Homogeneity of variance and ANOVA
Assess homogeneity of variance when comparing three independent groups on a continuous outcome
Homogeneity of variance essentially makes sure that the distributions of the outcomes in each independent group are comparable and/or equal. If independent groups are not similar in this regard, spurious findings can be yielded. ANOVA should not be conducted on continuous variables that violate the assumption of homogeneity of variance. ANOVA should only be conducted on continuous outcomes between groups that have "equivalent" or similar variances.
The steps for assessing the assumption of homogeneity of variance for ANOVA in SPSS
2. Drag the cursor over the Compare Means drop-down menu.
3. Click on One-way ANOVA.
4. Click on the continuous outcome variable to highlight it.
5. Click on the arrow to move the outcome variable into the Dependent List: box.
6. Click on the "grouping" variable to highlight it.
7. Click on the arrow to move the "grouping" variable into the Factor: box.
8. Click on the Options button.
9. In the Statistics table, click the Homogeneity of variance test box.
10. Click Continue.
11. Click OK.
The steps for interpreting the SPSS output for homogeneity of variance with ANOVA
If the p-value is MORE THAN .05, then researchers have met the assumption of homogeneity of variance and can conduct a one-way ANOVA.
If the p-value is LESS THAN .05, then researchers have violated the assumption of homogeneity of variance and will use a non-parametric Kruskal-Wallis test to conduct the analysis.
Was the assumption of homogeneity of variance met for ANOVA?
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