Background: Repeated measures designs are commonly used in health and social sciences research. Although there
are other, more advanced, statistical analyses, the F-statistic of repeated measures analysis of variance (RM-ANOVA)
remains the most widely used procedure for analyzing differences in means. The impact of the violation of normality
has been extensively studied for between-subjects ANOVA, but this is not the case for RM-ANOVA. Therefore, studies
that extensively and systematically analyze the robustness of RM-ANOVA under the violation of normality are needed.
This paper reports the results of two simulation studies aimed at analyzing the Type I error and power of RM-ANOVA
when the normality assumption is violated but sphericity is fulfilled. Method: Study 1 considered 20 distributions, both
known and unknown, and we manipulated the number of repeated measures (3, 4, 6, and 8) and sample size (from 10
to 300). Study 2 involved unequal distributions in each repeated measure. The distributions analyzed represent slight,
moderate, and severe deviation from normality. Results: Overall, the results show that the Type I error and power of the
F-statistic are not altered by the violation of normality. Conclusions: RM-ANOVA is generally robust to non-normality
when the sphericity assumption is met.
