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openEBGM  

EBGM Disproportionality Scores for Adverse Event Data Mining
View on CRAN: Click here


Download and install openEBGM package within the R console
Install from CRAN:
install.packages("openEBGM")

Install from Github:
library("remotes")
install_github("cran/openEBGM")

Install by package version:
library("remotes")
install_version("openEBGM", "0.10.0")



Attach the package and use:
library("openEBGM")
Maintained by
John Ihrie
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-05-05
Latest Update: 2023-09-14
Description:
An implementation of DuMouchel's (1999) Bayesian data mining method for the market basket problem. Calculates Empirical Bayes Geometric Mean (EBGM) and posterior quantile scores using the Gamma-Poisson Shrinker (GPS) model to find unusually large cell counts in large, sparse contingency tables. Can be used to find unusually high reporting rates of adverse events associated with products. In general, can be used to mine any database where the co-occurrence of two variables or items is of interest. Also calculates relative and proportional reporting ratios. Builds on the work of the 'PhViD' package, from which much of the code is derived. Some of the added features include stratification to adjust for confounding variables and data squashing to improve computational efficiency. Includes an implementation of the EM algorithm for hyperparameter estimation loosely derived from the 'mederrRank' package.
How to cite:
John Ihrie (2017). openEBGM: EBGM Disproportionality Scores for Adverse Event Data Mining. R package version 0.10.0, https://cran.r-project.org/web/packages/openEBGM. Accessed 05 Oct. 2026.
Previous versions and publish date:
(2026-09-03 23:00), 0.1.0 (2017-05-05 20:09), 0.2.0 (2017-07-31 23:52), 0.3.0 (2017-11-15 23:26), 0.4.0 (2018-03-09 17:48), 0.5.0 (2018-04-02 18:15), 0.6.0 (2018-05-21 22:08), 0.7.0 (2018-08-16 20:00), 0.8.0 (2019-01-30 00:20), 0.8.1 (2019-02-28 21:10), 0.8.2 (2019-04-25 17:40), 0.8.3 (2020-03-02 21:20), 0.9.1 (2023-09-15 00:40)
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