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Bartlett correction factors in logistic regression models
dc.contributor.authorMoulton, Lawrence H.en_US
dc.contributor.authorWeissfeld, Lisa A.en_US
dc.contributor.authorSt. Laurent, Roy T.en_US
dc.date.accessioned2006-04-10T15:55:12Z
dc.date.available2006-04-10T15:55:12Z
dc.date.issued1993-01en_US
dc.identifier.citationMoulton, Lawrence H., Weissfeld, Lisa A., St. Laurent, Roy T. (1993/01)."Bartlett correction factors in logistic regression models." Computational Statistics &amp; Data Analysis 15(1): 1-11. <http://hdl.handle.net/2027.42/31011>en_US
dc.identifier.urihttp://www.sciencedirect.com/science/article/B6V8V-45DHVTD-18/2/a1d432140cdc577f43bc7f31ab426b77en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/31011
dc.description.abstractBartlett correction factors for likelihood ratio tests of parameters in conditional and unconditional logistic regression models are calculated. The resulting tests are compared to the Wald, likelihood ratio, and score tests, and a test proposed by Moolgavkar and Venzon in Modern Statistical Methods in Chronic Disease Epidemiology. (Wiley, New York, 1986).en_US
dc.format.extent789341 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherElsevieren_US
dc.titleBartlett correction factors in logistic regression modelsen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelStatistics and Numeric Dataen_US
dc.subject.hlbsecondlevelMathematicsen_US
dc.subject.hlbtoplevelSocial Sciencesen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumUniversity of Michigan, Ann Arbor, MI, 48109-2029, USAen_US
dc.contributor.affiliationumUniversity of Michigan, Ann Arbor, MI, 48109-2029, USAen_US
dc.contributor.affiliationotherUniversity of Pittsburgh, Pittsburgh, PA, USAen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/31011/1/0000686.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1016/0167-9473(93)90216-Gen_US
dc.identifier.sourceComputational Statistics &amp; Data Analysisen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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