title: Evaluating the effectiveness of interventions: exploration of two statistical methods.
abstract: Repeated measures designs are often used to evaluate the effectiveness of interventions. In these designs, the outcomes are measured on several occasions before and after implementation of the intervention. Two statistical methods, the repeated measures analysis of variance (RM-ANOVA) and hierarchical linear models (HLM), can be used to analyze the data. The authors provide an overview of the statistical models underlying RM-ANOVA and HLM and discuss the strengths and limitations of each. They propose that the 2 methods are complementary in determining the effectiveness of interventions.
authors.affiliation: Faculty of Nursing, University of Toronto, Ontario, Canada. mfox@baycrest.org
authors.forename: Mary T
authors.initials: MT
authors.lastname: Fox
authors.forename: Angela Cooper
authors.initials: AC
authors.lastname: Brathwaite
authors.forename: Souraya
authors.initials: S
authors.lastname: Sidani
mesh_terms: D000704:Analysis of Variance; D003627:Data Interpretation, Statistical; D006801:Humans; D016014:Linear Models; D015399:Nursing Research / Q000193:education / Q000379:methods* / Q000592:standards; D017063:Outcome Assessment, Health Care; D015203:Reproducibility of Results; D012107:Research Design; D012680:Sensitivity and Specificity