Cramming Sam's top tips from chapter 16
Click on the topic to read Sam's tips from the book
- Mixed designs compare several means when there are two or more independent variables, and at least one of them has been measured using the same entities and at least one other has been measured using different entities.
- Correct for deviations from sphericity for the repeated-measures variable(s) by routinely interpreting the Greenhouse–Geisser corrected effects. (Some people do this only if Mauchly’s test is significant, but this approach is problematic because the results of the test depend on the sample size.)
- The table labelled Tests of Within-Subjects Effects shows the F-statistic(s) for any repeated-measures variables and all of the interaction effects. For each effect, read the row labelled Greenhouse–Geisser or Huynh–Feldt (read the previous chapter to find out the relative merits of the two procedures). If the value in the Sig. column is less than 0.05 then the means are significantly different.
- The table labelled Tests of Between-Subjects Effects shows the F-statistic(s) for any between-group variables. If the value in the Sig. column is less than 0.05 then the means of the groups are significantly different.
- 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 are if the significance value is less than 0.05).
- Look at the means – or, better still, draw graphs – to help you interpret the contrasts.