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A modified two-factor multivariate analysis of variance: Asymptotics and small sample approximations

机译:修正的两因素方差多元分析:渐近和小样本近似

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In this paper, we present results for testing main, simple and interaction effects in heteroscedastic two factor MANOVA models. In particular, we suggest modifications to the MANOVA sum of squares and cross product matrices to account for heteroscedasticity. Based on these modified matrices, we define some multivariate test statistics and derive their asymptotic distributions under non-normality for the null as well as non-null cases. Derivation of these results relies on the perturbation method and limit theorems for independently distributed random matrices. Based on the asymptotic distributions, we devise small sample approximations for the quantiles of the null distributions. The numerical accuracy of the large sample as well as small sample approximations are favorable. A real data set from a Smoking Cessation Trial is analyzed to illustrate the application of the methods.
机译:在本文中,我们介绍了在异方差两因素MANOVA模型中测试主要,简单和交互作用的结果。特别是,我们建议对MANOVA平方和和叉积矩阵的和进行修改,以解决异方差问题。基于这些修改后的矩阵,我们定义了一些多元检验统计量,并得出了在非正态和非零情况下非正态下的渐近分布。这些结果的推导依赖于扰动方法,并且限制了独立分布的随机矩阵的定理。基于渐近分布,我们为零分布的分位数设计了小的样本近似值。大样本的数值精度以及小的样本近似值都是有利的。分析了戒烟试验中的真实数据集,以说明该方法的应用。

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