title: Randomized clinical trials with a pre- and a post-treatment measurement: repeated measures versus ANCOVA models.
abstract: Repeated measures (RM) and ANCOVA models are compared with respect to treatment effect estimation in randomized clinical trials with a pre- and a post-treatment measure. The covariance matrices of repeated measures are assumed to be I) homogeneous or II) heterogeneous across groups. In situation I, ANCOVA is preferred to RM, because the estimated variance of the treatment effect estimator is unbiased for ANCOVA and biased downwards for RM. In situation II, RM with Kenward and Roger's adjustment is preferred to ANCOVA, because the ANCOVA variance estimator does not correct for unknown pre-treatment expectation. The results are illustrated with an example.
authors.affiliation: Department of Methodology and Statistics, University of Maastricht, P.O. Box 616, 6200 MD Maastricht, The Netherlands. bjorn.winkens@stat.unimaas.nl
authors.forename: Bjorn
authors.initials: B
authors.lastname: Winkens
authors.forename: Gerard J P
authors.initials: GJ
authors.lastname: van Breukelen
authors.forename: Hubert J A
authors.initials: HJ
authors.lastname: Schouten
authors.forename: Martijn P F
authors.initials: MP
authors.lastname: Berger
mesh_terms: D000704:Analysis of Variance; D035843:Biomedical Research / Q000706:statistics & numerical data; D006801:Humans; D016018:Least-Squares Analysis; D015233:Models, Statistical; D009426:Netherlands; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D016896:Treatment Outcome