are psychometric models used
to categorically estimate respondents mastery, or proficiency, on a
set of predefined skills (Bradshaw, 2016,
<doi:10.1002/9781118956588.ch13>). Diagnostic models can be estimated
with 'Stan'; however, the necessary scripts can be long and
complicated. This package automates the creation of 'Stan' scripts for
diagnostic classification models. Specify different types of
diagnostic models, define prior distributions, and automatically
generate the necessary 'Stan' code for estimating the model.

W. Jake Thompson

dcmstan

Generate 'Stan' Code for Diagnostic Classification Models

Jeffrey Hoover

Auburn Jimenez

University of Kansas 

Institute of Education Sciences 

prior_tibble function

<dl><dt>x</dt>
<dd>A model specification (e.g., <code>dcm_specify()</code>, measurement model
(e.g., <code>lcdm()</code>), or structural model (e.g., <code>unconstrained()</code>) object.</dd>
<dt>...</dt>
<dd>Additional arguments passed to methods. See details.</dd></dl>

Arguments

Coerce a dcmprior object to a tibble — prior_tibble

<dl>

<dt>x</dt>
<dd>A model specification (e.g., <code>dcm_specify()</code>, measurement model
(e.g., <code>lcdm()</code>), or structural model (e.g., <code>unconstrained()</code>) object.</dd>


<dt>...</dt>
<dd>Additional arguments passed to methods. See details.</dd>

</dl>

prior_tibble: Coerce a dcmprior object to a tibble

Description

Usage

Value

Arguments

Details

Examples