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Biostatistics Advance Access published online on February 6, 2009
Biostatistics, doi:10.1093/biostatistics/kxn043
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© The Author 2009. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.

A robust method for finely stratified familial studies with proband-based sampling

Molin Wang*

Department of Biostatistics, Harvard School of Public Health and Dana-Farber Cancer Institute, 44 Binney Street, Boston, MA 02115, USA mwang{at}jimmy.harvard.edu

John J. Hanfelt

Department of Biostatistics, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA

* To whom correspondence should be addressed.

This paper presents a robust method to conduct inference in finely stratified familial studies under proband-based sampling. We assume that the interest is in both the marginal effects of subject-specific covariates on a binary response and the familial aggregation of the response, as quantified by intrafamilial pairwise odds ratios. We adopt an estimating function for proband-based family studies originally developed by Zhao and others (1998) in the context of an unstratified design and treat the stratification effects as fixed nuisance parameters. Our method requires modeling only the first 2 joint moments of the observations and reduces by 2 orders of magnitude the bias induced by fitting the stratum-specific nuisance parameters. An analytical standard error estimator for the proposed estimator is also provided. The proposed approach is applied to a matched case–control familial study of sleep apnea. A simulation study confirms the usefulness of the approach.

Keywords: 2-Index asymptotics; Adjusted profile estimating function; Ascertainment bias; Bias reduction; Familial aggregation; Nuisance parameter; Proband; Sparse data; Stratified study

Received August 17, 2007; revised April 29, 2008; revised August 15, 2008; revised October 8, 2008; revised October 17, 2008; accepted for publication November 21, 2008.


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