meta_meat

Meta-analysis of the effectiveness of educational behavior interventions that
attempt to reduce meat consumption by appealing to animal welfare.

datasets

Meta-analyses can be compromised by studies' internal biases (e.g.,
confounding in nonrandomized studies) as well as by publication bias. This
package conducts sensitivity analyses for the joint effects of these biases
(per Mathur (2022) <doi:10.31219/osf.io/u7vcb>). These sensitivity analyses
address two questions: (1) For a given severity of internal bias across
studies and of publication bias, how much could the results change?; and
(2) For a given severity of publication bias, how severe would internal bias
have to be, hypothetically, to attenuate the results to the null or by a given
amount?

Peter Solymos

multibiasmeta

Sensitivity Analysis for Multiple Biases in Meta-Analyses

Maya Mathur

Mika Braginsky

meta_meat function

A data frame with 100 rows and 4 columns:<dl>
<dt>yi</dt>
<dd>Point estimate on log-risk ratio scale</dd><dt>vi</dt>
<dd>Variance of point estimate</dd><dt>cluster</dt>
<dd>Paper that contributed the point estimate</dd><dt>randomized</dt>
<dd>Logical indicating whether study was randomized</dd>
</dl>

Format

Meta-analysis about meat consumption — meta_meat

A data frame with 100 rows and 4 columns:<dl>
<dt>yi</dt>
<dd>Point estimate on log-risk ratio scale</dd>

<dt>vi</dt>
<dd>Variance of point estimate</dd>

<dt>cluster</dt>
<dd>Paper that contributed the point estimate</dd>

<dt>randomized</dt>
<dd>Logical indicating whether study was randomized</dd>


</dl>

meta_meat: Meta-analysis about meat consumption

Description

Usage

Arguments

Format

References