Multivariate analysis of variance (MANOVA)
Multivariate analysis of variance (MANOVA) is a statistical procedure to determine mean differences between independent groups for more than one dependent variable that is continuous. One potential application of MANOVA may be to determine whether or not the results of these functional tests are influenced by the position the athlete plays. Although MANOVA is the appropriate choice over ANOVA when dependent variables are correlated, the technique is laden with statistical assumptions from both ANOVA and OLS regression. In addition, MANOVA is less robust to assumption violations, and can be less sensitive to revealing group differences than standard univariate techniques if dependent variables are not correlated. There are a number of statistical assumptions associated with MANOVA similar to ANOVA. The advantage of MANOVA is that the overlapping variance is accounted for, leading to a more appropriate assessment of group differences.