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) <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.
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
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
NeedsCompilation: no
Packaged: 2026-03-04 19:56:17 UTC; c263386
Author: Richard Payne [aut, cre],
  Sai Dharmarajan [rev],
  Eli Lilly and Company [cph]
Maintainer: Richard Payne <paynestatistics@gmail.com>
Repository: CRAN
Date/Publication: 2026-03-04 20:10:02 UTC
Built: R 4.6.0; ; 2026-04-26 16:48:45 UTC; unix
