Multivariate analysis of variance (MANOVA) is an extension of univariate analysis of variance (ANOVA) in which the independent variable is some combination of group membership but there is more than one dependent variable. MANOVA is often used either when the researcher has correlated dependent variables or, instead of a repeated-measures ANOVA, to avoid the sphericity assumption. While MANOVA has the advantage of providing a single, more powerful test of multiple dependent variables, it can be difficult to interpret the results.
For example, a researcher might have a large data set of information from a high school about their former students. Each student can be described using a combination of two factors: gender (male or female) and whether they graduated from high school (yes or no). The ...
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