Weingarten2018

The data set contains correlation coefficients between the manipulation
and outcome variable (r_xy), sample sizes (N), and various study characteristics
including publication status, country (USA vs. other), number of few and many
examples requested, whether the trial targeted episodic memory, paradigm type (standard vs. other),
dataset type (proximal vs. distal), and mediation variables (r_xm, r_my).
The meta-analysis examined whether subjective ease mediates the ease-of-retrieval effect,
where participants list either few or many examples and then make judgments
weingarten2018doesRoBMA.

datasets

A framework for Bayesian meta-analysis, including model estimation,
prior specification, model comparison, prediction, summaries, visualizations,
and diagnostics. The package fits single and model-averaged meta-analytic,
meta-regression, multilevel, publication bias adjusted, and generalized linear
mixed models The model-averaged meta-analytic models combine competing models
based on their predictive performance, weight inference by posterior model probabilities,
and test model components using Bayes factors (e.g., effect vs. no effect;
Bartoš et al., 2022, <doi:10.1002/jrsm.1594>; Maier, Bartoš & Wagenmakers, 2022,
<doi:10.1037/met0000405>; Bartoš et al., 2025, <doi:10.1037/met0000737>).
Users can specify flexible prior distributions for effect sizes, heterogeneity,
publication bias (including selection models and PET-PEESE), and moderators.

Franti<c5><a1>ek Barto<c5><a1>

RoBMA

Robust Bayesian Meta-Analyses

František Bartoš

Maximilian Maier

Eric-Jan Wagenmakers

Joris Goosen

Matthew Denwood

Martyn Plummer

Weingarten2018 function

A data.frame with 12 columns and 582 observations:<dl>
<dt><code>r_xy</code></dt>
<dd>Correlation between manipulation and outcome.</dd><dt><code>N</code></dt>
<dd>Sample size.</dd><dt><code>paper_id</code></dt>
<dd>Paper identifier.</dd><dt><code>published</code></dt>
<dd>Publication-status indicator.</dd><dt><code>USA</code></dt>
<dd>Whether the study was conducted in the USA.</dd><dt><code>number_of_few</code></dt>
<dd>Number of examples in the few-examples condition.</dd><dt><code>number_of_many</code></dt>
<dd>Number of examples in the many-examples condition.</dd><dt><code>episodic_memory</code></dt>
<dd>Whether the trial targeted episodic memory.</dd><dt><code>standard_paradigm</code></dt>
<dd>Whether the standard paradigm was used.</dd><dt><code>proximal_dataset</code></dt>
<dd>Whether the data set was proximal.</dd><dt><code>r_xm</code></dt>
<dd>Correlation between manipulation and mediator.</dd><dt><code>r_my</code></dt>
<dd>Correlation between mediator and outcome.</dd>
</dl>

Format

582 effect sizes examining the ease-of-retrieval effect
from a meta-analysis by weingarten2018does;textualRoBMA — Weingarten2018

A data.frame with 12 columns and 582 observations:<dl>
<dt><code>r_xy</code></dt>
<dd>Correlation between manipulation and outcome.</dd>

<dt><code>N</code></dt>
<dd>Sample size.</dd>

<dt><code>paper_id</code></dt>
<dd>Paper identifier.</dd>

<dt><code>published</code></dt>
<dd>Publication-status indicator.</dd>

<dt><code>USA</code></dt>
<dd>Whether the study was conducted in the USA.</dd>

<dt><code>number_of_few</code></dt>
<dd>Number of examples in the few-examples condition.</dd>

<dt><code>number_of_many</code></dt>
<dd>Number of examples in the many-examples condition.</dd>

<dt><code>episodic_memory</code></dt>
<dd>Whether the trial targeted episodic memory.</dd>

<dt><code>standard_paradigm</code></dt>
<dd>Whether the standard paradigm was used.</dd>

<dt><code>proximal_dataset</code></dt>
<dd>Whether the data set was proximal.</dd>

<dt><code>r_xm</code></dt>
<dd>Correlation between manipulation and mediator.</dd>

<dt><code>r_my</code></dt>
<dd>Correlation between mediator and outcome.</dd>


</dl>

Weingarten2018: 582 effect sizes examining the ease-of-retrieval effect from a meta-analysis by weingarten2018does;textualRoBMA

Description

Usage

Arguments

Format

References