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Statistics in Medicine
Article . 2010 . Peer-reviewed
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Research . 2010
Data sources: EconStor
PubliCatt
Article . 2011
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Testing Hardy–Weinberg equilibrium: An objective Bayesian analysis

Authors: Consonni, Guido; Moreno, Elias; Venturini, Sergio;

Testing Hardy–Weinberg equilibrium: An objective Bayesian analysis

Abstract

AbstractWe analyze the general (multiallelic) Hardy–Weinberg equilibrium problem from an objective Bayesian testing standpoint. We argue that for small or moderate sample sizes the answer is rather sensitive to the prior chosen, and this suggests to carry out a sensitivity analysis with respect to the prior. This goal is achieved through the identification of a class of priors specifically designed for this testing problem. In this paper, we consider the class of intrinsic priors under the full model, indexed by a tuning quantity, the training sample size. These priors are objective, satisfy Savage's continuity condition and have proved to behave extremely well for many statistical testing problems. We compute the posterior probability of the Hardy–Weinberg equilibrium model for the class of intrinsic priors, assess robustness over the range of plausible answers, as well as stability of the decision in favor of either hypothesis. Copyright © 2010 John Wiley & Sons, Ltd.

Country
Italy
Keywords

BAYES FACTOR; HARDY-WEINBERG EQUILIBRIUM; INTRINSIC PRIOR, Models, Statistical, 330, Models, Genetic, ddc:330, Intrinsic prior, intrinsic prior, Model posterior probability, Bayes Theorem, model posterior probability, robustness, Hardy-Weinberg equilibrium, Bayes factor; Hardy-Weinberg equilibrium; Intrinsic prior; Model posterior probability; Robustness., Linkage Disequilibrium, Bayes factor, Diabetes Mellitus, Type 1, Humans, Hardy–Weinberg equilibrium, Computer Simulation, Robustness, Alleles

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Average
Average
Top 10%
Green
bronze