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Multivariate analysis of variance (MANOVA) is a statistical model that generalizes and extends the univariate analysis of variance model. This model is necessary when answers to research questions require the evaluation of multiple outcome measures. While in some cases it may be useful to examine individual outcomes separately, using the univariate model, in many studies the outcomes observed are interrelated. Because of the interrelationship among outcome measures, it is generally more appropriate and meaningful to analyze the outcomes as a composite(s) or weighted combination(s) of the measures using the multivariate model.

While the multivariate model can be applied to a variety of research designs (e.g., between group, repeated measures, mixed model), the focus here is given to posttests-only between-group designs. Furthermore, only a single-factor between-group design ...

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