Literature DB >> 17094340

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

Katy Molodianovitch1, David Faraggi, Benjamin Reiser.   

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.

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Year:  2006        PMID: 17094340     DOI: 10.1002/bimj.200610223

Source DB:  PubMed          Journal:  Biom J        ISSN: 0323-3847            Impact factor:   2.207


  23 in total

1.  Parametric and non-parametric confidence intervals of the probability of identifying early disease stage given sensitivity to full disease and specificity with three ordinal diagnostic groups.

Authors:  Tuochuan Dong; Lili Tian; Alan Hutson; Chengjie Xiong
Journal:  Stat Med       Date:  2011-12-05       Impact factor: 2.373

2.  Mapping plant interactomes using literature curated and predicted protein-protein interaction data sets.

Authors:  KiYoung Lee; David Thorneycroft; Premanand Achuthan; Henning Hermjakob; Trey Ideker
Journal:  Plant Cell       Date:  2010-04-06       Impact factor: 11.277

3.  Youden Index and the optimal threshold for markers with mass at zero.

Authors:  Enrique F Schisterman; David Faraggi; Benjamin Reiser; Jessica Hu
Journal:  Stat Med       Date:  2008-01-30       Impact factor: 2.373

4.  Youden Index and optimal cut-point estimated from observations affected by a lower limit of detection.

Authors:  Marcus D Ruopp; Neil J Perkins; Brian W Whitcomb; Enrique F Schisterman
Journal:  Biom J       Date:  2008-06       Impact factor: 2.207

5.  Confidence interval estimation of the difference between paired AUCs based on combined biomarkers.

Authors:  Lili Tian; Albert Vexler; Li Yan; Enrique F Schisterman
Journal:  J Stat Plan Inference       Date:  2009       Impact factor: 1.111

6.  Low coherence interferometry approach for aiding fine needle aspiration biopsies.

Authors:  Ernest W Chang; Joseph Gardecki; Martha Pitman; Eric J Wilsterman; Ankit Patel; Guillermo J Tearney; Nicusor Iftimia
Journal:  J Biomed Opt       Date:  2014       Impact factor: 3.170

7.  Comparison of two correlated ROC curves at a given specificity or sensitivity level.

Authors:  Leonidas E Bantis; Ziding Feng
Journal:  Stat Med       Date:  2016-06-20       Impact factor: 2.373

8.  Nonparametric ROC summary statistics for correlated diagnostic marker data.

Authors:  Liansheng Larry Tang; Aiyi Liu; Zhen Chen; Enrique F Schisterman; Bo Zhang; Zhuang Miao
Journal:  Stat Med       Date:  2012-10-11       Impact factor: 2.373

9.  Multivariate normally distributed biomarkers subject to limits of detection and receiver operating characteristic curve inference.

Authors:  Neil J Perkins; Enrique F Schisterman; Albert Vexler
Journal:  Acad Radiol       Date:  2013-07       Impact factor: 3.173

10.  Exact confidence interval estimation for the difference in diagnostic accuracy with three ordinal diagnostic groups.

Authors:  Lili Tian; Chengjie Xiong; Chin-Ying Lai; Albert Vexler
Journal:  J Stat Plan Inference       Date:  2010-07-20       Impact factor: 1.111

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