dcmstan

dcmstan-package

<img src="figures/logo.png?package=dcmstan&version=0.1.0" style="float: right" alt="logo" width="120">
Diagnostic classification models are psychometric models used to categorically estimate respondents mastery, or proficiency, on a set of predefined skills (Bradshaw, 2016, tools:::Rd_expr_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.

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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

Generate 'Stan' Code for Diagnostic Classification Models

Jeffrey Hoover

Auburn Jimenez

University of Kansas 

Institute of Education Sciences 

dcmstan-package function

Maintainer: W. Jake Thompson <a href="/link/wjakethompson%40gmail.com?package=dcmstan&version=0.1.0" data-mini-rdoc="dcmstan::wjakethompson@gmail.com">wjakethompson@gmail.com</a> (<a href="https://orcid.org/0000-0001-7339-0300">ORCID</a>)
Authors:<ul>
<li>Jeffrey Hoover <a href="/link/jeffrey.c.hoover%40gmail.com?package=dcmstan&version=0.1.0" data-mini-rdoc="dcmstan::jeffrey.c.hoover@gmail.com">jeffrey.c.hoover@gmail.com</a> (<a href="https://orcid.org/0000-0002-0276-0308">ORCID</a>)</li>
<li>Auburn Jimenez <a href="/link/auburn.jimenez34%40gmail.com?package=dcmstan&version=0.1.0" data-mini-rdoc="dcmstan::auburn.jimenez34@gmail.com">auburn.jimenez34@gmail.com</a> (<a href="https://orcid.org/0000-0002-7072-2960">ORCID</a>)</li>
</ul>Other contributors:<ul>
<li>University of Kansas [copyright holder]</li>
<li>Institute of Education Sciences [funder]</li>
</ul>

Author

<img src='figures/logo.png' style='float: right' alt='logo' width='120' />
Diagnostic classification models are psychometric models used to categorically estimate respondents mastery, or proficiency, on a set of predefined skills (Bradshaw, 2016, tools:::Rd_expr_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.

dcmstan: Generate 'Stan' Code for Diagnostic Classification Models — dcmstan-package

Maintainer: W. Jake Thompson <a href='mailto:wjakethompson@gmail.com'>wjakethompson@gmail.com</a> (<a href='https://orcid.org/0000-0001-7339-0300'>ORCID</a>)
Authors:<ul>
<li>Jeffrey Hoover <a href='mailto:jeffrey.c.hoover@gmail.com'>jeffrey.c.hoover@gmail.com</a> (<a href='https://orcid.org/0000-0002-0276-0308'>ORCID</a>)</li>
<li>Auburn Jimenez <a href='mailto:auburn.jimenez34@gmail.com'>auburn.jimenez34@gmail.com</a> (<a href='https://orcid.org/0000-0002-7072-2960'>ORCID</a>)</li>
</ul>

Other contributors:<ul>
<li>University of Kansas [copyright holder]</li>
<li>Institute of Education Sciences [funder]</li>
</ul>

dcmstan-package: dcmstan: Generate 'Stan' Code for Diagnostic Classification Models

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Author

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