Weingarten2018

<p>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 memory 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.</p>

datasets

A framework for estimating ensembles of meta-analytic, meta-regression, and
multilevel models (assuming either presence or absence of the effect, heterogeneity,
publication bias, and moderators). The RoBMA framework uses Bayesian model-averaging to
combine the competing meta-analytic models into a model ensemble, weights
the posterior parameter distributions based on posterior model probabilities
and uses Bayes factors to test for the presence or absence of the
individual components (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 define a wide range of prior distributions for the effect size, heterogeneity,
publication bias (including selection models and PET-PEESE), and moderator components.
The package provides convenient functions for summary, visualizations, and fit diagnostics.

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

<p>A data.frame with 12 columns and 582 observations.</p>

Format

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

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

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

Description

Usage

Arguments

Value

Format

References