One of the assumptions of repeated measures ANOVA is called sphericity or circularity (the two are synonyms), explained here. How can you know if data violate this assumption?
How to quantify deviations from sphericity Deviations from sphericity in repeated measures ANOVA can be quantified by a value known as epsilon. There are two methods for calculating it. Based on a recommendation from Maxwell and Delaney (p 545, reference below), Prism 6 uses the method of Greenhouse and Geisser. While this method might be a bit convervative and underestimate deviations from the ideal, the alternative method by Huynh and Feldt tends to go too far in the other direction. If you choose not to assume sphericity in repeated measures ANOVA, Prism reports the value of epsilon. Its value can never be higher than 1.0, and can never be lower than 1/(k – 1), where k is the number of treatment groups.
