Multivariate survival analysis for case-control family data

Li Hsu, Malka Gorfine

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Multivariate survival data arise from case-control family studies in which the ages at disease onset for family members may be correlated. In this paper, we consider a multivariate survival model with the marginal hazard function following the proportional hazards model. We use a frailty-based approach in the spirit of Glidden and Self (1999) to account for the correlation of ages at onset among family members. Specifically, we first estimate the baseline hazard function nonparametrically by the innovation theorem, and then obtain maximum pseudolikelihood estimators for the regression and correlation parameters plugging in the baseline hazard function estimator. We establish a connection with a previously proposed generalized estimating equation-based approach. Simulation studies and an analysis of case-control family data of breast cancer illustrate the methodology's practical utility.

Original languageEnglish
Pages (from-to)387-398
Number of pages12
JournalBiostatistics
Volume7
Issue number3
DOIs
StatePublished - Jul 2006

Keywords

  • Case-control family study
  • Cox proportional hazards model
  • Familial aggregation
  • Frailty model
  • Innovation theorem

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