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Article: Asymptotic powers for matched trend tests and robust matched trend tests in case-control genetic association studies

TitleAsymptotic powers for matched trend tests and robust matched trend tests in case-control genetic association studies
Authors
Issue Date2010
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/csda
Citation
Computational Statistics And Data Analysis, 2010, v. 54 n. 1, p. 65-77 How to Cite?
AbstractThe matched trend test (MTT), developed using a conditional logistic regression, has been proposed to test for association in matched case-control studies to control the bias of known confounding effects and reduce the potential impact of population stratification. The MTT requires a known genetic model. When the genetic model is unknown, a Monte Carlo robust test, MAX, has been proposed for the analysis of matched case-control studies. The MAX statistic takes the maximum of three MTTs optimal for three common genetic models. We derive the asymptotic power for MTTs and robust tests. In particular, we derive the asymptotic p-value for MAX. Using these analytical results, we conduct simulation studies to compare the performance of MAX and the two-degree-of-freedom Chi-square test for matched case-control studies, where the latter is implemented in most computing software. Our simulation results show that MAX is always asymptotically more powerful than the two-degree-of-freedom Chi-square test under common genetic models. Our results provide guidelines for the analysis of genetic association using matched case-control data. An illustration of our results to a real matched pair case-control etiologic study of sarcoidosis is given. © 2009 Elsevier B.V.
Persistent Identifierhttp://hdl.handle.net/10722/172464
ISSN
2015 Impact Factor: 1.179
2015 SCImago Journal Rankings: 1.283
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorZang, Yen_US
dc.contributor.authorFung, WKen_US
dc.contributor.authorZheng, Gen_US
dc.date.accessioned2012-10-30T06:22:39Z-
dc.date.available2012-10-30T06:22:39Z-
dc.date.issued2010en_US
dc.identifier.citationComputational Statistics And Data Analysis, 2010, v. 54 n. 1, p. 65-77en_US
dc.identifier.issn0167-9473en_US
dc.identifier.urihttp://hdl.handle.net/10722/172464-
dc.description.abstractThe matched trend test (MTT), developed using a conditional logistic regression, has been proposed to test for association in matched case-control studies to control the bias of known confounding effects and reduce the potential impact of population stratification. The MTT requires a known genetic model. When the genetic model is unknown, a Monte Carlo robust test, MAX, has been proposed for the analysis of matched case-control studies. The MAX statistic takes the maximum of three MTTs optimal for three common genetic models. We derive the asymptotic power for MTTs and robust tests. In particular, we derive the asymptotic p-value for MAX. Using these analytical results, we conduct simulation studies to compare the performance of MAX and the two-degree-of-freedom Chi-square test for matched case-control studies, where the latter is implemented in most computing software. Our simulation results show that MAX is always asymptotically more powerful than the two-degree-of-freedom Chi-square test under common genetic models. Our results provide guidelines for the analysis of genetic association using matched case-control data. An illustration of our results to a real matched pair case-control etiologic study of sarcoidosis is given. © 2009 Elsevier B.V.en_US
dc.languageengen_US
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/csdaen_US
dc.relation.ispartofComputational Statistics and Data Analysisen_US
dc.titleAsymptotic powers for matched trend tests and robust matched trend tests in case-control genetic association studiesen_US
dc.typeArticleen_US
dc.identifier.emailFung, WK: wingfung@hku.hken_US
dc.identifier.authorityFung, WK=rp00696en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1016/j.csda.2009.07.011en_US
dc.identifier.scopuseid_2-s2.0-70349299831en_US
dc.identifier.hkuros171331-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-70349299831&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume54en_US
dc.identifier.issue1en_US
dc.identifier.spage65en_US
dc.identifier.epage77en_US
dc.identifier.isiWOS:000273015500007-
dc.publisher.placeNetherlandsen_US
dc.identifier.scopusauthoridZang, Y=16053902200en_US
dc.identifier.scopusauthoridFung, WK=13310399400en_US
dc.identifier.scopusauthoridZheng, G=35265434100en_US
dc.identifier.citeulike5322180-

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