A Bayesian Approach for the Analysis of Panel-Count Data with Dependent Termination
Article first published online: 11 MAR 2004
Volume 60, Issue 1, pages 34–40, March 2004
How to Cite
Sinha, D. and Maiti, T. (2004), A Bayesian Approach for the Analysis of Panel-Count Data with Dependent Termination. Biometrics, 60: 34–40. doi: 10.1111/j.0006-341X.2004.00140.x
- Issue published online: 11 MAR 2004
- Article first published online: 11 MAR 2004
- Received November 2002. Revised June 2003. Accepted September 2003.
- Gibbs sampling;
- Posterior distribution;
- Recurrent events
Summary. We consider modeling and Bayesian analysis for panel-count data when the termination time for each subject may depend on its history of the recurrent events. We propose a fully specified semiparametric model for the joint distribution of the recurrent events and the termination time. For this model, we provide a natural motivation, derive several novel properties, and develop a Bayesian analysis based on a Markov chain Monte Carlo algorithm. Comparisons are made to other existing models and methods for panel-count data. We demonstrate the usefulness of our new models and methodologies through the reanalysis of a data set from a clinical trial.