sergioventurini/mederrRank: Bayesian Methods for Identifying the Most Harmful Medication Errors

Two distinct but related statistical approaches to the problem of identifying the combinations of medication error characteristics that are more likely to result in harm are implemented in this package: 1) a Bayesian hierarchical model with optimal Bayesian ranking on the log odds of harm, and 2) an empirical Bayes model that estimates the ratio of the observed count of harm to the count that would be expected if error characteristics and harm were independent. In addition, for the Bayesian hierarchical model, the package provides functions to assess the sensitivity of results to different specifications of the random effects distributions.

Getting started

Package details

AuthorSergio Venturini, Jessica Myers
MaintainerSergio Venturini <[email protected]>
LicenseGPL (>= 2) | file LICENSE
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
sergioventurini/mederrRank documentation built on May 29, 2018, 5:18 p.m.