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.

Version: 0.1.0
Depends: BB, methods, numDeriv, utils
Imports: graphics, stats
Published: 2023-09-05
DOI: 10.32614/CRAN.package.mederrRank
Author: Sergio Venturini, Jessica Myers
Maintainer: Sergio Venturini <sergio.venturini at unicatt.it>
License: GPL-2 | GPL-3 | file LICENSE [expanded from: GPL (≥ 2) | file LICENSE]
NeedsCompilation: no
Materials: README
CRAN checks: mederrRank results

Documentation:

Reference manual: mederrRank.pdf

Downloads:

Package source: mederrRank_0.1.0.tar.gz
Windows binaries: r-devel: mederrRank_0.1.0.zip, r-release: mederrRank_0.1.0.zip, r-oldrel: mederrRank_0.1.0.zip
macOS binaries: r-release (arm64): mederrRank_0.1.0.tgz, r-oldrel (arm64): mederrRank_0.1.0.tgz, r-release (x86_64): mederrRank_0.1.0.tgz, r-oldrel (x86_64): mederrRank_0.1.0.tgz
Old sources: mederrRank archive

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