title: Data analytic techniques for treatment outcome studies with pretest/posttest measurements: an extensive primer.
abstract: This paper discusses several data analytic technique, for examining treatment efficacy in pretest-posttest control group designs. The following approaches are described: ANOVA on post scores, ANOVA on difference scores, split-plot repeated measures ANOVA, profile analysis, and ANOCOVA with prescore as the co-variate. Guidelines for choosing between available techniques are provided; the primary focus here is on the nature of the null hypothesis, the assumptions underlying the approach, and the power of the procedure. The importance of examining the characteristics of the data set in selecting an analytic technique is illustrated.
authors.affiliation: Oregon Research Institute, Eugene, USA. LSheeber@ori.org
authors.forename: L B
authors.initials: LB
authors.lastname: Sheeber
authors.forename: E D
authors.initials: ED
authors.lastname: Sorensen
authors.forename: S R
authors.initials: SR
authors.lastname: Howe
mesh_terms: D000704:Analysis of Variance; D003627:Data Interpretation, Statistical; D003866:Depressive Disorder / Q000628:therapy; D006801:Humans; D015999:Multivariate Analysis; D016896:Treatment Outcome