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".
| Version: |
1.0.0 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
brms (≥ 2.19.0), dplyr (≥ 1.1.0), ggplot2 (≥ 3.4.0), rlang (≥ 1.1.0), tibble (≥ 3.2.0), scales (≥ 1.2.0), viridisLite (≥ 0.4.0), stats, utils, magrittr (≥ 2.0.0) |
| Suggests: |
INLA (≥ 22.05.07), testthat (≥ 3.0.0), rmarkdown, MASS, circular, sn |
| Published: |
2025-09-01 |
| Author: |
Tony Myers  [aut,
cre] |
| Maintainer: |
Tony Myers <admyers at aol.com> |
| BugReports: |
https://github.com/Tony-Myers/powerbrmsINLA/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/Tony-Myers/powerbrmsINLA |
| NeedsCompilation: |
no |
| Additional_repositories: |
https://inla.r-inla-download.org/R/stable |
| Materials: |
README |
| CRAN checks: |
powerbrmsINLA results |
Documentation:
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