model_comp.bayesparobs

compute the model comparison measures

Contains functions performing Bayesian inference for meta-analytic and network meta-analytic models through Markov chain Monte Carlo algorithm. Currently, the package implements Hui Yao, Sungduk Kim, Ming-Hui Chen, Joseph G. Ibrahim, Arvind K. Shah, and Jianxin Lin (2015) <doi:10.1080/01621459.2015.1006065> and Hao Li, Daeyoung Lim, Ming-Hui Chen, Joseph G. Ibrahim, Sungduk Kim, Arvind K. Shah, Jianxin Lin (2021) <doi:10.1002/sim.8983>. For maximal computational efficiency, the Markov chain Monte Carlo samplers for each model, written in C++, are fine-tuned. This software has been developed under the auspices of the National Institutes of Health and Merck & Co., Inc., Kenilworth, NJ, USA.

Daeyoung Lim

metapack

Bayesian Meta-Analysis and Network Meta-Analysis

Ming-Hui Chen

Sungduk Kim

Joseph Ibrahim

Arvind Shah

Jianxin Lin

model_comp.bayesparobs function

<dl><dt>object</dt>
<dd>the output model from fitting a meta analysis/regression model</dd>
<dt>type</dt>
<dd>the type of model comparison measures; DIC or LPML</dd>
<dt>verbose</dt>
<dd>FALSE by default; If TRUE, then progress bar will appear</dd>
<dt>ncores</dt>
<dd>the number of CPU cores to use for parallel processing. It must not exceed the number of existing cores. If unspecified, it will default to 2 cores or the number of existing cores, whichever is smaller.</dd></dl>

Arguments

compute the model comparison measures — model_comp.bayesparobs

<dl>

<dt>object</dt>
<dd>the output model from fitting a meta analysis/regression model</dd>


<dt>type</dt>
<dd>the type of model comparison measures; DIC or LPML</dd>


<dt>verbose</dt>
<dd>FALSE by default; If TRUE, then progress bar will appear</dd>


<dt>ncores</dt>
<dd>the number of CPU cores to use for parallel processing. It must not exceed the number of existing cores. If unspecified, it will default to 2 cores or the number of existing cores, whichever is smaller.</dd>

</dl>

model_comp.bayesparobs: compute the model comparison measures

Description

Usage

Value

Arguments