is.RoBMA

is.RoBMA.reg

is.NoBMA

is.NoBMA.reg

is.BiBMA

Reports whether x is a RoBMA object

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

is.RoBMA function

<dl><dt>x</dt>
<dd>an object to test</dd></dl>

Arguments

Reports whether x is a RoBMA object — is.RoBMA

<dl>

<dt>x</dt>
<dd>an object to test</dd>

</dl>

Reports whether x is a RoBMA object

is.RoBMA: Reports whether x is a RoBMA object

Description

Usage

Value

Arguments