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Nonparametric statistical inference method for partial areas under receiver operating characteristic curves, with application to genomic studies.

机译:接收机工作特性曲线下局部区域的非参数统计推断方法,在基因组研究中的应用。

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摘要

Recently ROC(50) index-the area under the lower portion of the receiver operating characteristic (ROC) curve up to the first 50 false positives-has been increasingly widely used in genomic research. Unfortunately, statistical inferences on the ROC(50) index are not commonly drawn due to a lack of handy statistical inference methods and/or software tools. In this paper, we reviewed developments in statistical methods for the partial areas under ROC curves and using nonparametric methods we derived a simple and direct variance calculation formula for the partial areas, different from existing methods in the literature. We have also verified our method through simulation studies and compared our method with existing bi-normal approaches. We have shown that the partial area has an asymptotic normal distribution using trimmed U-statistics theory. On the basis of this asymptotic normality, we have given formulas for the confidence interval and the test statistic and we reported on their application to a genomic study of sample size approximately 10 000. Copyright (c) 2008 John Wiley & Sons, Ltd.
机译:最近,ROC(50)指数(在接收器工作特性(ROC)曲线的下部下方直到前50个假阳性的区域)已越来越广泛地用于基因组研究。不幸的是,由于缺乏方便的统计推断方法和/或软件工具,通常无法得出对ROC(50)指数的统计推断。在本文中,我们回顾了ROC曲线下局部区域统计方法的发展,并使用非参数方法得出了局部区域的简单直接方差计算公式,这与文献中已有方法不同。我们还通过仿真研究验证了我们的方法,并将我们的方法与现有的双标准方法进行了比较。我们已经显示出使用修整U统计理论的局部区域具有渐近正态分布。基于这种渐近正态性,我们给出了置信区间和检验统计量的公式,并报告了它们在样本量约为10000的基因组研究中的应用。版权所有(c)2008 John Wiley&Sons,Ltd.

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