MHTrajectoryR
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.
- Version1.0.1
- R version≥ 2.10
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Last release04/05/2016
Team
Mohammed Sedki
Matthieu Marbac and Mohammed Sedki
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- Depends1 package
- Imports2 packages