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Comparación de pruebas diagnósticas desde la curva ROC

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Pablo Martínez-Camblor ()
Abstract

Se aborda el problema de comparar el poder de clasificación de métodos diferentes a partir de la curva ROC. Por un lado, se propone un método de comparación basado en la medida del supremo y, por otro, una solución al problema de comparar más de dos pruebas diagnósticas a través del área bajo la curva ROC (AUC) a partir de sus propiedades asintóticas. También se comprueba la validez de los estimadores propuestos para muestras pequeñas a partir del método bootstrap. Finalmente, se aplican los métodos propuestos en la predicción de diagnósticos sépticos (infecciosos) en pacientes admitidos en la Unidad de Cuidados Intensivos Pediátricos (UCIP) del Hospital Central de Asturias.

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File URL: http://www.ciencias.unal.edu.co/publicaciones/estadistica/rce/V30/v30n2a01Martinez.pdf
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Article provided by REVISTA COLOMBIANA DE ESTADISTICA in its journal Revista Colombiana de Estadística.

Volume (Year): (2007)
Issue (Month): ()
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Handle: RePEc:col:000163:004450

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  1. Peter G. Hall & Rob J. Hyndman & Yanan Fan, 2003. "Non Parametric Confidence Intervals for Receiver Operating Characteristic Curves," Monash Econometrics and Business Statistics Working Papers 12/03, Monash University, Department of Econometrics and Business Statistics. [Downloadable!]
  2. Peter Hall & Rob J. Hyndman, 2002. "An Improved Method for Bandwidth Selection when Estimating ROC Curves," Monash Econometrics and Business Statistics Working Papers 11/02, Monash University, Department of Econometrics and Business Statistics. [Downloadable!]
  3. Cai T. & Pepe M.S., 2002. "Semiparametric Receiver Operating Characteristic Analysis to Evaluate Biomarkers for Disease," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1099-1107, December. [Downloadable!] (restricted)
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This page was last updated on 2009-12-23.


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