loo_compare.loo

Method for comparing RoBMA-targeted <code>loo</code> or <code>waic</code>
objects directly.

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

loo_compare.loo function

<dl><dt>x</dt>
<dd>a RoBMA-targeted <code>loo</code> or <code>waic</code> object (the first model
to compare).</dd>
<dt>...</dt>
<dd>additional RoBMA-targeted <code>loo</code>/<code>waic</code> or <code>brma</code>
objects to compare.</dd>
<dt>unit</dt>
<dd>output/deletion unit used when extracting LOO from brma objects.</dd></dl>

Arguments

Compare loo Objects Using LOO — loo_compare.loo

<dl>

<dt>x</dt>
<dd>a RoBMA-targeted <code>loo</code> or <code>waic</code> object (the first model
to compare).</dd>


<dt>...</dt>
<dd>additional RoBMA-targeted <code>loo</code>/<code>waic</code> or <code>brma</code>
objects to compare.</dd>


<dt>unit</dt>
<dd>output/deletion unit used when extracting LOO from brma objects.</dd>

</dl>

loo_compare.loo: Compare loo Objects Using LOO

Description

Usage

Value

Arguments

See Also