title: A confidence-limit-based approach to the assessment of Hardy-Weinberg equilibrium.
abstract: The classical chi(2)-procedure for the assessment of Hardy-Weinberg equilibrium (HWE) is tailored for detecting violations of HWE. However, many applications in genetic epidemiology require approximate compatibility with HWE. In a previous contribution to the field (Wellek, S. (2004). Biometrics, 60, 694-703), the methodology of statistical equivalence testing was exploited for the construction of tests for problems in which the assumption of approximate compatibility of a given genotype distribution with HWE plays the role of the alternative hypothesis one aims to establish. In this article, we propose a procedure serving the same purpose but relying on confidence limits rather than critical bounds of a significance test. Interval estimation relates to essentially the same parametric function that was previously chosen as the target parameter for constructing an exact conditional UMPU test for equivalence with a HWE conforming genotype distribution. This population parameter is shown to have a direct genetic interpretation as a measure of relative excess heterozygosity. Confidence limits are constructed using both asymptotic and exact methods. The new approach is illustrated by reanalyzing genotype distributions obtained from published genetic association studies, and detailed guidance for choosing the equivalence margin is provided. The methods have been implemented in freely available SAS macros.
authors.affiliation: Department of Biostatistics, Central Institute of Mental Health Mannheim/University of Heidelberg, 68159 Mannheim, J5, Germany. stefan.wellek@zi.mannheim.de
authors.forename: Stefan
authors.initials: S
authors.lastname: Wellek
authors.forename: Katrina A B
authors.initials: KA
authors.lastname: Goddard
authors.forename: Andreas
authors.initials: A
authors.lastname: Ziegler
mesh_terms: D000465:Algorithms; D001699:Biometry / Q000379:methods*; D002874:Chromosome Mapping / Q000379:methods*; D003198:Computer Simulation; D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D008957:Models, Genetic; D015233:Models, Statistical