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. ⋯ 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.
Mary T Fox, Angela Cooper Brathwaite, and Souraya Sidani.
Faculty of Nursing, University of Toronto, Ontario, Canada. mfox@baycrest.org
Can J Nurs Res. 2004 Sep 1;36(3):20-30.
AbstractRepeated 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.