Article first published online: 16 JUL 2012
Copyright © 2012 John Wiley & Sons, Ltd.
Statistics in Medicine
Volume 32, Issue 1, pages 142–152, 15 January 2013
How to Cite
Pietzner, D. and Wienke, A. (2013), The trend-renewal process: a useful model for medical recurrence data. Statist. Med., 32: 142–152. doi: 10.1002/sim.5503
- Issue published online: 11 DEC 2012
- Article first published online: 16 JUL 2012
- Manuscript Accepted: 1 JUN 2012
- Manuscript Received: 3 MAY 2011
- German Research Council. Grant Number: DFG WI 3288/1-1
- German Ministry for Education and Research. Grant Number: 01ZZ0404
- recurrent events;
- colon cancer;
- trend-renewal process;
Time-to-event data analysis has a long tradition in applied statistics. Many models have been developed for data where each subject or observation unit experiences at most one event during its life. In contrast, in some applications, the subjects may experience more than one event. Recurrent events appear in science, medicine, economy, and technology. Often the events are followed by a repair action in reliability or a treatment in life science. A model to deal with recurrent event times for incomplete repair of technical systems is the trend-renewal process. It is composed of a trend and a renewal component. In the present paper, we use a Weibull process for both of these components. The model is extended to include a Cox type covariate term to account for observed heterogeneity. A further extension includes random effects to account for unobserved heterogeneity. We fit the suggested version of the trend-renewal process to a data set of hospital readmission times of colon cancer patients to illustrate the method for application to clinical data. Copyright © 2012 John Wiley & Sons, Ltd.