Abstract
In longitudinal studies, individual subjects may experience recurrent events of the same type over a relatively long period of time. The longitudinal pattern of the gaps between the 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 proportional reverse-time hazards models with unspecified baseline functions to accommodate heterogeneous individual underlying distributions, when the ongitudinal pattern parameter is of main interest. Inference procedures are proposed and studied by way of proper riskset construction. The proposed methodology is demonstrated by Monte-Carlo simulations and an application to the well-known Denmark schizophrenia cohort study data set
Disciplines
Longitudinal Data Analysis and Time Series | Statistical Methodology | Statistical Models | Statistical Theory | Survival Analysis
Suggested Citation
Chen, Ying Qing; Wang, Mei-Cheng; and Huang, Yijian, "Semiparametric Regression Analysis on Longitudinal Pattern of Recurrent Gap Times" (August 2002). U.C. Berkeley Division of Biostatistics Working Paper Series. Working Paper 112.
https://biostats.bepress.com/ucbbiostat/paper112
Included in
Longitudinal Data Analysis and Time Series Commons, Statistical Methodology Commons, Statistical Models Commons, Statistical Theory Commons, Survival Analysis Commons
Comments
Published in 2004 Biostatistics 5(2), pp. 277-290.