adjusted_effect computes the adjusted effect size
for a fitted RoBMA.reg and BiBMA.reg object.
adjusted_effect(
object,
conditional = FALSE,
output_scale = NULL,
probs = c(0.025, 0.975),
...
)pooled_effect returns a list of tables of class 'BayesTools_table'.
a fitted RoBMA object
show the conditional estimates (assuming that the
alternative is true). Defaults to FALSE. Only available for
type == "ensemble".
transform the meta-analytic estimates to a different
scale. Defaults to NULL which returns the same scale as the model was estimated on.
quantiles of the posterior samples to be displayed.
Defaults to c(.025, .975)
additional arguments
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).
pooled_effect()