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Article: Evaluating the Accuracy of Small P-Values In Genetic Association Studies Using Edgeworth Expansions

TitleEvaluating the Accuracy of Small P-Values In Genetic Association Studies Using Edgeworth Expansions
Authors
Keywordschi-squared test
Edgeworth expansion
maximin efficiency robust test (MERT)
maximum likelihood estimate
nuisance parameter
Issue Date2018
PublisherWiley-Blackwell Publishing Ltd. The Journal's web site is located at http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1467-9469
Citation
Scandinavian Journal of Statistics: theory and applications, 2018, v. 45 n. 1, p. 1-33 How to Cite?
AbstractThe asymptotic distributions of many classical test statistics are normal. The resulting approximations are often accurate for commonly used significance levels, 0.05 or 0.01. In genome-wide association studies, however, the significance level can be as low as 1×10−7, and the accuracy of the p-values can be challenging. We study the accuracies of these small p-values are using two-term Edgeworth expansions for three commonly used test statistics in GWAS. These tests have nuisance parameters not defined under the null hypothesis but estimable. We derive results for this general form of testing statistics using Edgeworth expansions, and find that the commonly used score test, maximin efficiency robust test and the chi-squared test are second order accurate in the presence of the nuisance parameter, justifying the use of the p-values obtained from these tests in the genome-wide association studies. © 2017 Board of the Foundation of the Scandinavian Journal of Statistics
Persistent Identifierhttp://hdl.handle.net/10722/248572
ISSN
2023 Impact Factor: 0.8
2023 SCImago Journal Rankings: 0.892
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZheng, G-
dc.contributor.authorXiong, J-
dc.contributor.authorLi, Q-
dc.contributor.authorXu, J-
dc.contributor.authorYuan, A-
dc.contributor.authorGastwirth, J-
dc.date.accessioned2017-10-18T08:45:16Z-
dc.date.available2017-10-18T08:45:16Z-
dc.date.issued2018-
dc.identifier.citationScandinavian Journal of Statistics: theory and applications, 2018, v. 45 n. 1, p. 1-33-
dc.identifier.issn0303-6898-
dc.identifier.urihttp://hdl.handle.net/10722/248572-
dc.description.abstractThe asymptotic distributions of many classical test statistics are normal. The resulting approximations are often accurate for commonly used significance levels, 0.05 or 0.01. In genome-wide association studies, however, the significance level can be as low as 1×10−7, and the accuracy of the p-values can be challenging. We study the accuracies of these small p-values are using two-term Edgeworth expansions for three commonly used test statistics in GWAS. These tests have nuisance parameters not defined under the null hypothesis but estimable. We derive results for this general form of testing statistics using Edgeworth expansions, and find that the commonly used score test, maximin efficiency robust test and the chi-squared test are second order accurate in the presence of the nuisance parameter, justifying the use of the p-values obtained from these tests in the genome-wide association studies. © 2017 Board of the Foundation of the Scandinavian Journal of Statistics-
dc.languageeng-
dc.publisherWiley-Blackwell Publishing Ltd. The Journal's web site is located at http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1467-9469-
dc.relation.ispartofScandinavian Journal of Statistics: theory and applications-
dc.subjectchi-squared test-
dc.subjectEdgeworth expansion-
dc.subjectmaximin efficiency robust test (MERT)-
dc.subjectmaximum likelihood estimate-
dc.subjectnuisance parameter-
dc.titleEvaluating the Accuracy of Small P-Values In Genetic Association Studies Using Edgeworth Expansions-
dc.typeArticle-
dc.identifier.emailXu, J: xujf@hku.hk-
dc.identifier.authorityXu, J=rp02086-
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1111/sjos.12283-
dc.identifier.scopuseid_2-s2.0-85021289457-
dc.identifier.hkuros281085-
dc.identifier.volume45-
dc.identifier.issue1-
dc.identifier.spage1-
dc.identifier.epage33-
dc.identifier.isiWOS:000424656000001-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl0303-6898-

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