summary_heterogeneity

Computes the prediction interval, the absolute
heterogeneity (tau, tau^2), and relative measures of heterogeneity
(I^2, H^2) for a fitted RoBMA object.

A framework for estimating ensembles of meta-analytic and meta-regression 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>). 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

summary_heterogeneity function

<dl><dt>object</dt>
<dd>a fitted RoBMA object</dd>
<dt>type</dt>
<dd>whether to show the overall RoBMA results (<code>"ensemble"</code>)
or a detailed summary of the individual models (<code>"individual"</code>).
Can be abbreviated to first letters.</dd>
<dt>conditional</dt>
<dd>show the conditional estimates (assuming that the
alternative is true). Defaults to <code>FALSE</code>. Only available for
<code>type == "ensemble"</code>.</dd>
<dt>output_scale</dt>
<dd>transform the meta-analytic estimates to a different
scale. Defaults to <code>NULL</code> which returns the same scale as the model was estimated on.</dd>
<dt>probs</dt>
<dd>quantiles of the posterior samples to be displayed.
Defaults to <code>c(.025, .975)</code></dd>
<dt>short_name</dt>
<dd>whether priors names should be shortened to the first
(couple) of letters. Defaults to <code>FALSE</code>.</dd>
<dt>remove_spike_0</dt>
<dd>whether spike prior distributions with location at zero should
be omitted from the summary. Defaults to <code>FALSE</code>.</dd></dl>

Arguments

Summarizes heterogeneity of a RoBMA model — summary_heterogeneity

<dl>

<dt>object</dt>
<dd>a fitted RoBMA object</dd>


<dt>type</dt>
<dd>whether to show the overall RoBMA results (<code>"ensemble"</code>)
or a detailed summary of the individual models (<code>"individual"</code>).
Can be abbreviated to first letters.</dd>


<dt>conditional</dt>
<dd>show the conditional estimates (assuming that the
alternative is true). Defaults to <code>FALSE</code>. Only available for
<code>type == "ensemble"</code>.</dd>


<dt>output_scale</dt>
<dd>transform the meta-analytic estimates to a different
scale. Defaults to <code>NULL</code> which returns the same scale as the model was estimated on.</dd>


<dt>probs</dt>
<dd>quantiles of the posterior samples to be displayed.
Defaults to <code>c(.025, .975)</code></dd>


<dt>short_name</dt>
<dd>whether priors names should be shortened to the first
(couple) of letters. Defaults to <code>FALSE</code>.</dd>


<dt>remove_spike_0</dt>
<dd>whether spike prior distributions with location at zero should
be omitted from the summary. Defaults to <code>FALSE</code>.</dd>

</dl>

summary_heterogeneity: Summarizes heterogeneity of a RoBMA model

Description

Usage

Value

Arguments