Semiparametric Transformation Models with Time-Varying Coefficients for Recurrent and Terminal Events

Xingqiu Zhao, Jie Zhou, Liuquan Sun

Research output: Journal article publicationJournal articleAcademic researchpeer-review

24 Citations (Scopus)

Abstract

In this article, we propose a family of semiparametric transformation models with time-varying coefficients for recurrent event data in the presence of a terminal event such as death. The new model offers great flexibility in formulating the effects of covariates on the mean functions of the recurrent events among survivors at a given time. For the inference on the proposed models, a class of estimating equations is developed and asymptotic properties of the resulting estimators are established. In addition, a lack-of-fit test is provided for assessing the adequacy of the model, and some tests are presented for investigating whether or not covariate effects vary with time. The finite-sample behavior of the proposed methods is examined through Monte Carlo simulation studies, and an application to a bladder cancer study is also illustrated.
Original languageEnglish
Pages (from-to)404-414
Number of pages11
JournalBiometrics
Volume67
Issue number2
DOIs
Publication statusPublished - 1 Jun 2011

Keywords

  • Counting process
  • Estimating equation
  • Marginal model
  • Model checking
  • Recurrent events
  • Terminal event
  • Time-varying coefficients

ASJC Scopus subject areas

  • Statistics and Probability
  • Medicine(all)
  • Immunology and Microbiology(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

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