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

Provides tools for Bayesian power analysis and assurance calculations using the statistical frameworks of 'brms' and 'INLA'. Includes simulation-based approaches, support for multiple decision rules (direction, threshold, ROPE), sequential designs, and visualisation helpers. Methods are based on Kruschke (2014, ISBN:9780124058880) "Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan", O'Hagan & Stevens (2001) <doi:10.1177/0272989X0102100307> "Bayesian Assessment of Sample Size for Clinical Trials of Cost-Effectiveness", Kruschke (2018) <doi:10.1177/2515245918771304> "Rejecting or Accepting Parameter Values in Bayesian Estimation", Rue et al. (2009) <doi:10.1111/j.1467-9868.2008.00700.x> "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations", and Bürkner (2017) <doi:10.18637/jss.v080.i01> "brms: An R Package for Bayesian Multilevel Models using Stan".

Package details

AuthorTony Myers [aut, cre] (ORCID: <https://orcid.org/0000-0003-4516-4829>)
MaintainerTony Myers <admyers@aol.com>
LicenseMIT + file LICENSE
Version1.3.0
URL https://github.com/Tony-Myers/powerbrmsINLA
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("powerbrmsINLA")

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