ABSTRACT
The mixed analysis of variance (ANOVA) is called “mixed” because it involves a mixture of between-subjects and within-subjects variables (specifically, one of each). That is, participants will be in groups on a between-subjects independent variable (for example, an experimental condition and a control condition). However, the mixed ANOVA can be used in any situation where there is one between-subjects independent variable and one within-subjects independent variable. Much like the factorial ANOVA, in the mixed ANOVA, our primary analytic interest and focus are on interactions. In the mixed ANOVA, the potential interaction would be between the between-subjects and within-subjects variable. The mixed ANOVA will produce an interaction term, which in this case, is the interaction of the between-subjects and within-subjects independent variables. If there is a significant interaction, the entire focus of our interpretation will be on the interaction. The mixed ANOVA also produces a test of within-subjects differences, disregarding the between-subjects variable.
