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World of Statistics  
   
 
SEMINÁRIOS: Robust Inference for ROC Regression
 
  • Profª Vanda Inácio de Carvalho - School of Mathematics, University of Edinburgh, UK
  • FCUL - Campo Grande - Bloco C6 Piso 4 - Sala: 6.4.31 - 15:00h
  • Wednesday, May 31 of 2017
  • Project Reference: Projecto FCT: UID/MAT/00006/2013
 FCT

 

Abstract:

The receiver operating characteristic (ROC) curve is the most popular tool for evaluating the diagnostic accuracy of continuous biomarkers. Often, covariate information that affects the biomarker performance is also available and several regression methods have been proposed to incorporate covariates in the ROC framework. In this work, we propose robust inference methods for ROC regression, which can be used to safeguard against the presence of outlying biomarker values. Simulation results suggest that the methods perform well in recovering the true conditional ROC curve and corresponding area under the curve, on a variety of data contamination scenarios. Methods are illustrated using data on age-specific accuracy of glucose as a biomarker of diabetes.
 

 


 

     
 
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