A critique and improvement of the CL common language effect size statistics of McGraw and Wong
A critique and improvement of the CL common language effect size statistics of McGraw and Wong
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DOI：
10.3102/10769986025002101
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发表时间：
2000-06-01
影响因子：
2.4
通讯作者：
Delaney, HD
中科院分区：
文献类型：
--
作者：
Vargha, A;Delaney, HD
McGraw and Wong（1992）描述了一个吸引人的效应大小指数，称为CL，该指数衡量了两个人群之间的差异，即从第一个人群随机抽样的分数将大于从随机中抽样的分数大于随机取得的分数。第二。麦格劳（McGraw）和黄（Wong）为正常分布引入了这种“通用语言效应尺寸统计量”，然后提出了任何连续分布的近似估计。此外，他们将CL概括为N组情况，相关样品案例和离散值情况。在当前论文中，提出了不同的Cl的概括，称为随机优势的A度量，可以直接应用。对于任何至少尺寸缩放的离散或连续变量。提供了点和间隔估计的确切方法以及A = .5假设的显着性检验。为多组和相关样品案例提供了CL的新概括。
McGraw and Wong (1992) described an appealing index of effect size, called CL, which measures the difference between two populations in terms of the probability that a score sampled at random from the first population will be greater than a score sampled at random from the second. McGraw, and Wong introduced this "common language effect size statistic" for normal distributions and then proposed an approximate estimation for any continuous distribution. In addition, they generalized CL to the n-group case, the correlated samples case, and the discrete values case.In the current paper a different generalization of CL, called the A measure of stochastic superiority, is proposed, which may be directly applied for any discrete or continuous variable that is at least ordinally scaled. Exact methods for point and interval estimation as well as the significance tests of the A = .5 hypothesis are provided. New generalizations of CL are provided for the multi-group and correlated samples cases.