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

被引:92
作者
Molodianovitch, Katy [1 ]
Faraggi, David [1 ]
Reiser, Benjamin [1 ]
机构
[1] Univ Haifa, Dept Stat, IL-31905 Haifa, Israel
关键词
Box-Cox transformation; diagnostic markers; hypothesis testing; Mann-Whitney statistic;
D O I
10.1002/bimj.200610223
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页码:745 / 757
页数:13
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