Detecting repeated measures effects with univariate and multivariate statistics

Power differences between multivariate and is an element of-adjusted univariate tests are presented for various configurations and sizes of population means, degrees of nonsphericity, and sample sizes for small and large repeated measures designs with 1 within-subjects factor. The results are applicable to various designs (e.g., longitudinal). Power differences were calculated by adapting procedures presented in K. E. Muller and C. N. Barton (1989, 1991). The results demonstrate that, for parametric conditions likely to be encountered by psychological researchers, the differences between the 2 approaches can be considerable. The authors recommend that sample size be chosen according to the procedures enumerated by Muller and Barton but provide simple guidelines for use when the information required by the Muller-Barton approach is not available.