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. 2009 Mar 1;9(1):1.

Estimation and Comparison of Receiver Operating Characteristic Curves

Margaret Pepe  1 , Gary Longton, Holly Janes
Affiliations

Estimation and Comparison of Receiver Operating Characteristic Curves

Margaret Pepe et al. Stata J. .

Abstract

The receiver operating characteristic (ROC) curve displays the capacity of a marker or diagnostic test to discriminate between two groups of subjects, cases versus controls. We present a comprehensive suite of Stata commands for performing ROC analysis. Non-parametric, semiparametric and parametric estimators are calculated. Comparisons between curves are based on the area or partial area under the ROC curve. Alternatively pointwise comparisons between ROC curves or inverse ROC curves can be made. Options to adjust these analyses for covariates, and to perform ROC regression are described in a companion article. We use a unified framework by representing the ROC curve as the distribution of the marker in cases after standardizing it to the control reference distribution.

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Figures

Figure 1
Figure 1
Non-parametric ROC curves for two markers of pancreatic cancer. 90% confidence intervals for ROC(0.2) are displayed.
Figure 2
Figure 2
ROC curves for CA-125 as a marker of pancreatic cancer.
See this image and copyright information in PMC

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