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brisk  

Bayesian Benefit Risk Analysis
View on CRAN: Click here


Download and install brisk package within the R console
Install from CRAN:
install.packages("brisk")

Install from Github:
library("remotes")
install_github("cran/brisk")

Install by package version:
library("remotes")
install_version("brisk", "0.1.0")



Attach the package and use:
library("brisk")
Maintained by
Richard Payne
[Scholar Profile | Author Map]
First Published: 2022-08-31
Latest Update: 2022-08-31
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.
How to cite:
Richard Payne (2022). brisk: Bayesian Benefit Risk Analysis. R package version 0.1.0, https://cran.r-project.org/web/packages/brisk. Accessed 03 May. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited brisk R package
View brisk citation profile
Other R packages that brisk depends, imports, suggests or enhances
Complete documentation for brisk
Functions, R codes and Examples using the brisk R package
Some associated functions: br . br_group . pbrisk . plot.brisk_br . plot_utility . sim_weights . summary.brisk_br . 
Some associated R codes: assert.R . benefit_risk.R . imports.R . plot.R . weights.R .  Full brisk package functions and examples
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