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

Katy Molodianovitch, David Faraggi, Benjamin Reiser

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)745-757
Number of pages13
JournalBiometrical Journal
Volume48
Issue number5
DOIs
StatePublished - Aug 2006

Keywords

  • Box-cox transformation
  • Diagnostic markers
  • Hypothesis testing
  • Mann-Whitney statistic

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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