Multivariate Analysis of Variance (35 and 30 Patients)

Abstract

Multivariate analysis is a method that, simultaneously, assesses more than a single outcome variable. It is different from repeated measures analysis of variance and mixed models, that assess both the difference between the outcomes and the overall effects of the predictors on the outcomes. Multivariate analysis, simultaneously, assesses the separate effects of the predictors on one outcome adjusted for the other. E.g., it can answer clinically important questions like: does drug-compliance not only predict drug efficacy, but also, independently of the first effect, predict quality of life. Path statistics can be used as an alternative approach to multivariate analysis of variance (MANOVA) (Chap. 17). However, MANOVA is the real thing, because it produces an overall level of significance of a predictive model with multiple outcome and predictor variables.