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PVM is an R package containing a wide variety of methods used in the field of pharmacovigilance for discovering 'interesting' drug-adverse event pairs from spontaneous reporting data.

The methods currently implemented are:

1. the reporting odds ratio (ROR), see R/ROR.R;

2. Yule's Q, see R/YulesQ.R;

3. the proportional relative risk (PRR), see R/PRR.R;

4. the relative report rate (RRR), see R/RRR.R;

5. the reporting Fisher's exact test (RFET) and the mid-p-value test (midRFET), see R/fisherExactTest.R;

6. the chi-squared test (with and without Yates' correction for continuity), see R/chi2Test.R;

7. the binomial likelihood ratio test, see R/logLikelihoodRatioBinomial.R;

8. the test of the Poisson mean, see R/PoissonTest.R;

9. the Bayesian confidence propagation neural network (BCPNN), see R/BCPNN.R;

10. the Gamma Poisson shrinker (GPS), see R/GPS.R, and

11. the LASSO, see R/LASSO.R

To install, simply type in R

devtools::install_github("bips-hb/pvm")

We gratefully acknowledge the financial support from the innovation fund (“Innovationsfonds”) of the Federal Joint Committee in Germany (grant number: 01VSF16020).

Please cite

Adverse Drug Reaction or Innocent Bystander? A Systematic Comparison of Statistical Discovery Methods for Spontaneous Reporting Systems
L.J. Dijkstra, M. Garling, R. Foraita & I. Pigeot
Pharmacoepidemiology and Drug Safety (2020)
DOI:10.1002/PDS.4970

Louis Dijkstra
Leibniz Institute for Prevention Research & Epidemiology
E-mail: dijkstra (at) leibniz-bips.de