Testing Hardy-Weinberg equilibrium with a simple root-mean-square statistic. Academic Article

abstract

• We provide evidence that, in certain circumstances, a root-mean-square test of goodness of fit can be significantly more powerful than state-of-the-art tests in detecting deviations from Hardy-Weinberg equilibrium. Unlike Pearson's $chi ^2$ test, the log-likelihood-ratio test, and Fisher's exact test, which are sensitive to relative discrepancies between genotypic frequencies, the root-mean-square test is sensitive to absolute discrepancies. This can increase statistical power, as we demonstrate using benchmark data sets and simulations, and through asymptotic analysis.

authors

• Carroll, Raymond

published proceedings

• Biostatistics

altmetric score

• 0.5

author list (cited authors)

• Ward, R., & Carroll, R. J.

citation count

• 6

complete list of authors

• Ward, Rachel||Carroll, Raymond J

publication date

• January 2014

publisher

• Oxford University Press (OUP)  Publisher

published in

• Biostatistics  Journal

keywords

• Absolute Discrepancies
• Algorithms
• Alleles
• Computer Simulation
• Genotype
• Hardy–weinberg Equilibrium
• Humans
• Models, Genetic
• Monte Carlo Method
• Relative Discrepancies
• Root Mean Square

PubMed Central ID

• 23975799

Digital Object Identifier (DOI)

• 10.1093/biostatistics/kxt028

start page

• 74

end page

• 86

volume

• 15

issue

• 1

URL

• http%3A%2F%2Fdx.doi.org%2F10.1093%2Fbiostatistics%2Fkxt028