Quantitative methods for benefit-risk analysis help to condense complex decisions into a univariate metric describing the overall benefit relative to risk. One approach is to use the multi-criteria decision analysis framework (MCDA), as in Mussen, Salek, and Walker (2007) <doi:10.1002/pds.1435>. Bayesian benefit-risk analysis incorporates uncertainty through posterior distributions which are inputs to the benefit-risk framework. The brisk package provides functions to assist with Bayesian benefit-risk analyses, such as MCDA. Users input posterior samples, utility functions, weights, and the package outputs quantitative benefit-risk scores. The posterior of the benefit-risk scores for each group can be compared. Some plotting capabilities are also included.
| Version: | 0.1.1 |
| Imports: | dplyr (≥ 1.2), ggplot2 (≥ 3.3), hitandrun (≥ 0.5), purrr (≥ 0.3), rlang (≥ 1.0), tidyr (≥ 1.1) |
| Suggests: | knitr, fs (≥ 1.5), testthat (≥ 3.0.0), tibble (≥ 3.1), rmarkdown |
| Published: | 2026-03-04 |
| DOI: | 10.32614/CRAN.package.brisk |
| Author: | Richard Payne [aut, cre], Sai Dharmarajan [rev], Eli Lilly and Company [cph] |
| Maintainer: | Richard Payne <paynestatistics at gmail.com> |
| BugReports: | https://github.com/rich-payne/brisk/issues |
| License: | MIT + file LICENSE |
| URL: | https://rich-payne.github.io/brisk/ |
| NeedsCompilation: | no |
| Materials: | README, NEWS |
| CRAN checks: | brisk results |
| Reference manual: | brisk.html , brisk.pdf |
| Vignettes: |
Random Weights (source, R code) |
| Package source: | brisk_0.1.1.tar.gz |
| Windows binaries: | r-devel: brisk_0.1.1.zip, r-release: brisk_0.1.1.zip, r-oldrel: brisk_0.1.1.zip |
| macOS binaries: | r-release (arm64): brisk_0.1.1.tgz, r-oldrel (arm64): brisk_0.1.1.tgz, r-release (x86_64): brisk_0.1.1.tgz, r-oldrel (x86_64): brisk_0.1.1.tgz |
| Old sources: | brisk archive |
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