Analysis of repeated measurements

Abstract

Recent literature demonstrates that uniformity of population variances and covariances is a sufficient but not a necessary requirement for valid F ratios in repeated measures designs; the tests will be valid if the loss restrictive condition of circularity is satisfied. The circularity assumptions of various repeated measures designs are presented and the empirical literature is reviewed and interpreted in light of these assumptions. An empirical investigation is then presented which compares numerous data analytic strategies when circularity assumptions have been violated, Results indicate that adjusted univariate and multivariate tests are comparable with respect to Type I error control and power. Furthermore, it is shown that by formulating planned comparisons researchers can by pass all or some circularity constraints.