- One-way repeated-measures ANOVA compares several means when those means have come from the same entities; for example, if you measured people's statistical ability each month over a year-long course.
- In repeated-measures ANOVA there is an additional assumption: sphericity. This assumption needs to be considered only when you have three or more repeated-measures conditions.
- Test for sphericity using Mauchly's test. Find the table with this label: if the value in the column labelled Sig. is less than.05 then the assumption is violated, if it is greater than.05 then sphericity can be assumed.
- The table labelled Tests of Within-Subjects Effects shows the main result of your ANOVA. If the assumption of sphericity has been met then look at the row labelled Sphericity Assumed. If the assumption was violated then read the row labelled Greenhouse-Geisser (you can also look at Huynh-Feldt but you'll have to read this chapter to find out the relative merits of the two procedures). Having selected the appropriate row, look at the column labelled Sig. If the value is less than .05 then the means of the groups are significantly different.
- For contrasts and post hoc tests, again look to the columns labelled Sig. to discover if your comparisons are significant (they will be if the significance value is less than .05).
- Two-way repeated-measures ANOVA compares several means when there are two independent variables, and the same entities have been used in all conditions.
- Test the assumption of sphericity when you have three or more repeated-measures conditions. Find the table labelled Mauchly's test: the assumption is violated if the value in the column labelled Sig. is less than.05. You should test this assumption for all effects (in a two-way ANOVA this means you test it for the effect of both variables and the interaction term).
- The table labelled Tests of Within-Subjects Effects shows the main result of your ANOVA. In a two-way ANOVA you will have three effects: a main effect of each variable and the interaction between the two. For each effect, if the assumption of sphericity has been met then look at the row labelled Sphericity Assumed. If the assumption was violated then read the row labelled Greenhouse–Geisser (you can also look at Huynh–Feldt, but you'll have to read this chapter to find out the relative merits of the two procedures). If the value in the column labelled Sig. is less than.05 then the effect is significant.
- Break down the main effects and interaction terms using contrasts. These contrasts appear in the table labelled Tests of Within-Subjects Contrasts; again look to the columns labelled Sig. to discover if your comparisons are significant (they will be if the significance value is less than .05).
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