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dc.contributor.authorOnder, Hasan
dc.date.accessioned2020-06-21T13:39:52Z
dc.date.available2020-06-21T13:39:52Z
dc.date.issued2016
dc.identifier.issn0361-0918
dc.identifier.issn1532-4141
dc.identifier.urihttps://doi.org/10.1080/03610918.2015.1010000
dc.identifier.urihttps://hdl.handle.net/20.500.12712/13708
dc.descriptionWOS: 000382581500003en_US
dc.description.abstractIn this study, it was aimed to determine accuracy of generalized estimating equations versus logistic regressions on different correlation levels and sample sizes. For this aim, two methods were compared with different sample sizes 10, 25, 50 and 100 and correlation levels 0.0, 0.3, 0.5 and 0.8. Result of this study showed that using generalized estimating equations could be preferred versus logistic regression when the sample size is over than 25 and correlation level is higher than 0.3 on data taken from studies with repeated measurements, but logistic regression could be better when the autocorrelations do not exist.en_US
dc.description.sponsorshipOndokuz Mayis University, Project Management OfficeOndokuz Mayis University [PYO.ZRT.1901.09.005]en_US
dc.description.sponsorshipThis study was supported by Ondokuz Mayis University, Project Management Office with project number of PYO.ZRT.1901.09.005.en_US
dc.language.isoengen_US
dc.publisherTaylor & Francis Incen_US
dc.relation.isversionof10.1080/03610918.2015.1010000en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAutocorrelationen_US
dc.subjectGeneralized estimating equationsen_US
dc.subjectLogistic regressionsen_US
dc.subject62G05en_US
dc.subject62G08en_US
dc.titleComparative Study of Generalized Estimating Equations and Logistic Regressions on Different Sample Sizes and Correlation Levelsen_US
dc.typearticleen_US
dc.contributor.departmentOMÜen_US
dc.identifier.volume45en_US
dc.identifier.issue10en_US
dc.identifier.startpage3528en_US
dc.identifier.endpage3533en_US
dc.relation.journalCommunications in Statistics-Simulation and Computationen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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