论文标题
基于分位数的MANOVA：推断阶乘设计中多元数据的新工具
Quantile-based MANOVA: A new tool for inferring multivariate data in factorial designs
论文作者
论文摘要
多变量分析（MANOVA）是检查多元终点的良好工具。尽管经典方法取决于诸如正态性和同质性之类的限制性假设，但最新的趋势是更一般和灵活的proce dures。在本文中，我们在这条道路上进行，但不遵循典型的以均值为中心的观点。取而代之的是，我们考虑一般分位数，尤其是中位数，以进行更强大的多元分析。最终的方法适用于各种阶乘设计，并被证明是渐近有效的。我们的理论结果通过针对小样本和中等样本量的广泛模拟研究补充。还提供了说明性数据分析。
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 proce dures. 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.
