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PSYC 2030 - Test 2 Notes (Winter 2012)

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PSYC 2030
Rebecca Jubis

PSYC 2030 Test 2 Notes Chapter 8 Experimental Design II Factorial Designs Factorial Design involves any study with more than one IV It is described with a numbering system that simultaneously identifies the number of IV and the number of levels in each variableThe conditions to be tested on compared can be determined by looking at all of the combinations of different levels of each IV through a factorial matrixThe main effect is used to describe the overall effect of a given IV equally the number of possible main effects or equal the number of IV It is the mean for one particular IV level involving the combination of all the data for each of the levels of that factorThe interaction effect occurs when the effect of one IV depends upon the level of the other IV There is one major interaction effectCeiling Effect Occurs when scores in 2 or more conditions are near the maximum This can give the impression that no differences exist between conditions they are so close to the maximum that there is not enough room for an increase to be demonstratedThe parallel opposite of the Ceiling Effect is called the Floor Effect Mixed Factorial Design is a factorial design with at least one betweensubjects factor and one withinsubjects factor In contrast to P x E Factorial Design it is a factorial design with at least one subject factor Pperson variable and one manipulated factor Eenvironmental variableMixed P x E Factorial Design is a mixed design with at least one subject factor and one manipulated factor ATI Design Aptitude by Treatment Interaction Design is a form of P x E Factorial Design found in educational research The goal is to examine possible interactions between an aptitude variable person factor and a treatment variable environmental factor
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