mederrRank: Bayesian Methods for Identifying the Most Harmful Medication
Errors
This package implements 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: 1) Bayesian hierarchical models 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: |
0.0.7 |
Depends: |
BB, methods, numDeriv, utils |
Published: |
2012-11-17 |
Author: |
Sergio Venturini, Jessica Myers |
Maintainer: |
Sergio Venturini <sergio.venturini at unibocconi.it> |
License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: |
no |
CRAN checks: |
mederrRank results |
Downloads: