Artículo
Robust consistent estimators for ROC curves with covariates
Fecha de publicación:
07/2022
Editorial:
Institute of Mathematical Statistics
Revista:
Electronic Journal of Statistics
ISSN:
1935-7524
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
The Receiver Operating Characteristic (ROC) curve is a use-ful tool to measure the classification capability of a continuous variable to assess the accuracy of a medical test that distinguishes between two conditions. Sometimes, covariates related to the diagnostic variable may increase the discriminating power of the ROC curve. Due to the lack of stability of classical ROC curves estimators to outliers, we introduce a procedure to obtain robust estimators in presence of covariates. The considered proposal focusses on a semiparametric approach which robustly fits a location-scale regression model to the diagnostic variable and considers robust adaptive empirical estimators of the regression residuals. The uniform consistency of the proposal is derived under mild assumptions. A Monte Carlo study is carried out to compare the performance of the robust proposed estimators with the classical ones both, in clean and contaminated samples. A real data set is also analysed.
Palabras clave:
COVARIATES
,
PARAMETRIC REGRESSION
,
ROBUSTNESS
,
ROC CURVES
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Licencia
Identificadores
Colecciones
Articulos (IC)
Articulos de INSTITUTO DE CALCULO
Articulos de INSTITUTO DE CALCULO
Citación
Bianco, Ana Maria; Boente Boente, Graciela Lina; González Manteiga, Wenceslao; Robust consistent estimators for ROC curves with covariates; Institute of Mathematical Statistics; Electronic Journal of Statistics; 16; 2; 7-2022; 4133-4161
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