Shared frailty models for recurrent events and a terminal event

Lei Liu*, Robert A. Wolfe, Xuelin Huang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

205 Scopus citations

Abstract

There has been an increasing interest in the analysis of recurrent event data (Cook and Lawless, 2002, Statistical Methods in Medical Research 11, 141-166). In many situations, a terminating event such as death can happen during the follow-up period to preclude further occurrence of the recurrent events. Furthermore, the death time may be dependent on the recurrent event history. In this article we consider frailty proportional hazards models for the recurrent and terminal event processes. The dependence is modeled by conditioning on a shared frailty that is included in both hazard functions. Covariate effects can be taken into account in the model as well. Maximum likelihood estimation and inference are carried out through a Monte Carlo EM algorithm with Metropolis-Hastings sampler in the E-step. An analysis of hospitalization and death data for waitlisted dialysis patients is presented to illustrate the proposed methods. Methods to check the validity of the proposed model are also demonstrated. This model avoids the difficulties encountered in alternative approaches which attempt to specify a dependent joint distribution with marginal proportional hazards and yields an estimate of the degree of dependence.

Original languageEnglish (US)
Pages (from-to)747-756
Number of pages10
JournalBiometrics
Volume60
Issue number3
DOIs
StatePublished - Sep 1 2004

Keywords

  • Counting process
  • Dependent censoring
  • Hospitalization
  • Proportional hazards model
  • Survival analysis

ASJC Scopus subject areas

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

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