IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v23y2003i2p160-166.html
   My bibliography  Save this article

The Area under an ROC Curve with Limited Information

Author

Listed:
  • Wilbert B. van den Hout

Abstract

The area under the receiver operating characteristic (ROC) curve of a diagnostic test can be used as a summary measure for its discriminative ability. If only a single point of an ROC curve is available, then the entire form of the ROC curve is unknown and the area under it cannot be calculated. Assuming that the unknown ROC curve is either monotone or concave, lower and upper bounds are derived for the area. From these bounds, the minmax approximations are obtained. Compared to only assuming monotonicity, assuming that the unknown ROC curve is concave renders a higher minmax approximation for the area under it, with tighter bounds.

Suggested Citation

  • Wilbert B. van den Hout, 2003. "The Area under an ROC Curve with Limited Information," Medical Decision Making, , vol. 23(2), pages 160-166, March.
  • Handle: RePEc:sae:medema:v:23:y:2003:i:2:p:160-166
    DOI: 10.1177/0272989X03251246
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X03251246
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0272989X03251246?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Scott B. Cantor & Michael W. Kattan, 2000. "Determining the Area under the ROC Curve for a Binary Diagnostic Test," Medical Decision Making, , vol. 20(4), pages 468-470, October.
    2. Anna N. Angelos Tosteson & Colin B. Begg, 1988. "A General Regression Methodology for ROC Curve Estimation," Medical Decision Making, , vol. 8(3), pages 204-215, August.
    3. Yvonne T. Van Der Schouw & Huub Straatman & Andre L.M. Verbeek, 1994. "ROC Curves and the Areas under Them for Dichotomized Tests," Medical Decision Making, , vol. 14(4), pages 374-381, October.
    4. Jørgen Hilden, 1991. "The Area under the ROC Curve and Its Competitors," Medical Decision Making, , vol. 11(2), pages 95-101, June.
    Full references (including those not matched with items on IDEAS)

    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. Arthur De Sá Ferreira & Ney Meziat-Filho & Ana Paula Antunes Ferreira, 2021. "Double threshold receiver operating characteristic plot for three-modal continuous predictors," Computational Statistics, Springer, vol. 36(3), pages 2231-2245, September.
    2. Jin, Hua & Lu, Ying, 2009. "The ROC region of a regression tree," Statistics & Probability Letters, Elsevier, vol. 79(7), pages 936-942, April.
    3. Julianne Cassista & Julie Payne-Gagnon & Brigitte Martel & Marie-Pierre Gagnon, 2014. "Applying Theory to Understand and Modify Nurse Intention to Adhere to Recommendations regarding the Use of Filter Needles: An Intervention Mapping Approach," Nursing Research and Practice, Hindawi, vol. 2014, pages 1-8, July.
    4. Ziyi Li & Yijian Huang & Dattatraya Patil & Martin G. Sanda, 2023. "Covariate adjustment in continuous biomarker assessment," Biometrics, The International Biometric Society, vol. 79(1), pages 39-48, March.
    5. repec:jss:jstsof:08:i12 is not listed on IDEAS
    6. Bernd Lütkenhöner & Türker Basel, 2013. "Predictive Modeling for Diagnostic Tests with High Specificity, but Low Sensitivity: A Study of the Glycerol Test in Patients with Suspected Menière’s Disease," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-12, November.
    7. Rodríguez-Álvarez, María Xosé & Roca-Pardiñas, Javier & Cadarso-Suárez, Carmen, 2011. "A new flexible direct ROC regression model: Application to the detection of cardiovascular risk factors by anthropometric measures," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3257-3270, December.
    8. B Rey deCastro, 2019. "Cumulative ROC curves for discriminating three or more ordinal outcomes with cutpoints on a shared continuous measurement scale," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-16, August.
    9. Nasim Vahabi & Anoshirvan Kazemnejad & Somnath Datta, 2018. "A Marginalized Overdispersed Location Scale Model for Clustered Ordinal Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 80(1), pages 103-134, December.
    10. J Nevil Amos & Andrew F Bennett & Ralph Mac Nally & Graeme Newell & Alexandra Pavlova & James Q Radford & James R Thomson & Matt White & Paul Sunnucks, 2012. "Predicting Landscape-Genetic Consequences of Habitat Loss, Fragmentation and Mobility for Multiple Species of Woodland Birds," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-12, February.
    11. Sean F. Reardon & Benjamin R. Shear & Katherine E. Castellano & Andrew D. Ho, 2017. "Using Heteroskedastic Ordered Probit Models to Recover Moments of Continuous Test Score Distributions From Coarsened Data," Journal of Educational and Behavioral Statistics, , vol. 42(1), pages 3-45, February.
    12. Pahalage Dhanushka Sandaruwan & Champi Thusangi Wannige, 2021. "An improved deep learning model for hierarchical classification of protein families," PLOS ONE, Public Library of Science, vol. 16(10), pages 1-15, October.
    13. Rodríguez-Álvarez, María Xosé & Tahoces, Pablo G. & Cadarso-Suárez, Carmen & Lado, María José, 2011. "Comparative study of ROC regression techniques--Applications for the computer-aided diagnostic system in breast cancer detection," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 888-902, January.
    14. Yang, Hanfang & Zhao, Yichuan, 2012. "Smoothed empirical likelihood for ROC curves with censored data," Journal of Multivariate Analysis, Elsevier, vol. 109(C), pages 254-263.
    15. Yang, Hanfang & Zhao, Yichuan, 2015. "Smoothed jackknife empirical likelihood inference for ROC curves with missing data," Journal of Multivariate Analysis, Elsevier, vol. 140(C), pages 123-138.
    16. Maria G.M. Hunink & Douglas K. Richardson & Peter M. Doubilet & Colin B. Begg, 1990. "Testing for Fetal Pulmonary Maturity," Medical Decision Making, , vol. 10(3), pages 201-211, August.
    17. Lang, Joseph B., 1999. "Bayesian ordinal and binary regression models with a parametric family of mixture links," Computational Statistics & Data Analysis, Elsevier, vol. 31(1), pages 59-87, July.
    18. Benjamin R. Shear & Sean F. Reardon, 2021. "Using Pooled Heteroskedastic Ordered Probit Models to Improve Small-Sample Estimates of Latent Test Score Distributions," Journal of Educational and Behavioral Statistics, , vol. 46(1), pages 3-33, February.
    19. V. Robles & C. Bielza & P. Larrañaga & S. González & L. Ohno-Machado, 2008. "Optimizing logistic regression coefficients for discrimination and calibration using estimation of distribution algorithms," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(2), pages 345-366, December.
    20. D. J. Hand & C. Anagnostopoulos, 2023. "Notes on the H-measure of classifier performance," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 17(1), pages 109-124, March.

    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:sae:medema:v:23:y:2003:i:2:p:160-166. 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: SAGE Publications (email available below). General contact details of provider: .

    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.