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A novel method for testing normality in a mixed model of a nested classification

机译:在嵌套分类的混合模型中测试正态性的新方法

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摘要

Normality is one of the most common assumptions made in the development of statistical models such as the fixed effect model and the random effect model. White and MacDonald [1980. Some large-sample tests for normality in the linear regression model. JASA 75, 16–18] and Bonett and Woodward [1990. Testing residual normality in the ANOVA model. J. Appl. Statist. 17, 383–387] showed that many tests of normality perform well when applied to the residuals of a fixed effect model. The elements of the error vector are not independent in random effects models and standard tests of normality are not expected to perform properly when applied to the residuals of a random effects model.
机译:正态性是诸如固定效应模型和随机效应模型之类的统计模型开发中最常见的假设之一。怀特和麦克唐纳[1980。一些大样本检验线性回归模型中的正态性。 JASA 75,16-18]和Bonett and Woodward [1990年。在ANOVA模型中测试残留正态性。 J.应用统计员。 [17,383–387]表明,将许多正态性检验应用于固定效应模型的残差时,效果很好。误差矢量的元素在随机效应模型中不是独立的,当应用于随机效应模型的残差时,正常性的标准检验不能正常执行。

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