Title of article
Non‐parametric estimation for time-dependent AUC
Author/Authors
Chiang، نويسنده , , Chin-Tsang and Hung، نويسنده , , Hung، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2010
Pages
13
From page
1162
To page
1174
Abstract
The area under the receiver operating characteristic (ROC) curve (AUC) is one of the commonly used measure to evaluate or compare the predictive ability of markers to the disease status. Motivated by an angiographic coronary artery disease (CAD) study, our objective is mainly to evaluate and compare the performance of several baseline plasma levels in the prediction of CAD-related vital status over time. Based on censored survival data, the non-parametric estimators are proposed for the time-dependent AUC. The limiting Gaussian processes of the estimators and the estimated asymptotic variance–covariance functions enable us to further construct confidence bands and develop testing procedures. Applications and finite sample properties of the proposed estimation methods and inference procedures are demonstrated through the CAD-related death data from the British Columbia Vital Statistics Agency and Monte Carlo simulations.
Keywords
ROC , Smoothing Parameter , Survival data , Non?parametric estimator , Bivariate estimation , AUC , Gaussian process , Bootstrap , Kaplan–Meier estimator
Journal title
Journal of Statistical Planning and Inference
Serial Year
2010
Journal title
Journal of Statistical Planning and Inference
Record number
2220572
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