MHTrajectoryR1.0.1 package

Bayesian Model Selection in Logistic Regression for the Detection of Adverse Drug Reactions

Spontaneous adverse event reports have a high potential for detecting adverse drug reactions. However, due to their dimension, the analysis of such databases requires statistical methods. We propose to use a logistic regression whose sparsity is viewed as a model selection challenge. Since the model space is huge, a Metropolis-Hastings algorithm carries out the model selection by maximizing the BIC criterion.

  • Maintainer: Mohammed Sedki
  • License: GPL (>= 2)
  • Last published: 2016-04-05