Compute estimated true effect sizes — true

true_effects computes the estimated true effect size for a fitted RoBMA object. These estimates correspond to the frequentist "Best Linear Unbiased Predictions (BLUPs)" (blup). Only available for normal-normal models estimated using the spike-and-slab algorithm (i.e., algorithm = "ss").

Usage

true_effects(
  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.

Value

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

Details

The true effect size estimates are computed under the normal likelihood. As such, they might not approximate the true effect size estimates under selection models well.

The conditional estimate is calculated conditional on the presence of the effect (in meta-analysis) or the intercept (in meta-regression).