plot.causal_estimates

Plot method for objects of class 'causal_estimates' to generate a boxplot of percent sample effective sample size (ESS) for a specific weighting method using bootstrap samples.

Implementation of integrative weighting approaches for multiple observational studies and causal inferences. The package features three weighting approaches, each representing a special case of the unified weighting framework, introduced by Guha and Li (2024) <doi:10.1093/biomtc/ujae070>, which includes an extension of inverse probability weights for data integration settings.

Subharup Guha

WMAP

Weighted Meta-Analysis with Pseudo-Populations

Mengqi Xu

Kashish Priyam

Yi Li

plot.causal_estimates function

<dl><dt>x</dt>
<dd>An object of class 'causal_estimates', the number of bootstrap samples <code>B</code> must be greater than 0.</dd>
<dt>...</dt>
<dd>Additional arguments including:<dl>
<dt>y_limit</dt>
<dd>The y-axis range. Default is <code>c(0,50)</code>.</dd></dl></dd><dt>color</dt>
<dd>The boxplot color. Default is "red".</dd>
</dl>

Arguments

Boxplot of percent ESS — plot.causal_estimates

<dl>

<dt>x</dt>
<dd>An object of class 'causal_estimates', the number of bootstrap samples <code>B</code> must be greater than 0.</dd>


<dt>...</dt>
<dd>Additional arguments including:<dl>
<dt>y_limit</dt>
<dd>The y-axis range. Default is <code>c(0,50)</code>.</dd>

<dt>color</dt>
<dd>The boxplot color. Default is "red".</dd>


</dl></dd>

</dl>

plot.causal_estimates: Boxplot of percent ESS

Description

Usage

Value

Arguments

Examples