A Composite Likelihood Approach in Testing for Hardy Weinberg Equilibrium Using Family-Based Genetic Survey Data

• Activity Number: 483
• Type: Topic Contributed
• Date/Time: Wednesday, August 12, 2015 : 8:30 AM to 10:20 AM
• Sponsor: Biometrics Section
• Author(s): Yan Li* and Lingxiao Wang and Barry I. Graubard
• Companies: University of Maryland and University of Maryland and National Cancer Institute
• Keywords: Complex sampling ; survey data ; composite likelihood ; Taylor linearization

Abstract

In population-based household surveys, for example, the National Health and Nutrition Examination Survey (NHANES), individuals related by blood are often sampled within households. Therefore, genetic data collected from these population-based household surveys are often correlated due to two levels of correlation. One level of correlation is caused by the multistage geographical cluster sampling and the other is caused by biological inheritance among participants within the same sampled family. In this paper, we develop an efficient HWE test considering the weighting effect induced by the differential selection probabilities in complex sample designs, as well as the two levels of clustering (correlation) effects described above. The developed tests account for various complex designs for selecting households and individuals within households, and are evaluated via Monte Carlo simulation studies. The results show that the developed HWE tests maintain the nominal levels, and are more powerful than existing methods (Li et al. 2011) under various (non)informative sample designs that depend on genotypes, family relationships, or both, especially when within-household sampling depends o