title: How many repeated measurements are useful?
abstract: 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.
authors.affiliation: University of Texas Health Science Center, USA.
authors.forename: J E
authors.initials: JE
authors.lastname: Overall
mesh_terms: D000704:Analysis of Variance; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D003627:Data Interpretation, Statistical; D006801:Humans; D009010:Monte Carlo Method; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data*; D011336:Probability