EBGM Disproportionality Scores for Adverse Event Data Mining
Overview
An implementation of DuMouchel's (1999) doi:10.1080/00031305.1999.10474456 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.
- Improved numerical stability of hyperparameter calculations.
- Now requires 'numDeriv' package for calculating Hessian matrices.
- Removed 'param_lower' and 'param_upper' arguments from hyperEM().
- Added 'transformed' argument to the likelihood functions to allow for optimization on the log & logit scales.
- Added 'min_theta' & 'max_theta' arguments to Qn(), ebgm(), quantBisect(), & ebScores(). Alpha values now must also be between one half & twice the value of the corresponding beta values. Values outside these ranges are replaced by the limits.
- Updates to vignettes, data, examples, etc.
- Fixed NOTES regarding documentation.
From NEWS.md in the release
Install
Health
- OK13 OK2026-09-10
- NOTE14 NOTE2026-03-10
Documentation
- Help pages
- 20 (1 internal)includes a package overview page
- Examples that run
- 100%12 run in a plain check
- Exported functions with examples
- 79%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 70%
Downloads
Dependencies
Installing openEBGM adds 19 packages (8 with compiled code, 19 MB of source tarballs). Heaviest: ggplot2 6.0 MB, data.table 5.7 MB, isoband 1.5 MB.
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- 0.10.0Latest
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 0.9.12023-09-15 · diff ↗
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- 0.8.32020-03-02 · diff ↗
- RR 3.6.0 released · 2019-04-26
- 0.8.22019-04-25 · diff ↗
- 0.8.12019-02-28 · diff ↗
- 0.8.02019-01-30 · diff ↗
- 0.7.0
- 0.6.02018-05-21 · diff ↗
Package metadata
- First published
- 2017-05-05
- Total releases
- 13 / 9 yrs
- License
- GPL-2 | GPL-3 OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 90 KB / 2 files
- Download size
- 283 KB
Cite
Cite this package
Run in R for the authors' entry:
citation("openEBGM")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.32614/rj-2017-063.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-21, which the citation names so these numbers can be found later. More on citing and the projects behind them.