Literature DB >> 15606414

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

Li Hsu1, Lu Chen, Malka Gorfine, Kathleen Malone.   

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.

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Year:  2004        PMID: 15606414     DOI: 10.1111/j.0006-341X.2004.00249.x

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  11 in total

Review 1.  Bias Correction Methods Explain Much of the Variation Seen in Breast Cancer Risks of BRCA1/2 Mutation Carriers.

Authors:  Janet R Vos; Li Hsu; Richard M Brohet; Marian J E Mourits; Jakob de Vries; Kathleen E Malone; Jan C Oosterwijk; Geertruida H de Bock
Journal:  J Clin Oncol       Date:  2015-07-06       Impact factor: 44.544

2.  Marginal hazards regression for retrospective studies within cohort with possibly correlated failure time data.

Authors:  Sangwook Kang; Jianwen Cai
Journal:  Biometrics       Date:  2008-05-19       Impact factor: 2.571

3.  Statistical inference on the penetrances of rare genetic mutations based on a case-family design.

Authors:  Hong Zhang; Sylviane Olschwang; Kai Yu
Journal:  Biostatistics       Date:  2010-02-23       Impact factor: 5.899

4.  A fully nonparametric estimator of the marginal survival function based on case-control clustered age-at-onset data.

Authors:  Malka Gorfine; Nadia Bordo; Li Hsu
Journal:  Biostatistics       Date:  2016-07-19       Impact factor: 5.899

5.  Frailty Models for Familial Risk with Application to Breast Cancer.

Authors:  Malka Gorfine; Li Hsu; Giovanni Parmigiani
Journal:  J Am Stat Assoc       Date:  2013-12-01       Impact factor: 5.033

6.  Missing genetic information in case-control family data with general semi-parametric shared frailty model.

Authors:  Anna Graber-Naidich; Malka Gorfine; Kathleen E Malone; Li Hsu
Journal:  Lifetime Data Anal       Date:  2010-12-12       Impact factor: 1.588

7.  Semiparametric inference on the penetrances of rare genetic mutations based on a case-family design.

Authors:  Hong Zhang; Donglin Zeng; Sylviane Olschwang; Kai Yu
Journal:  J Stat Plan Inference       Date:  2013-02       Impact factor: 1.111

8.  A frailty-model-based approach to estimating the age-dependent penetrance function of candidate genes using population-based case-control study designs: an application to data on the BRCA1 gene.

Authors:  Lu Chen; Li Hsu; Kathleen Malone
Journal:  Biometrics       Date:  2009-12       Impact factor: 2.571

9.  Conditional and Marginal Estimates in Case-Control Family Data - Extensions and Sensitivity Analyses.

Authors:  Malka Gorfine; Rottem De-Picciotto; Li Hsu
Journal:  J Stat Comput Simul       Date:  2012-07-05       Impact factor: 1.424

10.  CASE-CONTROL SURVIVAL ANALYSIS WITH A GENERAL SEMIPARAMETRIC SHARED FRAILTY MODEL - A PSEUDO FULL LIKELIHOOD APPROACH.

Authors:  Malka Gorfine; David M Zucker; Li Hsu
Journal:  Ann Stat       Date:  2009       Impact factor: 4.028

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