openEBGM: An R Implementation of the Gamma-Poisson Shrinker Data Mining Model

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Authors Travis Canida, John Ihrie
Journal/Conference Name The R Journal
Paper Category
Paper Abstract We introduce the R package openEBGM, an implementation of the Gamma-Poisson Shrinker (GPS) model for identifying unexpected counts in large contingency tables using an empirical Bayes approach. The Empirical Bayes Geometric Mean (EBGM) and quantile scores are obtained from the GPS model estimates. openEBGM provides for the evaluation of counts using a number of different methods, including the model-based disproportionality scores, the relative reporting ratio (RR), and the proportional reporting ratio (PRR). Data squashing for computational efficiency and stratification for confounding variable adjustment are included. Application to adverse event detection is discussed.
Date of publication 2017
Code Programming Language R
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