How many repeated measurements are useful?

Simulated data for a two-group repeated measurements design were generated with different numbers of equally-spaced measurements interposed between baseline and the end of the study. A standard repeated measurements ANOVA for a split-pilot design was used to test the significance of the between-groups main effect, the Geisser-Greenhouse corrected groups x times interaction, and the difference in linear trends across time. The analyses were repeated with and without baseline measurements entered as a covariate in the model. Monte Carlo results confirmed that increasing the number of repeated measurements across a fixed treatment period generally had negative or neutral implications for power of the tests of significance in the presence of serial dependencies that produced heterogeneous correlations among the repeated measurements.