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|Title:||Interpretation of data showing something has one effect sometimes and a different effect in other circumstances: Theories of interaction of factors|
|Citation:||ASOR Bulletin, 2009; 28(3):25-29|
|Publisher:||Australian Society for Operations Research Inc|
|T. P. Hutchinson|
|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.|
|Appears in Collections:||Centre for Automotive Safety Research conference papers|
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