Abstract
The receiver operating characteristic (ROC) curve is a popular method for characterizing the accuracy of diagnostic tests when test results are not binary. Various methodologies for estimating and comparing ROC curves have been developed. One approach, due to Pepe, uses a parametric regression model with the baseline function specified up to a finite-dimensional parameter. In this article we extend the regression models by allowing arbitrary nonparametric baseline functions. We also provide asymptotic distribution theory and procedures for making statistical inference. We illustrate our approach with dataset from a prostate cancer biomarker study. Simulation studies suggest that the extra flexibility inherent in the semiparametric method is gained with little loss in statistical efficiency.
Disciplines
Clinical Epidemiology | Medical Specialties | Statistical Methodology | Statistical Models | Statistical Theory
Suggested Citation
Cai, Tianxi and Pepe, Margaret S., "Semiparametric Receiver Operating Characteristic Analysis to Evaluate Biomarkers for Disease" (January 2003). UW Biostatistics Working Paper Series. Working Paper 185.
https://biostats.bepress.com/uwbiostat/paper185
Included in
Clinical Epidemiology Commons, Medical Specialties Commons, Statistical Methodology Commons, Statistical Models Commons, Statistical Theory Commons