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  "Description": "Quantitative methods for benefit-risk analysis help to\ncondense complex decisions into a univariate metric describing\nthe overall benefit relative to risk.  One approach is to use\nthe multi-criteria decision analysis framework (MCDA), as in\nMussen, Salek, and Walker (2007) <doi:10.1002/pds.1435>.\nBayesian benefit-risk analysis incorporates uncertainty through\nposterior distributions which are inputs to the benefit-risk\nframework.  The brisk package provides functions to assist with\nBayesian benefit-risk analyses, such as MCDA. Users input\nposterior samples, utility functions, weights, and the package\noutputs quantitative benefit-risk scores.  The posterior of the\nbenefit-risk scores for each group can be compared.  Some\nplotting capabilities are also included.",
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