Hoppen2025

<p>The data set contains Cohen's d effect sizes, variances, and study
characteristics including outcome type, feedback level, social comparison type,
number of sessions, sample type, sample size, and country. The meta-analysis
examined social comparison as a behavior change technique across the behavioral
sciences hoppen2025metaRoBMA.</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

Hoppen2025 function

<p>A data.frame with 9 columns and 37 observations.</p>

Format

37 studies from a meta-analysis of social comparison as a behavior change technique
by hoppen2025meta;textualRoBMA — Hoppen2025

37 studies from a meta-analysis of social comparison as a behavior change technique
by hoppen2025meta;textualRoBMA

Hoppen2025: 37 studies from a meta-analysis of social comparison as a behavior change technique by hoppen2025meta;textualRoBMA

Description

Usage

Arguments

Value

Format

References