Archive:Advanced ANOVA/Factorial ANOVA: Difference between revisions
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Factorial ANOVA involves testing differences between group means based on two or more independent variables. | 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) | |||
# 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 ''R''<sup>2</sup>) | |||
#* Standardised mean effect size (difference b/w two means) | |||
==Data== | ==Data== | ||
Revision as of 21:37, 6 August 2008
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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)