title: Size and power of two-sample tests of repeated measures data.
abstract: One method of using repeated measures data to compare treatment groups in a clinical trial is to summarize each subject's outcomes with a single summary statistic, and then perform a distribution-free comparison based on the resulting statistics. We examine extensions of this approach and conditions under which they retain proper size in the presence of missing data. The asymptotic relative efficiencies of several summary statistic tests are calculated to show which perform best in a variety of situations. The techniques are illustrated using data from an AIDS clinical trial.
authors.affiliation: Department of Preventive Medicine and Environmental Health, University of Iowa, Iowa City 52242.
authors.forename: J D
authors.initials: JD
authors.lastname: Dawson
authors.forename: S W
authors.initials: SW
authors.lastname: Lagakos
mesh_terms: D000704:Analysis of Variance; D001699:Biometry / Q000379:methods*; D015496:CD4-Positive T-Lymphocytes; D003627:Data Interpretation, Statistical; D015658:HIV Infections / Q000097:blood / Q000188:drug therapy; D006801:Humans; D016014:Linear Models; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*; D015203:Reproducibility of Results; D015215:Zidovudine / Q000627:therapeutic use
chemical_list: D015215:Zidovudine