openEBGM
EBGM Disproportionality Scores for Adverse Event Data Mining
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.
- Version0.9.1
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- openEBGM citation info
- Last release09/14/2023
Documentation
Team
John Ihrie
Sergio Venturini
Show author detailsRolesContributorIsmaïl Ahmed
Show author detailsRolesContributorJessica Myers
Show author detailsRolesContributorTravis Canida
Show author detailsRolesAuthorAntoine Poncet
Show author detailsRolesContributor
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- Imports2 packages
- Suggests6 packages