Lehmann family of ROC curves Journal Article


Authors: Gonen, M.; Heller, G.
Article Title: Lehmann family of ROC curves
Abstract: Receiver operating characteristic (ROC) curves evaluate the discriminatory power of a continuous marker to predict a binary outcome. The most popular parametric model for an ROC curve is the binormal model, which assumes that the marker, after a monotone transformation, is normally distributed conditional on the outcome. Here, the authors present an alternative to the binormal model based on the Lehmann family, also known as the proportional hazards specification. The resulting ROC curve and its functionals (such as the area under the curve and the sensitivity at a given level of specificity) have simple analytic forms. Closed-form expressions for the functional estimates and their corresponding asymptotic variances are derived. This family accommodates the comparison of multiple markers, covariate adjustments, and clustered data through a regression formulation. Evaluation of the underlying assumptions, model fitting, and model selection can be performed using any off-the-shelf proportional hazards statistical software package.
Keywords: accuracy; cluster analysis; models, theoretical; theoretical model; roc curve; receiver operating characteristic; regression; concordance; clustered data; proportional hazards
Journal Title: Medical Decision Making
Volume: 30
Issue: 4
ISSN: 0272-989X
Publisher: Sage Publications  
Date Published: 2010-07-01
Start Page: 509
End Page: 517
Language: English
DOI: 10.1177/0272989x09360067
PUBMED: 20354227
PROVIDER: scopus
PMCID: PMC4590288
DOI/URL:
Notes: --- - "Export Date: 20 April 2011" - "CODEN: MDMAD" - "Source: Scopus"
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MSK Authors
  1. Glenn Heller
    399 Heller
  2. Mithat Gonen
    1028 Gonen