example_data

The data set contains a binary outcome variable Y, a binary exposure A,
a binary mediator M, and two confounding variables (Z1 and Z2) for
300 individuals.

datasets

Performs parametric mediation analysis using the Bayesian g-formula approach for binary and continuous outcomes. The methodology is based on Comment (2018) <doi:10.5281/zenodo.1285275> and a demonstration of its application can be found at Yimer et al. (2022) <doi:10.48550/arXiv.2210.08499>.

Belay Birlie Yimer

BayesGmed

Bayesian Causal Mediation Analysis using 'Stan'

Mark Lunt

Marcus Beasley

 Gary J  Macfarlane

John McBeth

example_data function

<div class="section" id="example-data">
<h3><code>example_data</code></h3>
A data frame with 300 rows and 5 columns:<dl>
<dt>Z1, Z2</dt>
<dd>confounders</dd><dt>A</dt>
<dd>binary exposure</dd><dt>M</dt>
<dd>binary mediator</dd><dt>Y</dt>
<dd>binary outcome</dd>...</dl></div>

Format

example_data: A simulated data set for illustrating mediation analysis in BayesGmed. — example_data

<div class='section' id='example-data'>
<h3><code>example_data</code></h3>


A data frame with 300 rows and 5 columns:<dl>
<dt>Z1, Z2</dt>
<dd>confounders</dd>

<dt>A</dt>
<dd>binary exposure</dd>

<dt>M</dt>
<dd>binary mediator</dd>

<dt>Y</dt>
<dd>binary outcome</dd>

...

</dl>

</div>

example_data: example_data: A simulated data set for illustrating mediation analysis in BayesGmed.

Description

Usage

Arguments

Format

`example_data`