A class of transformed hazards models for recurrent gap times

Fangyuan Kang, Liuquan Sun, Xingqiu Zhao

Research output: Journal article publicationJournal articleAcademic researchpeer-review

8 Citations (Scopus)

Abstract

In this article, a class of transformed hazards models is proposed for recurrent gap time data, including both the proportional and additive hazards models as special cases. An estimating equation-based inference procedure is developed for the model parameters, and the asymptotic properties of the resulting estimators are established. In addition, a lack-of-fit test is presented to assess the adequacy of the model. The finite sample behavior of the proposed estimators is evaluated through simulation studies, and an application to a clinic study on chronic granulomatous disease (CGD) is illustrated.
Original languageEnglish
Pages (from-to)151-167
Number of pages17
JournalComputational Statistics and Data Analysis
Volume83
DOIs
Publication statusPublished - 1 Jan 2015

Keywords

  • Estimating equations
  • Gap times
  • Model checking
  • Recurrent events
  • Transformed hazards model

ASJC Scopus subject areas

  • Statistics and Probability
  • Computational Mathematics
  • Computational Theory and Mathematics
  • Applied Mathematics

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