Package: brisk Title: Bayesian Benefit Risk Analysis Version: 0.1.1 Authors@R: c(person(given = "Richard", family = "Payne", role = c("aut", "cre"), email = "paynestatistics@gmail.com"), person(given = "Sai", family = "Dharmarajan", role = "rev", email = c("sai.dharmarajan@fda.hhs.gov", "shdharma@umich.edu")), person(family = "Eli Lilly and Company", role = "cph")) Description: 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) . 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. License: MIT + file LICENSE Imports: dplyr (>= 1.2), ggplot2 (>= 3.3), hitandrun (>= 0.5), purrr (>= 0.3), rlang (>= 1.0), tidyr (>= 1.1) Encoding: UTF-8 Roxygen: list(markdown = TRUE) RoxygenNote: 7.3.3 Suggests: knitr, fs (>= 1.5), testthat (>= 3.0.0), tibble (>= 3.1), rmarkdown Config/testthat/edition: 3 VignetteBuilder: knitr URL: https://rich-payne.github.io/brisk/ BugReports: https://github.com/rich-payne/brisk/issues Config/pak/sysreqs: libgmp3-dev libicu-dev Repository: https://rich-payne.r-universe.dev Date/Publication: 2026-03-03 18:39:20 UTC RemoteUrl: https://github.com/rich-payne/brisk RemoteRef: HEAD RemoteSha: 8afe94c9af11eee7e0953a62b385268ad3537971 NeedsCompilation: no Packaged: 2026-06-11 07:03:02 UTC; root Author: Richard Payne [aut, cre], Sai Dharmarajan [rev], Eli Lilly and Company [cph] Maintainer: Richard Payne