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Article: Robust Mantel-Haenszel test under genetic model uncertainty allowing for covariates in case-control association studies

TitleRobust Mantel-Haenszel test under genetic model uncertainty allowing for covariates in case-control association studies
Authors
Issue Date2011
PublisherJohn Wiley & Sons, Inc. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/35841
Citation
Genetic Epidemiology, 2011, v. 35 n. 7, p. 695-705 How to Cite?
AbstractThe trend test under the additive model is commonly used when a case-control genetic association study is carried out. However, for many complex diseases, the underlying genetic models are unknown and a mis-specification of the genetic model may result in a substantial loss of power. MAX3 has been proposed as an efficiency robust test against genetic model uncertainty which takes the maximum absolute value of the trend test statistics under the recessive, additive, and dominant models. Besides its popularity, little attention has been paid to the adjustment of covariates in this test and existing approaches all depend on the estimators of parameters of interest which may be seriously biased if the individuals are divided into a large number of partial tables stratified by covariates. In this article, we propose a modified MAX3 test based on the Mantel-Haenszel test (MHT). This new test avoids estimating the nuisance parameters induced by the covariates; thus, it is valid under both large and small numbers of partial tables while still enjoys the property of efficiency robustness. The asymptotic distribution of the test under the null hypothesis of no association is also derived; thus the corresponding asymptotic P-value of the statistic can be easily calculated. Besides, we prove that this new test can be equally derived through a conditional likelihood. As a result, the original MAX3 based on the trend tests or the matching trend tests can be treated as a special case and generally incorporated into the newly proposed test. Simulation results show that the modified MAX3 can keep the correct size under the null hypothesis and is more efficiency robustness than any single MHT optimal for a specified genetic model under the alternative hypothesis. Two real examples corresponding to the large and small number of partial tables scenarios, respectively, are analyzed using the proposed method. A type 2 diabetes mellitus data set is also analyzed to evaluate the performance of the proposed test under the GWAS criteria. © 2011 Wiley Periodicals, Inc.
Persistent Identifierhttp://hdl.handle.net/10722/159903
ISSN
2015 Impact Factor: 2.553
2015 SCImago Journal Rankings: 2.101
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorZang, Yen_HK
dc.contributor.authorFung, WKen_HK
dc.date.accessioned2012-08-16T05:59:09Z-
dc.date.available2012-08-16T05:59:09Z-
dc.date.issued2011en_HK
dc.identifier.citationGenetic Epidemiology, 2011, v. 35 n. 7, p. 695-705en_HK
dc.identifier.issn0741-0395en_HK
dc.identifier.urihttp://hdl.handle.net/10722/159903-
dc.description.abstractThe trend test under the additive model is commonly used when a case-control genetic association study is carried out. However, for many complex diseases, the underlying genetic models are unknown and a mis-specification of the genetic model may result in a substantial loss of power. MAX3 has been proposed as an efficiency robust test against genetic model uncertainty which takes the maximum absolute value of the trend test statistics under the recessive, additive, and dominant models. Besides its popularity, little attention has been paid to the adjustment of covariates in this test and existing approaches all depend on the estimators of parameters of interest which may be seriously biased if the individuals are divided into a large number of partial tables stratified by covariates. In this article, we propose a modified MAX3 test based on the Mantel-Haenszel test (MHT). This new test avoids estimating the nuisance parameters induced by the covariates; thus, it is valid under both large and small numbers of partial tables while still enjoys the property of efficiency robustness. The asymptotic distribution of the test under the null hypothesis of no association is also derived; thus the corresponding asymptotic P-value of the statistic can be easily calculated. Besides, we prove that this new test can be equally derived through a conditional likelihood. As a result, the original MAX3 based on the trend tests or the matching trend tests can be treated as a special case and generally incorporated into the newly proposed test. Simulation results show that the modified MAX3 can keep the correct size under the null hypothesis and is more efficiency robustness than any single MHT optimal for a specified genetic model under the alternative hypothesis. Two real examples corresponding to the large and small number of partial tables scenarios, respectively, are analyzed using the proposed method. A type 2 diabetes mellitus data set is also analyzed to evaluate the performance of the proposed test under the GWAS criteria. © 2011 Wiley Periodicals, Inc.en_HK
dc.languageengen_US
dc.publisherJohn Wiley & Sons, Inc. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/35841en_HK
dc.relation.ispartofGenetic Epidemiologyen_HK
dc.subject.meshCase-Control Studiesen_HK
dc.subject.meshData Interpretation, Statisticalen_HK
dc.subject.meshDiabetes Mellitus, Type 2 - geneticsen_HK
dc.subject.meshGenetic Predisposition to Diseaseen_HK
dc.subject.meshGenome-Wide Association Studyen_HK
dc.subject.meshHumansen_HK
dc.subject.meshModels, Geneticen_HK
dc.subject.meshModels, Statisticalen_HK
dc.subject.meshPPAR gamma - geneticsen_HK
dc.subject.meshPolymorphism, Single Nucleotideen_HK
dc.subject.meshUncertaintyen_HK
dc.titleRobust Mantel-Haenszel test under genetic model uncertainty allowing for covariates in case-control association studiesen_HK
dc.typeArticleen_HK
dc.identifier.emailFung, WK: wingfung@hku.hken_HK
dc.identifier.authorityFung, WK=rp00696en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1002/gepi.20620en_HK
dc.identifier.pmid22009791-
dc.identifier.scopuseid_2-s2.0-80054742076en_HK
dc.identifier.hkuros203695en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-80054742076&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume35en_HK
dc.identifier.issue7en_HK
dc.identifier.spage695en_HK
dc.identifier.epage705en_HK
dc.identifier.eissn1098-2272-
dc.identifier.isiWOS:000296846900014-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridZang, Y=16053902200en_HK
dc.identifier.scopusauthoridFung, WK=13310399400en_HK
dc.identifier.citeulike10041953-

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