Semiparametric regression analysis on longitudinal pattern of recurrent gap times

Ying Qing Chen, Mei Cheng Wang, Yijian Huang

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
Pages (from-to)277-290
Number of pages14
JournalBiostatistics
Volume5
Issue number2
DOIs
Publication statusPublished - Apr 2004

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Keywords

  • Induced dependent censorship
  • Longitudinal studies
  • Reverse-time hazard function
  • Right truncation
  • Riskset

ASJC Scopus subject areas

  • Medicine(all)
  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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