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http://dx.doi.org/10.29220/CSAM.2022.29.5.533

Estimating the AUC of the MROC curve in the presence of measurement errors  

G, Siva (Department of Statistics, Pondicherry University)
R, Vishnu Vardhan (Department of Statistics, Pondicherry University)
Kamath, Asha (Department of Data Science, MAHE)
Publication Information
Communications for Statistical Applications and Methods / v.29, no.5, 2022 , pp. 533-545 More about this Journal
Abstract
Collection of data on several variables, especially in the field of medicine, results in the problem of measurement errors. The presence of such measurement errors may influence the outcomes or estimates of the parameter in the model. In classification scenario, the presence of measurement errors will affect the intrinsic cum summary measures of Receiver Operating Characteristic (ROC) curve. In the context of ROC curve, only a few researchers have attempted to study the problem of measurement errors in estimating the area under their respective ROC curves in the framework of univariate setup. In this paper, we work on the estimation of area under the multivariate ROC curve in the presence of measurement errors. The proposed work is supported with a real dataset and simulation studies. Results show that the proposed bias-corrected estimator helps in correcting the AUC with minimum bias and minimum mean square error.
Keywords
multivariate ROC curve; area under the curve; measurement errors; minimax approach;
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