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Testing for Hardy Weinberg Equilibrium in National Household Surveys that Collect Family‐Based Genetic Data
Author(s) -
Li Yan,
Li Zhaohai,
Graubard Barry I.
Publication year - 2011
Publication title -
annals of human genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.537
H-Index - 77
eISSN - 1469-1809
pISSN - 0003-4800
DOI - 10.1111/j.1469-1809.2011.00680.x
Subject(s) - cluster analysis , sampling (signal processing) , weighting , statistics , national health and nutrition examination survey , selection (genetic algorithm) , econometrics , cluster sampling , monte carlo method , population , sample (material) , survey sampling , computer science , mathematics , medicine , environmental health , machine learning , chemistry , filter (signal processing) , chromatography , computer vision , radiology
Summary In population‐based household surveys, for example, the National Health and Nutrition Examination Survey (NHANES), blood‐related individuals are often sampled from the same household. Therefore, genetic data collected from national household surveys are often correlated due to two levels of clustering (correlation) with one induced by the multistage geographical cluster sampling , and the other induced by biological inheritance among multiple participants within the same sampled household . In this paper, we develop efficient statistical methods that consider the weighting effect induced by the differential selection probabilities in complex sample designs, as well as the clustering (correlation) effects described above. We examine and compare the magnitude of each level of clustering effects under different scenarios and identify the scenario under which the clustering effect induced by one level dominates the other. The proposed method is evaluated via Monte Carlo simulation studies and illustrated using the Hispanic Health and Nutrition Survey (HHANES) with simulated genotype data.