Second-Order Analysis of Semiparametric Recurrent Event Processes
Article first published online: 1 MAR 2011
© 2011, The International Biometric Society
Volume 67, Issue 3, pages 730–739, September 2011
How to Cite
Guan, Y. (2011), Second-Order Analysis of Semiparametric Recurrent Event Processes. Biometrics, 67: 730–739. doi: 10.1111/j.1541-0420.2011.01557.x
- Issue published online: 14 SEP 2011
- Article first published online: 1 MAR 2011
- Received May 2010. Revised November 2010. Accepted November 2010.
- Pair correlation function;
- Recurrent event process;
- Second-order analysis
Summary A typical recurrent event dataset consists of an often large number of recurrent event processes, each of which contains multiple event times observed from an individual during a follow-up period. Such data have become increasingly available in medical and epidemiological studies. In this article, we introduce novel procedures to conduct second-order analysis for a flexible class of semiparametric recurrent event processes. Such an analysis can provide useful information regarding the dependence structure within each recurrent event process. Specifically, we will use the proposed procedures to test whether the individual recurrent event processes are all Poisson processes and to suggest sensible alternative models for them if they are not. We apply these procedures to a well-known recurrent event dataset on chronic granulomatous disease and an epidemiological dataset on meningococcal disease cases in Merseyside, United Kingdom to illustrate their practical value.