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dc.contributor.authorCengiz, M. A.
dc.contributor.authorSenel, T.
dc.contributor.authorTerzi, Y.
dc.contributor.authorMurat, N.
dc.contributor.authorSavas, N.
dc.date.accessioned2020-06-21T14:48:45Z
dc.date.available2020-06-21T14:48:45Z
dc.date.issued2010
dc.identifier.issn1996-0816
dc.identifier.urihttps://hdl.handle.net/20.500.12712/17972
dc.descriptionWOS: 000277303000002en_US
dc.description.abstractGeneralized estimating equations (GEE) provide an applicable approach to modelling repeated and clustered data that are often encountered in medical application. This approach is very useful especially when response variables are correlated and categorical, covariates are time-depended, there are a large number explanatory variables and missing data. In this study, using this approach we focus on modelling repeated sedation measurements obtained during magnetic resonance imaging (MRI) and computerized tomography (CT) for children.en_US
dc.language.isoengen_US
dc.publisherAcademic Journalsen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectSedationen_US
dc.subjectmidazolamen_US
dc.subjectgeneralized linear modelsen_US
dc.titleComparing different sedation medications using generalized estimating equations approachen_US
dc.typearticleen_US
dc.contributor.departmentOMÜen_US
dc.identifier.volume4en_US
dc.identifier.issue4en_US
dc.identifier.startpage130en_US
dc.identifier.endpage134en_US
dc.relation.journalAfrican Journal of Pharmacy and Pharmacologyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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