set_default_priors: Set default prior distributions

In RoBMA: Robust Bayesian Meta-Analyses

Set default prior distributions

Description

Set default prior distributions for RoBMA models.

Usage

set_default_priors(parameter, null = FALSE, rescale = 1)

Arguments

parameter	a character string specifying the parameter for which the prior distribution should be set. Available options are "effect", "heterogeneity", "bias", "hierarchical", "covariates", "factors".
null	a logical indicating whether the prior distribution should be set for the null hypothesis. Defaults to FALSE.
rescale	a numeric value specifying the re-scaling factor for the default prior distributions. Defaults to 1. Allows convenient re-scaling of prior distributions simultaneously.

Details

The default prior distributions corresponds to the specification of RoBMA-PSMA and RoBMA-regression outlined in \insertCitebartos2021no;textualRoBMA and \insertCitebartos2023robust;textualRoBMA.

Specifically, the prior distributions are:

For the alternative hypothesis:

• Effect: Normal distribution with mean 0 and standard deviation 1.

• Heterogeneity: Inverse gamma distribution with shape 1 and scale 0.15.

• Bias: A list of 8 prior distributions defining the publication bias adjustments:

  • Two-sided: Weight function with steps 0.05.

  • Two-sided: Weight function with steps 0.05 and 0.1.

  • One-sided: Weight function with steps 0.05.

  • One-sided: Weight function with steps 0.025 and 0.05.

  • One-sided: Weight function with steps 0.05 and 0.5.

  • One-sided: Weight function with steps 0.025, 0.05, and 0.5.

  • PET-type model with regression coefficient: Cauchy distribution with location 0 and scale 1.

  • PEESE-type model with regression coefficient: Cauchy distribution with location 0 and scale 5.

  All weight functions use a unit cumulative Dirichlet prior distribution on relative prior probabilities.

• Standardized continuous covariates: Normal distribution with mean 0 and standard deviation 0.25.

• Factors (via by-level differences from the grand mean): Normal distribution with mean 0 and standard deviation 0.25.

For the null hypothesis:

• Effect: Point distribution at 0.

• Heterogeneity: Point distribution at 0.

• Bias: No prior distribution.

• Standardized continuous covariates: Point distribution at 0.

• Factors (via by-level differences from the grand mean): Point distribution at 0.

The rescaling factor adjusts the width of the effect, heterogeneity, covariates, factor, and PEESE-style model prior distributions. PET-style and weight function prior distributions are scale-invariant.

Value

A prior distribution object or a list of prior distribution objects.

Examples

set_default_priors("effect")
set_default_priors("heterogeneity")
set_default_priors("bias")

RoBMA documentation built on April 12, 2025, 1:55 a.m.