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A Marginal Likelihood Approach for Estimating Penetrance from Kin‐Cohort Designs
Author(s) -
Chatterjee Nilanjan,
Wacholder Sholom
Publication year - 2001
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.2001.00245.x
Subject(s) - penetrance , statistics , robustness (evolution) , econometrics , cohort , computer science , heritability , medicine , demography , mathematics , genetics , biology , sociology , gene , phenotype
Summary. The kin‐cohort design is a promising alternative to traditional cohort or case‐control designs for estimating penetrance of an identified rare autosomal mutation. In this design, a suitably selected sample of participants provides genotype and detailed family history information on the disease of interest. To estimate penetrance of the mutation, we consider a marginal likelihood approach that is computationally simple to implement, more flexible than the original analytic approach proposed by Wacholder et al. (1998, American Journal of Epidemiology 148 , 623–629), and more robust than the likelihood approach considered by Gail et al. (1999, Genetic Epidemiology 16 , 15–39) to presence of residual familial correlation. We study the trade‐off between robustness and efficiency using simulation experiments. The method is illustrated by analysis of the data from the Washington Ashkenazi Study.