Archive:Advanced ANOVA/Factorial ANOVA: Difference between revisions
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==Data== | ==Data== | ||
* [http://www.pearsoned.com.au/wpsBridge/francis5/files/AQUES.sav AQUES.sav] | |||
* [http://www.pearsoned.com.au/wpsBridge/francis5/files/motiv.sav Motiv.sav] | |||
==Francis exercises== | ==Francis exercises== | ||
Revision as of 21:38, 6 August 2008
| File:Wikademia.logo.png | 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.
General steps
- Establish hypothesis/hypotheses
- Make sure you have separate hypotheses for:
- Main effect for each IV
- Interactions between IVs
- Planned contrasts (if warranted)
- Make sure you have separate hypotheses for:
- Examine assumptions:
- 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
- Examine descriptive statistics, particularly the four moments (M, SD, Skewness, Kurtosis) overall, and also for each cell
- Examine graphs
- Conduct inferential test (ANOVA) and interpret significance of F scores
- Conduct follow-up tests (planned contrasts or post-hoc tests) if F is significant
- Interpret interactions
- Calculate and interpret effect sizes
- Eta-square (omnibus - equivalent to R2)
- Standardised mean effect size (difference b/w two means)
Data
Francis exercises
- 3.3 (Analysing Differences)
- 3.3.8 Factorial ANOVA
External links
- Factorial ANOVA (ucspace)