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Testing the Correlation for Clustered Categorical and Censored Discrete Time‐to‐Event Data When Covariates Are Measured without/with Errors
dc.contributor.authorLi, Yien_US
dc.contributor.authorLin, Xihongen_US
dc.date.accessioned2012-08-09T14:54:58Z
dc.date.available2012-08-09T14:54:58Z
dc.date.issued2003-03en_US
dc.identifier.citationLi, Yi; Lin, Xihong (2003). "Testing the Correlation for Clustered Categorical and Censored Discrete Time‐to‐Event Data When Covariates Are Measured without/with Errors." Biometrics 59(1). <http://hdl.handle.net/2027.42/92373>en_US
dc.identifier.issn0006-341Xen_US
dc.identifier.issn1541-0420en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/92373
dc.publisherBlackwell Publishing, Inc.en_US
dc.publisherWiley Periodicals, Inc.en_US
dc.subject.otherRandom Effectsen_US
dc.subject.otherPolytomous Responsesen_US
dc.subject.otherLongitudinal Dataen_US
dc.subject.otherVariance Componentsen_US
dc.subject.otherSIMEXen_US
dc.subject.otherScore Testen_US
dc.subject.otherGrouped Survival Dataen_US
dc.subject.otherFrailty Modelsen_US
dc.subject.otherClustered Dataen_US
dc.titleTesting the Correlation for Clustered Categorical and Censored Discrete Time‐to‐Event Data When Covariates Are Measured without/with Errorsen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelMathematicsen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, U.S.A. email: xlin@umich.eduen_US
dc.contributor.affiliationotherDepartment of Biostatistics, Harvard School of Public Health and the Dana Farber Cancer Institute, Boston, Massachusetts 02115, U.S.A. email: yili@jimmy.harvard.eduen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/92373/1/1541-0420.00004.pdf
dc.identifier.doi10.1111/1541-0420.00004en_US
dc.identifier.sourceBiometricsen_US
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dc.owningcollnameInterdisciplinary and Peer-Reviewed


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