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18 Cards in this Set
- Front
- Back
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Factorial Design. Experimental designs with two or more IVs in which every level of every variable is paired w/ every level of every other variable called factorial designs. Factors completely crossed. |
Two-Way Between-Subjects ANOVA |
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Two-Way Between-Subjects ANOVA Assumptions |
Normality of the error term (DV) in each cell. Homogeneity of variance. Independence of subjects. No outliers. Interval scale of the DV. |
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Degrees of Freedom Main Effect A |
dfA = J-1 |
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Degrees of Freedom Main Effect B |
dfB = K-1 |
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Degrees of Freedom Interaction AB |
dfAB = (J-1)(K-1) |
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Error S/AB |
dfS/AB = N-JK |
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Mean Squares MSa |
ssA/dfA |
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Mean Squares MSb |
ssB/dfB |
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Mean Squares MSab |
ssAB/dfAB |
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Mean Squares MSs/ab |
ssS/AB / dfS/AB |
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F Values Main effect A |
Fa = MSa / MSs/ab |
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F Values Main Effect B |
Fb = MSb / MSs/ab |
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Interaction AB |
Fab = MSa / MSsab |
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Types of Follow Up Analysis |
Marginal Comparisons, Simple Main Effects, Simple Comparisons, Interaction Contrasts |
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Tested when no interaction effect exists or the interaction effect is trivial compared to the main effect. Can be either simple or complex. Either priori or posteriori. Computation performed using t-test or f-test. |
Marginal Comparisons |
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Just like performing a one-way ANOVA on one of the columns or rows. |
Simple Main Effects |
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Natural follow up to simple main effect analysis if there are more than 2 levels. |
Simple Comparisons |
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Interaction of contrasts for A & B. Only perform if there is a priori hypothesis. No need to perform if the degree of freedom for the interaction effect is 1. |
Interaction Contrasts |
