Using adaptive tests for the analysis of repeated measurements

Several methods have been proposed for the analysis of data obtained from experimental units that are observed at multiple time points. In this paper we evaluate the performance of an adaptive test for the interaction of group and time, and an adaptive test for the group effect with data sets having measurements at common time points on two groups of experimental units. The results from extensive simulation studies show that the adaptive tests maintain their level of significance and are often more powerful than the corresponding likelihood ratio and mixed model tests when the error distributions and the random effect distributions are nonnormal. When the distributions are normal, the adaptive tests are nearly as powerful as the other tests.