Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/56881
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dc.contributor.authorHutchinson, T.en
dc.date.issued2009en
dc.identifier.citationASOR Bulletin, 2009; 28(3):25-29en
dc.identifier.issn0812-860Xen
dc.identifier.issn0812-860Xen
dc.identifier.urihttp://hdl.handle.net/2440/56881-
dc.description.abstractA possible explanation of interaction is that quantities derived from the independent variables separately add together, but then a curvilinear relationship intervenes between their total and the dependent variable observed. It is shown that two different theories of this type are always available to explain crossover interaction in a 2x2 table. For example, one theory may say that a good outcome occurs when there is an approximate match between values associated with the independent variables, and the other theory that a good outcome occurs when the total of values associated with the independent variables is either decisively small or large, with poorer outcome resulting from intermediate values.en
dc.description.statementofresponsibilityT. P. Hutchinsonen
dc.language.isoenen
dc.publisherAustralian Society for Operations Research Incen
dc.source.urihttp://www.asor.org.au/publication/page.php?page=1en
dc.titleInterpretation of data showing something has one effect sometimes and a different effect in other circumstances: Theories of interaction of factorsen
dc.typeJournal articleen
dc.identifier.rmid0020094973en
dc.identifier.pubid36055-
pubs.library.collectionCentre for Automotive Safety Research conference papersen
pubs.verification-statusVerifieden
pubs.publication-statusPublisheden
dc.identifier.orcidHutchinson, T. [0000-0002-4429-0885]en
Appears in Collections:Centre for Automotive Safety Research conference papers

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