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|dc.identifier.citation||ASOR Bulletin, 2009; 28(3):25-29||en|
|dc.description.abstract||A 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.statementofresponsibility||T. P. Hutchinson||en|
|dc.publisher||Australian Society for Operations Research Inc||en|
|dc.title||Interpretation of data showing something has one effect sometimes and a different effect in other circumstances: Theories of interaction of factors||en|
|pubs.library.collection||Centre for Automotive Safety Research conference papers||en|
|dc.identifier.orcid||Hutchinson, T. [0000-0002-4429-0885]||en|
|Appears in Collections:||Centre for Automotive Safety Research conference papers|
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