Biostatistics (2004), 5, 2, pp. 277-290
Biostatistics Vol. 5 No. 2 © Oxford University Press 2004; all rights reserved.
Semiparametric regression analysis on longitudinal pattern of recurrent gap times
Division of Biostatistics, School of Public Health, University of California, Berkeley, CA 94720-7360, USA and Department of Statistics, College of Medicine, University of Florida, Gainesville, FL 32610-0212, USA
yqchen{at}biostat.ufl.edu
Department of Biostatistics, School of Hygiene and Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
To whom correspondence should be addressed: Department of Statistics, College of Medicine, University of Florida, P.O. Box 100212, Gainesville, FL 32610-0212, USA.
In longitudinal studies, individual subject may experience recurrent events of the same type over a relatively long period of time. The longitudinal pattern of gaps between successive recurrent events is often of great research interest. In this article, the probability structure of the recurrent gap times is first explored in the presence of censoring. According to the discovered structure, we introduce the stratified proportional reverse-time hazards models with unspecified baseline functions to accommodate individual heterogeneity, when the longitudinal pattern parameter is of main interest. Inference procedures are proposed and studied by way of proper riskset construction. The proposed methodology is demonstrated by the Monte Carlo simulations and an application to a well-known Denmark schizophrenia cohort study data set.
Keywords: Induced dependent censorship; Longitudinal studies; Reverse-time hazard function; Right truncation; Riskset
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