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

N. Chatterjee, S. Wacholder

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)245-252
Number of pages8
Issue number1
StatePublished - Jan 1 2001
Externally publishedYes


  • Correlated data
  • EM algorithm
  • Failure time data
  • Residual familial correlation
  • Sandwich variance

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics


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