Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/96452
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dc.contributor.authorCasson, R.en
dc.contributor.authorFarmer, L.en
dc.date.issued2014en
dc.identifier.citationClinical and Experimental Ophthalmology, 2014; 42(6):590-596en
dc.identifier.issn1442-6404en
dc.identifier.issn1442-9071en
dc.identifier.urihttp://hdl.handle.net/2440/96452-
dc.description.abstractLinear regression (LR) is a powerful statistical model when used correctly. Because the model is an approximation of the long-term sequence of any event, it requires assumptions to be made about the data it represents in order to remain appropriate. However, these assumptions are often misunderstood. We present the basic assumptions used in the LR model and offer a simple methodology for checking if they are satisfied prior to its use. In doing so, we aim to increase the effectiveness and appropriateness of LR in clinical research.en
dc.description.statementofresponsibilityRobert J Casson and Lachlan DM Farmeren
dc.language.isoenen
dc.publisherWiley-Blackwellen
dc.rights© 2014 Royal Australian and New Zealand College of Ophthalmologistsen
dc.subjectAssumption; normality; regression; statistics.en
dc.titleUnderstanding and checking the assumptions of linear regression: A primer for medical researchersen
dc.typeJournal articleen
dc.identifier.rmid0030015253en
dc.identifier.doi10.1111/ceo.12358en
dc.identifier.pubid138015-
pubs.library.collectionMedical Sciences publicationsen
pubs.library.teamDS10en
pubs.verification-statusVerifieden
pubs.publication-statusPublisheden
dc.identifier.orcidCasson, R. [0000-0003-2822-4076]en
Appears in Collections:Medical Sciences publications

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