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首页> 外文期刊>Biometrics: Journal of the Biometric Society : An International Society Devoted to the Mathematical and Statistical Aspects of Biology >Power and sample size estimation for the Wilcoxon rank sum test with application to comparisons of C statistics from alternative prediction models.
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Power and sample size estimation for the Wilcoxon rank sum test with application to comparisons of C statistics from alternative prediction models.

机译：Wilcoxon秩和检验的功效和样本大小估计，可用于比较其他预测模型中的C统计量。

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摘要

The Wilcoxon Mann-Whitney (WMW) U test is commonly used in nonparametric two-group comparisons when the normality of the underlying distribution is questionable. There has been some previous work on estimating power based on this procedure (Lehmann, 1998, Nonparametrics). In this article, we present an approach for estimating type II error, which is applicable to any continuous distribution, and also extend the approach to handle grouped continuous data allowing for ties. We apply these results to obtaining standard errors of the area under the receiver operating characteristic curve (AUROC) for risk-prediction rules under H(1) and for comparing AUROC between competing risk prediction rules applied to the same data set. These results are based on SAS-callable functions to evaluate the bivariate normal integral and are thus easily implemented with standard software.
机译：当基础分布的正态性值得怀疑时，Wilcoxon Mann-Whitney（WMW）U检验通常用于非参数两组比较。以前有一些基于此过程的功率估计工作（Lehmann，1998，Nonparametrics）。在本文中，我们提出了一种估计II型错误的方法，该方法适用于任何连续分布，并且还扩展了该方法以处理允许关联的分组连续数据。我们将这些结果应用于针对H（1）下的风险预测规则获得接收器工作特征曲线（AUROC）下区域的标准误差，并比较应用于同一数据集的竞争风险预测规则之间的AUROC。这些结果基于可调用SAS的函数来评估二元正态积分，因此可以使用标准软件轻松实现。

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