What does it mean to assume sphericity?
The assumption of sphericity states that the variance of the differences between treatment A and B equals the variance of the difference between A and C, which equals the variance of the differences between A and D, which equals the variance of the differences between B and D…
Does repeated measures ANOVA assume normality?
The assumption of normality of difference scores is a statistical assumption that needs to be tested for when comparing three or more observations of a continuous outcome with repeated-measures ANOVA. Repeated-measures ANOVA should not be conducted when the assumption of normality of difference scores is violated.
Which is an ANOVA violates the assumption of sphericity?
ANOVAs with repeated measures (within-subject factors) are particularly susceptible to the violation of the assumption of sphericity. Sphericity is the condition where the variances of the differences between all combinations of related groups (levels) are equal.
When to use a repeated measures ANOVA in statistics?
A repeated measures ANOVA will not inform you where the differences between groups lie as it is an omnibus statistical test. The same would be true if you were investigating different conditions or treatments rather than time points, as used in this example.
How does sphericity relate to the repeated measures factor?
Basically, sphericity refers to the equality of the variances of the differences between levels of the repeated measures factor. In other words, we calculate the differences between each pair of levels of the repeated measures factor and then calculate the variance of these difference scores.
How to run post hoc tests for a repeated measures ANOVA in SPSS Statistics?
You can learn how to run appropriate post-hoc tests for a repeated measures ANOVA in SPSS Statistics on page 2 of our guide: One-Way Repeated Measures ANOVA in SPSS Statistics. The logic behind a repeated measures ANOVA is very similar to that of a between-subjects ANOVA.