IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v62y2006i1p221-229.html
   My bibliography  Save this article

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

Author

Listed:
  • Margaret Sullivan Pepe
  • Tianxi Cai
  • Gary Longton

Abstract

No abstract is available for this item.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2005.00420.x
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    2. Shinto Eguchi, 2002. "A class of logistic-type discriminant functions," Biometrika, Biometrika Trust, vol. 89(1), pages 1-22, March.
    3. 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.
    4. Stuart G. Baker, 2000. "Identifying Combinations of Cancer Markers for Further Study as Triggers of Early Intervention," Biometrics, The International Biometric Society, vol. 56(4), pages 1082-1087, December.
    5. 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.
    6. 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.
    7. Sherman, Robert P, 1993. "The Limiting Distribution of the Maximum Rank Correlation Estimator," Econometrica, Econometric Society, vol. 61(1), pages 123-137, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Weining Shen & Jing Ning & Ying Yuan & Anna S. Lok & Ziding Feng, 2018. "Model†free scoring system for risk prediction with application to hepatocellular carcinoma study," Biometrics, The International Biometric Society, vol. 74(1), pages 239-248, March.
    8. 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.
    9. 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.
    10. 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).
    11. Yuxin Zhu & Mei‐Cheng Wang, 2022. "Obtaining optimal cutoff values for tree classifiers using multiple biomarkers," Biometrics, The International Biometric Society, vol. 78(1), pages 128-140, March.
    12. Chiang, Chin-Tsang & Chiu, Chih-Heng, 2012. "Nonparametric and semiparametric optimal transformations of markers," Journal of Multivariate Analysis, Elsevier, vol. 103(1), pages 124-141, January.
    13. 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.
    14. 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.
    15. Zhongkai Liu & Howard D. Bondell, 2019. "Binormal Precision–Recall Curves for Optimal Classification of Imbalanced Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 11(1), pages 141-161, April.
    16. Kajal Lahiri & Liu Yang, 2023. "Predicting binary outcomes based on the pair-copula construction," Empirical Economics, Springer, vol. 64(6), pages 3089-3119, June.
    17. Sonia Pérez-Fernández & Pablo Martínez-Camblor & Peter Filzmoser & Norberto Corral, 2021. "Visualizing the decision rules behind the ROC curves: understanding the classification process," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(1), pages 135-161, March.
    18. 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.
    19. 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.
    20. Shuangge Ma & Jian Huang, 2007. "Combining Multiple Markers for Classification Using ROC," Biometrics, The International Biometric Society, vol. 63(3), pages 751-757, September.
    21. 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 1-22, June.
    22. 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.
    23. Yanqing Wang & Ying‐Qi Zhao & Yingye Zheng, 2020. "Learning‐based biomarker‐assisted rules for optimized clinical benefit under a risk constraint," Biometrics, The International Biometric Society, vol. 76(3), pages 853-862, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ming-Yueh Huang & Chin-Tsang Chiang, 2017. "Estimation and Inference Procedures for Semiparametric Distribution Models with Varying Linear-Index," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(2), pages 396-424, June.
    2. Yuxin Zhu & Mei‐Cheng Wang, 2022. "Obtaining optimal cutoff values for tree classifiers using multiple biomarkers," Biometrics, The International Biometric Society, vol. 78(1), pages 128-140, March.
    3. 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.
    4. Heikki Kauppi, 2016. "The Generalized Receiver Operating Characteristic Curve," Discussion Papers 114, Aboa Centre for Economics.
    5. Wei Dai & Ming Yang & Chaolong Wang & Tianxi Cai, 2017. "Sequence robust association test for familial data," Biometrics, The International Biometric Society, vol. 73(3), pages 876-884, September.
    6. Yingye Zheng & Tianxi Cai & Ziding Feng, 2006. "Application of the Time-Dependent ROC Curves for Prognostic Accuracy with Multiple Biomarkers," Biometrics, The International Biometric Society, vol. 62(1), pages 279-287, March.
    7. 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.
    8. Shuangge Ma & Jian Huang, 2007. "Combining Multiple Markers for Classification Using ROC," Biometrics, The International Biometric Society, vol. 63(3), pages 751-757, September.
    9. Margaret Pepe & Tianxi Cai & Zheng Zhang, 2004. "Combining Predictors for Classification Using the Area Under the ROC Curve," UW Biostatistics Working Paper Series 1021, Berkeley Electronic Press.
    10. Patrick Bajari & Jeremy Fox & Stephen Ryan, 2008. "Evaluating wireless carrier consolidation using semiparametric demand estimation," Quantitative Marketing and Economics (QME), Springer, vol. 6(4), pages 299-338, December.
    11. Khan, Shakeeb & Tamer, Elie, 2007. "Partial rank estimation of duration models with general forms of censoring," Journal of Econometrics, Elsevier, vol. 136(1), pages 251-280, January.
    12. Jochmans, Koen, 2015. "Multiplicative-error models with sample selection," Journal of Econometrics, Elsevier, vol. 184(2), pages 315-327.
    13. repec:hal:wpspec:info:hdl:2441/3vl5fe4i569nbr005tctlc8ll5 is not listed on IDEAS
    14. Shakeeb Khan & Arnaud Maurel & Yichong Zhang, 2023. "Informational Content of Factor Structures in Simultaneous Binary Response Models," Advances in Econometrics, in: Essays in Honor of Joon Y. Park: Econometric Methodology in Empirical Applications, volume 45, pages 385-410, Emerald Group Publishing Limited.
    15. Chin-Tsang Chiang & Shr-Yan Huang, 2009. "Estimation for the Optimal Combination of Markers without Modeling the Censoring Distribution," Biometrics, The International Biometric Society, vol. 65(1), pages 152-158, March.
    16. repec:spo:wpmain:info:hdl:2441/dambferfb7dfprc9m01h6f4h2 is not listed on IDEAS
    17. Drehmann, Mathias & Juselius, Mikael, 2014. "Evaluating early warning indicators of banking crises: Satisfying policy requirements," International Journal of Forecasting, Elsevier, vol. 30(3), pages 759-780.
    18. Koen Jochmans, 2011. "Identification in Bivariate binary-choice Models with elliptical innovations," Working Papers hal-01069483, HAL.
    19. Sokbae Lee & Myung Hwan Seo & Youngki Shin, 2017. "Correction," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 883-883, April.
    20. Gorgens, Tue & Horowitz, Joel L., 1999. "Semiparametric estimation of a censored regression model with an unknown transformation of the dependent variable," Journal of Econometrics, Elsevier, vol. 90(2), pages 155-191, June.
    21. repec:spo:wpmain:info:hdl:2441/3vl5fe4i569nbr005tctlc8ll5 is not listed on IDEAS
    22. Youngki Shin & Zvezdomir Todorov, 2021. "Exact computation of maximum rank correlation estimator," The Econometrics Journal, Royal Economic Society, vol. 24(3), pages 589-607.
    23. Debashis Ghosh, 2004. "Semiparametric methods for the binormal model with multiple biomarkers," The University of Michigan Department of Biostatistics Working Paper Series 1046, Berkeley Electronic Press.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:biomet:v:62:y:2006:i:1:p:221-229. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.