Abstract:
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Family-based association tests are currently developed for categorical, quantitative, and censored traits with nuclear families. Although these methods can be applied to data on pedigrees, they are not efficient, since they do not incorporate all available information. The proposed tests are extensions of a family-based association test to data on quantitative and censored traits with pedigrees. Proportional hazards regression models are used to motivate the methods with censored traits. Conditioning on the minimal sufficient statistics for association in the absence of linkage is used to avoid confounding, due to factors other than linkage. The tests involve estimating density and survival functions of the trait, given the observed marker genotypes and unobserved trait genotypes. A theory for such estimation is developed. Results of simulations that explore the performance of these procedures are described. The procedures are illustrated through an analysis of data on APOE genotype, a mutation of alpha-2 macroglobulin gene (A2M), and Alzheimer's disease.
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