Mixed or between-within factorial ANOVA
This chapter combines the components of both factorial and repeated-measures ANOVA which will allow us to examine different levels of one (or more) independent variable(s) in which each subject is measured on two (or more) occasions. This approach has different names, but typically it is called a mixed factorial ANOVA, or between-within ANOVA. The assumptions for a mixed factorial ANOVA are the same as for those of one-factor between-subjects ANOVA such as homogeneity of variance, normality, and independence of observation (for the between-subject independent variable). The sphericity assumption is rooted in matrix algebra and essentially focuses on equal variance between a set of difference scores. SPSS output provides the Mauchly's Sphericity test when performing repeated-measures ANOVA. The Mauchly's Sphericity test is an indication of variance homogeneity.