IDEAS home Printed from https://ideas.repec.org/a/oup/biomet/v97y2010i2p389-404.html
   My bibliography  Save this article

Calibrating parametric subject-specific risk estimation

Author

Listed:
  • T. Cai
  • L. Tian
  • Hajime Uno
  • Scott D. Solomon
  • L. J. Wei

Abstract

For modern evidence-based medicine, decisions on disease prevention or management strategies are often guided by a risk index system. For each individual, the system uses his/her baseline information to estimate the risk of experiencing a future disease-related clinical event. Such a risk scoring scheme is usually derived from an overly simplified parametric model. To validate a model-based procedure, one may perform a standard global evaluation via, for instance, a receiver operating characteristic analysis. In this article, we propose a method to calibrate the risk index system at a subject level. Specifically, we developed point and interval estimation procedures for t-year mortality rates conditional on the estimated parametric risk score. The proposals are illustrated with a dataset from a large clinical trial with post-myocardial infarction patients. Copyright 2010, Oxford University Press.

Suggested Citation

  • T. Cai & L. Tian & Hajime Uno & Scott D. Solomon & L. J. Wei, 2010. "Calibrating parametric subject-specific risk estimation," Biometrika, Biometrika Trust, vol. 97(2), pages 389-404.
  • Handle: RePEc:oup:biomet:v:97:y:2010:i:2:p:389-404
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/biomet/asq012
    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.

    Citations

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


    Cited by:

    1. Layla Parast & Beth Ann Griffin, 2017. "Landmark estimation of survival and treatment effects in observational studies," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(2), pages 161-182, April.
    2. Veronika Skrivankova & Patrick J. Heagerty, 2018. "Single index methods for evaluation of marker†guided treatment rules based on multivariate marker panels," Biometrics, The International Biometric Society, vol. 74(2), pages 663-672, June.
    3. Guanhua Chen & Donglin Zeng & Michael R. Kosorok, 2016. "Personalized Dose Finding Using Outcome Weighted Learning," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1509-1521, October.
    4. Yi Li & Lu Tian & Lee-Jen Wei, 2011. "Estimating Subject-Specific Dependent Competing Risk Profile with Censored Event Time Observations," Biometrics, The International Biometric Society, vol. 67(2), pages 427-435, June.
    5. Jan Beyersmann & Susanna Di Termini & Markus Pauly, 2013. "Weak Convergence of the Wild Bootstrap for the Aalen–Johansen Estimator of the Cumulative Incidence Function of a Competing Risk," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(3), pages 387-402, September.
    6. Denis Agniel & Tianxi Cai, 2017. "Analysis of multiple diverse phenotypes via semiparametric canonical correlation analysis," Biometrics, The International Biometric Society, vol. 73(4), pages 1254-1265, December.

    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:oup:biomet:v:97:y:2010:i:2:p:389-404. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Oxford University Press (email available below). General contact details of provider: https://academic.oup.com/biomet .

    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.