Havrankova2025

<p>The data set contains effect sizes (percent increase in earnings), standard errors,
study identifiers, sample sizes, and the type of customer contact (no, some, or direct).
The meta-analysis examined the relationship between perceived beauty and professional success
havrankova2025beautyRoBMA.</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

Havrankova2025 function

<p>A data.frame with 5 columns and 1159 observations.</p>

Format

1159 effect sizes from a meta-analysis of beauty and professional success
by havrankova2025beauty;textualRoBMA — Havrankova2025

1159 effect sizes from a meta-analysis of beauty and professional success
by havrankova2025beauty;textualRoBMA

Havrankova2025: 1159 effect sizes from a meta-analysis of beauty and professional success by havrankova2025beauty;textualRoBMA

Description

Usage

Arguments

Value

Format

References