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

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.

Publication types

  • Comparative Study

MeSH terms

  • Area Under Curve
  • Biomarkers
  • CA-125 Antigen / blood
  • CA-19-9 Antigen / blood
  • Computer Simulation
  • Data Interpretation, Statistical*
  • Humans
  • Pancreatic Neoplasms / diagnosis
  • ROC Curve*
  • Statistics, Nonparametric*

Substances

  • Biomarkers
  • CA-125 Antigen
  • CA-19-9 Antigen