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比较两条相关ROC曲线下的面积:参数法和非参数法

Comparing the areas under two correlated ROC curves: parametric and non-parametric approaches.

作者信息

Molodianovitch Katy, Faraggi David, Reiser Benjamin

机构信息

Department of Statistics, University of Haifa 31905, Israel.

出版信息

Biom J. 2006 Aug;48(5):745-57. doi: 10.1002/bimj.200610223.

Abstract

In order to compare the discriminatory effectiveness of two diagnostic markers the equality of the areas under the respective Receiver Operating Characteristic Curves is commonly tested. A non-parametric test based on the Mann-Whitney statistic is generally used. Weiand et al. (1989) present a parametric test based on normal distributional assumptions. We extend this test using the Box-Cox power family of transformations to non-normal situations. These three test procedures are compared in terms of significance level and power by means of a large simulation study. Overall we find that transforming to normality is to be preferred. An example of two pancreatic cancer serum biomarkers is used to illustrate the methodology.

摘要

为了比较两种诊断标志物的鉴别效能,通常会检验各自的受试者工作特征曲线下面积是否相等。一般使用基于曼-惠特尼统计量的非参数检验。韦安德等人(1989年)提出了一种基于正态分布假设的参数检验。我们使用Box-Cox幂变换族将此检验扩展到非正态情况。通过一项大型模拟研究,从显著性水平和检验功效方面对这三种检验方法进行了比较。总体而言,我们发现转换为正态分布更可取。以两种胰腺癌血清生物标志物为例来说明该方法。

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