Multivariate Analysis of Variance (MANOVA) is a foundational statistical method used to detect group differences across multiple correlated outcome variables. Classical MANOVA test statistics, including Wilk’s Lambda, Pillai’s Trace, and Roy’s Root, are optimal under multivariate normality and homogeneity of covariance matrices. However, their performances can deteriorate under non-normality or small sample sizes. This study builds upon the truncated MANOVA statistics (W3, P3, R3) which demonstrated improved robustness under specific non-Gaussian conditions.