Analysis of recurrent event data with incomplete observation gaps.
In analysis of recurrent event data, recurrent events are not completely experienced when the terminating event occurs before the end of a study. To make valid inference of recurrent events, several methods have been suggested for accommodating the terminating event (Statist. Med. 1997; 16:911-924; Biometrics 2000; 56:554-562). In this paper, our interest is to consider a particular situation, where intermittent dropouts result in observation gaps during which no recurrent events are observed. In this situation, risk status varies over time and the usual definition of risk variable is not applicable. In particular, we consider the case when information on the observation gap is incomplete, that is, the starting time of intermittent dropout is known but the terminating time is not available. This incomplete information is modeled in terms of an interval-censored mechanism. Our proposed method is applied to the study of the Young Traffic Offenders Program on conviction rates, wherein a certain proportion of subjects experienced suspensions with intermittent dropouts during the study.
Kim
Yang-Jin
YJ
Institute of Statistics, Korea University, Seoul 136-701, Korea.
Jhun
Myoungshic
M
D000293:Adolescent; D000465:Algorithms; D001334:Automobile Driving / Q000193:education; D003627:Data Interpretation, Statistical; D006801:Humans; D008137:Longitudinal Studies; D008923:Missouri; D019370:Observation; D010352:Patient Dropouts / Q000706:statistics & numerical data*; D013332:Student Dropouts / Q000706:statistics & numerical data; D016019:Survival Analysis