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.

AuthorSergio Venturini, Jessica Myers
Date of publication2015-07-08 00:27:38
MaintainerSergio Venturini <sergio.venturini@unibocconi.it>
LicenseGPL (>= 2)
Version0.0.8

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Man pages

bayes.rank: Optimal Bayesian Ranking

bhm.constr.resamp: Markov Chain Monte Carlo Estimation (Step 2) of the Bayesian...

bhm.mcmc: Markov Chain Monte Carlo Estimation (Step 1) of the Bayesian...

bhm.resample: Resampling Transformation for the Markov Chain Monte Carlo...

dmixnegbinom: The Negative Binomial Mixture Distribution

dnegbinom: The Negative Binomial Distribution

dst: The Skewed Student t Distribution

EBGM: Geometric Mean of the Relative Risk Empirical Bayes Posterior...

llDiffD: Log-Likelihood Difference for the delta_j Parameters

llDiffT: Log-Likelihood Difference for the theta_i Parameters

logp: Negative Log-Posterior Function of the Bayesian Hierarchical...

logunpost: Unnormalized Marginal Posterior Distributions for k and eta

mederrData-class: Class "mederrData". Data Specification for Identifying the...

mederrFit-class: Class "mederrFit". Simulated Monte Carlo Chains (Step 1) for...

mederrRank-package: Bayesian Methods for Identifying the Most Harmful Medication...

mederrResample-class: Class "mederrResample". Simulated Monte Carlo Chains (Step 2)...

MEDMARX: Subset of the MEDMARX Data

mixnegbinom.em: Expectation-Maximization Algorithm for the Mixture of...

mixnegbinom.loglik: Log-Likelihood Function for the Mixture of Negative Binomial...

mixnegbinom.score: Log-Likelihood Score Function for the Mixture of Negative...

negbinom.em: Expectation-Maximization Algorithm for the Negative Binomial...

negbinom.loglik: Log-Likelihood Function for the Mixture of Negative Binomial...

negbinom.score: Log-Likelihood Score Function for the Negative Binomial...

plot-methods: Plot of Medication Error Data and Analysis

post.rep: Posterior Predictive Data Replications

p.value: Posterior Predictive Test statistics

rmixnegbinom: The Negative Binomial Mixture Distribution

simdata: Simulated Data

summary-methods: Summary of Medication Error Data and Analysis

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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