Which type of ANOVA is best suited for studying groups with multiple dependent variables?

The most suitable type of ANOVA for studying groups with multiple dependent variables is Multivariate ANOVA (MANOVA). This statistical method is specifically designed to handle scenarios where there are two or more dependent variables that may be correlated. By using MANOVA, researchers can assess the effect of independent variables on these multiple dependent variables simultaneously, which allows for a more comprehensive analysis of the data.

In contrast, a One-way ANOVA is used when there is a single dependent variable that is being influenced by one independent variable, making it inadequate for cases where multiple dependent variables need to be examined. Mixed ANOVA combines both within-subjects and between-subjects factors but still focuses on one dependent variable at a time. The general term "Analysis of Variance" does not specify the number or type of dependent variables involved, and thus is too vague for the context of this question. Hence, Multivariate ANOVA is the ideal choice for effectively analyzing multiple dependent variables in a study.