A marginal likelihood approach for estimating penetrance from kin-cohort designs

The kin-cohort design is a promising alternative to traditional cohort or c ase-control designs for estimating penetrance of an identified rare autosom al mutation. In this design, a suitably selected sample of participants pro vides genotype and detailed family history information on the disease of in terest. To estimate penetrance of the mutation, we consider a marginal like lihood approach that is computationally simple to implement, more flexible than the original analytic approach proposed by Wacholder et al. (1998, Ame rican Journal of Epidemiology 148, 623-629), and more robust than the likel ihood approach considered by Call et al. (1999, Genetic Epidemiology 16, 15 -39) to presence of residual familial correlation We study the trade-off be tween robustness and efficiency using simulation experiments. The method is illustrated by analysis of the data from the Washington Ashkenazi Study.