In multivariate ANOVA, what does it examine?

Multivariate ANOVA (MANOVA) is a statistical test that is specifically designed to analyze the differences between groups when there are two or more dependent variables. The key feature of MANOVA is its ability to consider multiple outcome measures simultaneously, which allows it to examine the complex relationships that might exist across various dependent variables. By doing this, MANOVA can assess how independent variables affect multiple outcomes, which can provide a more comprehensive understanding of the data than univariate methods that focus on a single outcome. This capability is essential when researchers want to explore the interaction between multiple dependent variables and how they relate to categorical independent variables. Therefore, stating that MANOVA examines multiple outcomes among groups accurately captures its primary function and utility in research contexts.