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Activity Number: 492
Type: Contributed
Date/Time: Wednesday, August 3, 2016 : 8:30 AM to 10:20 AM
Sponsor: Survey Research Methods Section
Abstract #319820 View Presentation
Title: A Composite Likelihood Approach in Testing for Hardy Weinberg Equilibrium Using Family-Based Genetic Survey Data
Author(s): Lingxiao Wang* and Barry Graubard and Yan Li
Companies: Joint Program in Survey Methodology and National Cancer Institute and Joint Program in Survey Methodology
Keywords: Complex sampling ; composite likelihood ; survey data ; Taylor linearization variances

In population-based household surveys, households are often sampled by stratified multistage cluster sampling, and multiple individuals related by blood are often sampled within households. Therefore, genetic data collected from these population-based household surveys can be correlated due to two levels of correlation: one level caused by the multistage geographical cluster sampling and the other caused by biological inheritance among participants within the same sampled family. In this paper, we develop an efficient Hardy Weinberg Equilibrium (HWE) test utilizing pairwise composite likelihood methods that incorporate the sample weighting effect induced by the differential selection probabilities in complex sample designs, as well as the two-level correlation effects described above. Monte Carlo simulation studies show that the proposed HWE test maintains the nominal levels, and is more powerful than existing methods (Li et al. 2011) under various (non)informative sample designs that depend on genotypes (explicitly or implicitly), family relationships, or both. The developed tests are further evaluated using simulated genetic data based on the Hispanic Health and Nutrition Survey.

Authors who are presenting talks have a * after their name.

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