varenicline

<ul>
<li><code>study</code>: Study ID</li>
<li><code>d1</code>: Number of depression events in treatment group</li>
<li><code>n1</code>: Number of observations in treatment group</li>
<li><code>d0</code>: Number of depression events in control group</li>
<li><code>n0</code>: Number of observations in control group</li>
</ul>

datasets

Robust inference methods for fixed-effect and random-effects models of meta-analysis are implementable. The robust methods are developed using the density power divergence that is a robust estimating criterion developed in machine learning theory, and can effectively circumvent biases and misleading results caused by influential outliers. The density power divergence is originally introduced by Basu et al. (1998) <doi:10.1093/biomet/85.3.549>, and the meta-analysis methods are developed by Noma et al. (2022) <forthcoming>.

Hisashi Noma

robustmeta

Robust Inference for Meta-Analysis with Influential Outlying
Studies

Shonosuke Sugasawa

Toshi A. Furukawa

varenicline function

A data frame with 29 rows and 5 variables

varenicline: Thomas et al. (2015)'s varenicline data

Description

Usage

Arguments

Format

References