bhpm.Package: Bayesian Hierarchical Possion Models for Mulitple Grouped...

In bhpm: Bayesian Hierarchical Poisson Models for Multiple Grouped Outcomes with Clustering

Description

This package implements Bayesian Hierarchical models for the detection of differences in rates of outcomes for multiple treatments for clustered observations using groupings of outcomes.

Details

The methods implemented use assumed groupings of outcomes to detect differences in the occurrence of the outcome for different treatments. Methods based on Bayesian Hierarchical models are provided. The methods are extension of those described in Carragher (2017) for multiple treatments and clusters.

Author(s)

R. Carragher<[e-mail]; [e-mail]>

References

Carragher R. Detection of Safety Signals in Randomised Controlled Trials. PhD thesis. University of Strathclyde, 2017 <https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.736866>.

bhpm documentation built on April 1, 2020, 5:09 p.m.