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Combining Predictors for Classification Using the Area under the Receiver Operating Characteristic Curve

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  • Margaret Sullivan Pepe
  • Tianxi Cai
  • Gary Longton

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  • Margaret Sullivan Pepe & Tianxi Cai & Gary Longton, 2006. "Combining Predictors for Classification Using the Area under the Receiver Operating Characteristic Curve," Biometrics, The International Biometric Society, vol. 62(1), pages 221-229, March.
    • Handle: RePEc:bla:biomet:v:62:y:2006:i:1:p:221-229
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2005.00420.x
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    References listed on IDEAS

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    1. J. B. Copas, 2002. "Overestimation of the receiver operating characteristic curve for logistic regression," Biometrika, Biometrika Trust, vol. 89(2), pages 315-331, June.
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    4. Han, Aaron K., 1987. "Non-parametric analysis of a generalized regression model : The maximum rank correlation estimator," Journal of Econometrics, Elsevier, vol. 35(2-3), pages 303-316, July.
    5. Margaret Pepe & Holly Janes & Gary Longton & Wendy Leisenring & Polly Newcomb, 2004. "Limitations of the Odds Ratio in Gauging the Performance of a Diagnostic or Prognostic Marker," UW Biostatistics Working Paper Series 1035, Berkeley Electronic Press.
    6. Martin W. McIntosh & Margaret Sullivan Pepe, 2002. "Combining Several Screening Tests: Optimality of the Risk Score," Biometrics, The International Biometric Society, vol. 58(3), pages 657-664, September.
    7. Sherman, Robert P, 1993. "The Limiting Distribution of the Maximum Rank Correlation Estimator," Econometrica, Econometric Society, vol. 61(1), pages 123-137, January.
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    Cited by:

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    4. Shuangge Ma & Jian Huang, 2007. "Combining Multiple Markers for Classification Using ROC," Biometrics, The International Biometric Society, vol. 63(3), pages 751-757, September.
    5. Schmid Matthias & Hothorn Torsten & Krause Friedemann & Rabe Christina, 2012. "A PAUC-based Estimation Technique for Disease Classification and Biomarker Selection," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(5), pages 1-26, October.
    6. Qing Lu & Nancy Obuchowski & Sungho Won & Xiaofeng Zhu & Robert C. Elston, 2010. "Using the Optimal Robust Receiver Operating Characteristic (ROC) Curve for Predictive Genetic Tests," Biometrics, The International Biometric Society, vol. 66(2), pages 586-593, June.
    7. Xin Huang & Gengsheng Qin & Yixin Fang, 2011. "Optimal Combinations of Diagnostic Tests Based on AUC," Biometrics, The International Biometric Society, vol. 67(2), pages 568-576, June.
    8. Silver, Steven D. & Raseta, Marko & Bazarova, Alina, 2023. "Stochastic resonance in the recovery of signal from agent price expectations," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
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    13. Rocío Aznar-Gimeno & Luis M. Esteban & Gerardo Sanz & Rafael del-Hoyo-Alonso & Ricardo Savirón-Cornudella, 2021. "Incorporating a New Summary Statistic into the Min–Max Approach: A Min–Max–Median, Min–Max–IQR Combination of Biomarkers for Maximising the Youden Index," Mathematics, MDPI, vol. 9(19), pages 1-17, October.
    14. Yuanjia Wang & Huaihou Chen & Runze Li & Naihua Duan & Roberto Lewis-Fernández, 2011. "Prediction-Based Structured Variable Selection through the Receiver Operating Characteristic Curves," Biometrics, The International Biometric Society, vol. 67(3), pages 896-905, September.
    15. Osamu Komori, 2011. "A boosting method for maximization of the area under the ROC curve," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(5), pages 961-979, October.
    16. Rocío Aznar-Gimeno & Luis M. Esteban & Rafael del-Hoyo-Alonso & Ángel Borque-Fernando & Gerardo Sanz, 2022. "A Stepwise Algorithm for Linearly Combining Biomarkers under Youden Index Maximization," Mathematics, MDPI, vol. 10(8), pages 1-26, April.
    17. Graf Alexandra C. & Bauer Peter, 2009. "Model Selection Based on FDR-Thresholding Optimizing the Area under the ROC-Curve," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-20, June.
    18. Choi, Sungwoo & Park, Junyong, 2014. "Nonparametric additive model with grouped lasso and maximizing area under the ROC curve," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 313-325.
    19. Zhang Zhiwei & Ma Shujie & Nie Lei & Soon Guoxing, 2017. "A Quantitative Concordance Measure for Comparing and Combining Treatment Selection Markers," The International Journal of Biostatistics, De Gruyter, vol. 13(1), pages 1-24, May.
    20. Schneider, Matthew J. & Gorr, Wilpen L., 2015. "ROC-based model estimation for forecasting large changes in demand," International Journal of Forecasting, Elsevier, vol. 31(2), pages 253-262.
    21. Chen, Xiwei & Vexler, Albert & Markatou, Marianthi, 2015. "Empirical likelihood ratio confidence interval estimation of best linear combinations of biomarkers," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 186-198.
    22. Pablo Gonzalez Ginestet & Ales Kotalik & David M. Vock & Julian Wolfson & Erin E. Gabriel, 2021. "Stacked inverse probability of censoring weighted bagging: A case study in the InfCareHIV Register," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(1), pages 51-65, January.
    23. Conde David & Salvador Bonifacio & Rueda Cristina & Fernández Miguel A., 2013. "Performance and estimation of the true error rate of classification rules built with additional information. An application to a cancer trial," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 12(5), pages 583-602, October.

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