Analysing repeated measures or randomized block designs using trimmed means
Analysing repeated measures or randomized block designs using trimmed means
复制标题
使用修剪均值分析重复测量或随机区组设计
DOI：
10.1111/j.2044-8317.1993.tb01002.x
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发表时间：
1993
影响因子：
2.6
通讯作者：
R. Wilcox
中科院分区：
文献类型：
--
作者：
R. Wilcox
一个众所周知的结果是，样本均值的标准误差值对重尾很敏感(Tukey，1960)。特别是，稍微远离正态分布，转向更重的尾部分布，会使标准误差增加相当大的量。因此，用于比较平均值的方法可以具有相对较低的功率。这个问题在心理学中尤其严重，因为最近的调查表明，与心理测量测量相关的分布通常具有异常值和非常重的尾部(Micceri，1989；Wilcox，1990a)。解决这个问题的一种方法是比较调整后的均值。袁(1974)描述了一种比较两个独立群体的剔除均值的方法，她证明了她的方法可以比韦尔奇的均值检验具有更大的威力。本文将袁的解推广到重复测量和随机区组设计。仿真结果表明，新方法与通常使用Huynh-Feldt自由度修正的F检验方法相比有很好的效果。
A well-known result is that the value of the standard error of the sample mean is sensitive to heavy tails (Tukey, 1960). In particular, moving slightly away from a normal distribution toward a heavier tailed distribution can increase the standard error by a considerable amount. As a result, methods for comparing means can have relatively low power. This problem is particularly serious in psychology because recent investigations indicate that the distributions associated with psychometric measures often have outliers and very heavy tails (Micceri, 1989; Wilcox, 1990a). One approach to this problem is to compare trimmed means instead. Yuen (1974) describes a method for comparing the trimmed means of two independent groups, and she demonstrated that her procedure can have considerably more power than Welch's test for means. This paper extends Yuen's solution to repeated measures and randomized block designs. Simulations indicate that the new procedure compares well to the usual F test using the Huynh-Feldt correction of the degrees of freedom.