IDEAS home Printed from https://ideas.repec.org/a/oup/biomet/v103y2016i4p817-828..html
   My bibliography  Save this article

Optimal stratification in outcome prediction using baseline information

Author

Listed:
  • Florence H. Yong
  • Lu Tian
  • Sheng Yu
  • Tianxi Cai
  • L. J. Wei

Abstract

A common practice in predictive medicine is to use current study data to construct a stratification procedure, which groups subjects according to baseline information and forms stratum-specific prevention or intervention strategies. A desirable stratification scheme would not only have small intra-stratum variation but also have a clinically meaningful discriminatory capability. We show how to obtain optimal stratification rules with such desirable properties from fitting a set of regression models relating the outcome to baseline covariates and creating scoring systems for predicting potential outcomes. We propose that all available optimal stratifications be evaluated with an independent dataset to select a final stratification. Lastly, we obtain inferential results for this selected stratification scheme with a holdout dataset. When only one study of moderate size is available, we combine the first two steps via crossvalidation. Extensive simulation studies are used to compare the proposed stratification strategy with alternatives. We illustrate the new proposal using an AIDS clinical trial for binary outcomes and a cardiovascular clinical study for censored event time outcomes.

Suggested Citation

  • Florence H. Yong & Lu Tian & Sheng Yu & Tianxi Cai & L. J. Wei, 2016. "Optimal stratification in outcome prediction using baseline information," Biometrika, Biometrika Trust, vol. 103(4), pages 817-828.
    • Handle: RePEc:oup:biomet:v:103:y:2016:i:4:p:817-828.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/biomet/asw049
    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. Patrick Royston, 2006. "Explained variation for survival models," Stata Journal, StataCorp LP, vol. 6(1), pages 83-96, March.
    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. Yu, Haiyan & Yang, Ching-Chi & Yu, Ping, 2023. "Constrained optimization for stratified treatment rules in reducing hospital readmission rates of diabetic patients," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1355-1364.
    2. Danutė Krapavickaitė, 2022. "Impact of Stratum Composition Changes on the Accuracy of the Estimates in a Sample Survey," Mathematics, MDPI, vol. 10(7), pages 1-21, March.

    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. David Lodge & Marta Rodriguez-Vives, 2013. "How long can austerity persist? The factors that sustain fiscal consolidations," European Journal of Government and Economics, Europa Grande, vol. 2(1), pages 5-24, June.
    2. Leive, Adam, 2018. "Dying to win? Olympic Gold medals and longevity," Journal of Health Economics, Elsevier, vol. 61(C), pages 193-204.
    3. Nir Y. Krakauer & Jesse C. Krakauer, 2021. "Association of X-ray Absorptiometry Body Composition Measurements with Basic Anthropometrics and Mortality Hazard," IJERPH, MDPI, vol. 18(15), pages 1-13, July.
    4. Janez Stare & Maja Pohar Perme & Robin Henderson, 2011. "A Measure of Explained Variation for Event History Data," Biometrics, The International Biometric Society, vol. 67(3), pages 750-759, September.
    5. M Fernanda Lima-Costa & James Macinko & Juliana Vaz de Melo Mambrini & Cibele C Cesar & Sérgio V Peixoto & Wagner C S Magalhães & Bernardo L Horta & Mauricio Barreto & Erico Castro-Costa & Josélia O A, 2015. "Genomic Ancestry, Self-Rated Health and Its Association with Mortality in an Admixed Population: 10 Year Follow-Up of the Bambui-Epigen (Brazil) Cohort Study of Ageing," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-14, December.
    6. Klein, Daniel, 2018. "Executive turnover and the valuation of stock options," Journal of Corporate Finance, Elsevier, vol. 48(C), pages 76-93.
    7. Nir Y. Krakauer & Jesse C. Krakauer, 2020. "Association of Body Shape Index (ABSI) with Hand Grip Strength," IJERPH, MDPI, vol. 17(18), pages 1-12, September.

    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:103:y:2016:i:4:p:817-828.. 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: 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.