beta_binom_power: Analytic Assurance for Beta-Binomial Designs

In powerbrmsINLA: Bayesian Power Analysis Using 'brms' and 'INLA'

Analytic Assurance for Beta-Binomial Designs

Description

Computes assurance (power) using generating and audience Beta priors for a binomial count via a Beta-Binomial predictive distribution.

Usage

beta_binom_power(
  n,
  gen_prior_a,
  gen_prior_b,
  aud_prior_a,
  aud_prior_b,
  hdi_mass = 0.95,
  rope = NULL,
  hdi_max_width = NULL
)

Arguments

n	Sample size (number of trials).
gen_prior_a, gen_prior_b	Generating Beta prior parameters.
aud_prior_a, aud_prior_b	Audience Beta prior parameters.
hdi_mass	HDI mass (e.g., 0.95).
rope	Length-2 numeric vector for ROPE bounds, or NULL for max-width rule.
hdi_max_width	Positive width threshold for the HDI (used if rope=NULL).

Value

Assurance value between 0 and 1.

powerbrmsINLA documentation built on July 2, 2026, 5:07 p.m.