JSM 2012 Home

JSM 2012 Online Program

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

Online Program Home

Abstract Details

Activity Number: 511
Type: Contributed
Date/Time: Wednesday, August 1, 2012 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #304924
Title: Correcting AUC's for Measurement Error
Author(s): Bernard Rosner*+ and Weiliang Qiu and Robert Glynn
Companies: Harvard Medical School and Harvard Medical School and Harvard Medical School
Address: Channing Laboratory, Boston, MA, 02115, United States
Keywords: Risk prediction ; measurement error ; probit transformation ; c-statistic

Risk prediction models are used frequently in epidemiologic and clinical work. Risk scores are often derived from regression models based on risk factors, at least some of which are measured with error. It has been reported that ignoring measurement error can cause biased under-estimation of AUC, in many cases, resulting in misleading interpretation of the efficacy of a risk factor. Several methods have been proposed in the literature to correct AUC estimates for measurement error. Limitations of most existing methods include (a) assuming a normal distribution of risk scores; (b) assuming there is only one predictor and no other covariates in the model; and (c) not considering comparing two corrected AUCs derived from the same set of subjects. We propose an AUC correction method using the probit transformation to address the above three potential limitations. Both real data and simulation studies show good performance of the proposed AUC correction method in terms of bias and coverage probability. An example is given based on the Framingham Heart Study Risk Score.

The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2012 program

2012 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.