We examined nine adaptive methods of trimming, that is, methods that empirically determine when data should be trimmed and the amount to be trimmed from the tails of the empirical distribution. Over the 240 empirical values collected for each method investigated, in which we varied the total percentage of data trimmed, sample size, degree of variance heterogeneity, pairing of variances and group sizes, and population shape, one method resulted in exceptionally good control of Type I errors. However, under less extreme cases of non-normality and variance heterogeneity a number of methods exhibited reasonably good Type I error control. With regard to the power to detect non-null treatment effects, we found that the choice among the methods depended on the degree of non-normality and variance heterogeneity. Recommendations are offered.

中文翻译：

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自适应鲁棒估计和测试。

我们研究了九种自适应修整方法，即根据经验确定何时应修整数据以及应从经验分布的尾部修整量的方法。在为每种调查的方法收集的240个经验值中，我们改变了所修剪数据的总百分比，样本大小，方差异质性程度，方差和组大小的配对以及总体形状，其中一种方法导致对Type的异常良好控制我错了。但是，在非正态和方差异质性不太极端的情况下，许多方法表现出相当好的I类错误控制。关于检测非无效治疗效果的能力，我们发现方法之间的选择取决于非正态性和方差异质性的程度。提供建议。