brisk

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.

Downloads

Trend: +11.1% (30d vs prior 30d)

CRAN Check Status

Check History

Running examples in ‘brisk-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: benefit
> ### Title: Bayesian Benefit Risk
> ### Aliases: benefit risk br mcda
> 
> ### ** Examples
> 
>
...[truncated]...
:signal_abort(cnd, .file)
 11. │     └─base::signalCondition(cnd)
 12. └─dplyr (local) `<fn>`(`<dpl:::__>`)
 13.   └─dplyr (local) handler(cnd)
 14.     └─rlang::abort(message, class = error_class, parent = parent, call = error_call)
Execution halted

Dependency Network

Version History