Archive:Advanced ANOVA/Factorial ANOVA

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Resource type: this resource contains a tutorial or tutorial notes.

Template:0%done Factorial ANOVA involves testing differences between group means based on two or more independent variables.

One of the keys to understanding Factorial ANOVA is being able to intepret interactions.

SPSS tip

To show the syntax in the output:

• Edit - Options - General - Viewer - Display commands in log

General steps

1. Establish hypothesis/hypotheses
   • Make sure you have separate hypotheses for:
     • Main effect for each IV
     • Interactions between IVs
     • Planned contrasts (if warranted)
2. Examine assumptions:
3. IVs (categorical; between-subjects) and DV (at least interval)
   • The data in each cell is normally distributed
   • Homogeneity of variance (the variance in each cell is similar)
   • Cells are independent
4. Examine descriptive statistics, particularly the four moments (M, SD, Skewness, Kurtosis) overall, and also for each cell
5. Examine graphs
6. Conduct inferential test (ANOVA) and interpret significance of F scores
7. Conduct follow-up tests (planned contrasts or post-hoc tests) if F is significant
8. Interpret interactions
9. Calculate and interpret effect sizes
   • Eta-square (omnibus - equivalent to R²)
   • Standardised mean effect size (difference b/w two means)

Lecture slides

• Factorial ANOVA (theory)
• Factorial ANOVA (example)

Francis exercises

• 3.3 (Analysing Differences)
  • 3.3.8 Factorial ANOVA
    • AQUES.sav
    • Motiv.sav

External links

• Factorial ANOVA (ucspace)
  • Factorial ANOVA Notes (Handout)