title: Estimating sample sizes for repeated measurement designs.
abstract: Formulas for estimating sample sizes that are required to provide specified power for analysis of variance (ANOVA) tests of significance in a two-group repeated measurements design are presented and evaluated. Power and sample size requirements depend on the pattern of treatment effects and the pattern of correlations among the repeated measurements, as well as on parameters common to sample size estimation for cross-sectional comparisons of treatment effects in simple randomized designs. Simplifying assumptions permit generation of these numerous parameter estimates from predictions of the magnitude of the standardized "effect size" at end of trial and the single correlation between the baseline and endpoint measurements. Monte Carlo methods are used to verify the actual power of different tests of significance for treatment effects in repeated measurement designs using sample sizes estimated by the formulas. The sample size implications of different patterns of treatment effects, levels of correlation, and numbers of repeated measurements are evaluated.
authors.affiliation: Department of Psychiatry and Behavioral Sciences, University of Texas Medical School, Houston 77225.
authors.forename: J E
authors.initials: JE
authors.lastname: Overall
authors.forename: S R
authors.initials: SR
authors.lastname: Doyle
mesh_terms: D000704:Analysis of Variance; D006801:Humans; D015233:Models, Statistical; D016032:Randomized Controlled Trials as Topic / Q000379:methods / Q000706:statistics & numerical data*; D012107:Research Design; D012494:Sampling Studies