A comparison of recent approaches to the analysis of repeated measurements

Looney & Stanley's (1989) recommendations regarding analysis strategies for repeated measures designs containing between-subjects grouping variables and within-subjects repeated measures variables were re-examined and compared to recent analysis strategies. That is, corrected degrees of freedom univariate tests, multivariate tests, mixed model tests, and tests due to Keselman, Carriere & Lix (1993) and to Algina (1994), Huynh (1978) and Lecoutre (1991) were compared for rates of Type I error in unbalanced non-spherical repeated measures designs having varied covariance structures and no missing data on the within-subjects variable. Heterogeneous within-subjects and heterogeneous within- and between-subjects structures were investigated along with multivariate non-normality. Results indicated that the tests due to Keselman et al. and Algina, Huynh and Lecoutre provided effective Type I error control whereas the default mixed model approach computed with PROC MIXED (SAS Institute, 1995) generally did not. Based on power differences, we recommend that applied researchers adopt the Welch-James type test described by Keselman et al.