Compute adjusted effect size

adjusted_effect computes the adjusted effect size for a fitted RoBMA.reg and BiBMA.reg object.

Usage

adjusted_effect(
  object,
  conditional = FALSE,
  output_scale = NULL,
  probs = c(0.025, 0.975),
  ...
)

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)

...

additional arguments

Value

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

Details

Non-default meta-regression specification (i.e., using treatment contrasts for predictors) might results in the intercept corresponding to the effect estimate in the baseline group. (i.e., adjusting for the effect of moderators). The adjusted effect size function averages the effect size estimate across the moderators levels. Note that there is no Bayes factor test for the presence of the adjusted effect (the summary function provides the effect estimate in the baseline group and the test for the presence of the effect in the baseline group if a treatment contrasts are specified).

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

See also

pooled_effect()