Preliminary Testing: The Devil of Statistics?

J. Pearce, Ben Derrick
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引用次数: 8

Abstract

In quantitative research, the selection of the most appropriate statistical test for the comparison of two-independent samples can be problematic. There is a lack of consensus in the Statistics community regarding the appropriate approach; particularly towards assessing assumptions of normality and equal variances. The lack of clarity in the appropriate strategy affects the reproducibility of results. Statistical packages performing different tests under the same name, only adds to this issue. The process of preliminary testing assumptions of a test using the sample data, before performing a test conditional upon the preliminary test, is performed by some researchers; this practice is often criticised in the literature. Preliminary testing is typically performed at the arbitrary 5% significance level. In this paper this process is reviewed, and additional results are given using simulation, examining a procedure with normality and equal variance preliminary tests.
初步测试:统计的魔鬼?
在定量研究中,为两个独立样本的比较选择最合适的统计检验可能是有问题的。统计界对适当的方法缺乏共识;特别是在评估正态性和等方差的假设方面。适当的策略缺乏明确性会影响结果的可重复性。统计软件包进行不同的测试在同样的名字,只会增加这个问题。在以初步测试为条件进行测试之前,使用样本数据对测试假设进行初步测试的过程由一些研究人员执行;这种做法在文献中经常受到批评。初步检验通常在任意5%的显著性水平上进行。本文对这一过程进行了回顾,并通过模拟给出了附加结果,检验了一个具有正态性和等方差初步检验的过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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