A marginal likelihood approach for estimating penetrance from kin-cohort designs |
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Authors: | Chatterjee N Wacholder S |
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Affiliation: | Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland 20892, USA. chattern@mail.nih.gov |
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Abstract: | 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. |
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Keywords: | Correlated data EM algorithm Failure time data Residual familial correlation Sandwich variance |
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