pooled_effect: Compute pooled effect size

In RoBMA: Robust Bayesian Meta-Analyses

Compute pooled effect size

Description

pooled_effect computes the pooled effect size for a fitted RoBMA.reg and BiBMA.reg object. Only available for models estimated using the spike-and-slab algorithm (i.e., algorithm = "ss").

Usage

pooled_effect(
  object,
  conditional = FALSE,
  output_scale = NULL,
  probs = c(0.025, 0.975),
  as_samples = FALSE
)

Arguments

object	a fitted RoBMA object
conditional	show the conditional estimates (assuming that the alternative is true). Defaults to FALSE. Only available for type == "ensemble".
output_scale	transform the meta-analytic estimates to a different scale. Defaults to NULL which returns the same scale as the model was estimated on.
probs	quantiles of the posterior samples to be displayed. Defaults to c(.025, .975)
as_samples	whether posterior samples instead of a summary table should be returned. Defaults to FALSE.

Details

The meta-regression specification results in the intercept corresponding to the adjusted effect estimate (i.e., adjusting for the effect of moderators). In case of moderators inbalance, the adjusted effect estimate might not be representative of the sample of studies. The pooled effect size function averages the effect size estimate across the moderators proportionately to the moderators levels observed in the data set. Note that there is no Bayes factor test for the presence of the pooled effect (the summary function provides the adjusted effect and the test for the presence of the adjusted effect).

The conditional estimate is calculated conditional on the presence of the adjusted effect (i.e., the intercept).

Value

pooled_effect returns a list of tables of class 'BayesTools_table'.

See Also

adjusted_effect()

RoBMA documentation built on Sept. 10, 2025, 5:08 p.m.