Quantile-based MANOVA: A new tool for inferring multivariate data in factorial designs
提出一种基于分位数（如中位数）的多元方差分析方法，适用于各种因子设计，无需正态性和方差齐性假设，通过模拟和小样本验证其有效性。
Multivariate analysis-of-variance (MANOVA) is a well established tool to examine multivariate endpoints. While classical approaches depend on restrictive assumptions like normality and homogeneity, there is a recent trend to more general and flexible procedures. In this paper, we proceed on this path, but do not follow the typical mean-focused perspective. Instead we consider general quantiles, in particular the median, for a more robust multivariate analysis. The resulting methodology is applicable for all kind of factorial designs and shown to be asymptotically valid. Our theoretical results are complemented by an extensive simulation study for small and moderate sample sizes. An illustrative data analysis is also presented.