Semiparametric estimation of marginal hazard function from case-control family studies

Li Hsu, Lu Chen, Malka Gorfine, Kathleen Malone

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

Estimating marginal hazard function from the correlated failure time data arising from case-control family studies is complicated by noncohort study design and risk heterogeneity due to unmeasured, shared risk factors among the family members. Accounting for both factors in this article, we propose a two-stage estimation procedure. At the first stage, we estimate the dependence parameter in the distribution for the risk heterogeneity without obtaining the marginal distribution first or simultaneously. Assuming that the dependence parameter is known, at the second stage we estimate the marginal hazard function by iterating between estimation of the risk heterogeneity (frailty) for each family and maximization of the partial likelihood function with an offset to account for the risk heterogeneity. We also propose an iterative procedure to improve the efficiency of the dependence parameter estimate. The simulation study shows that both methods perform well under finite sample sizes. We illustrate the method with a case-control family study of early onset breast cancer.

Original languageEnglish
Pages (from-to)936-944
Number of pages9
JournalBiometrics
Volume60
Issue number4
DOIs
StatePublished - Dec 2004

Keywords

  • Case-control family data
  • Correlated failure times
  • Cross-ratio function
  • Frailty model
  • Hazard function
  • Semiparametric

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