IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v13y2024i1p44-d1554004.html
   My bibliography  Save this article

A Simulation Study on Adaptive Assignment Versus Randomizations in Clinical Trials

Author

Listed:
  • Chien-Tai Lin

    (Department of Mathematics, Tamkang University, New Taipei City 251301, Taiwan)

  • Yun-Wei Li

    (Institute of Hospital and Health Care Administration, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan)

  • Yi-Jun Hong

    (Department of Mathematics, Tamkang University, New Taipei City 251301, Taiwan)

Abstract

This study investigates a sequential clinical trial comparing two treatments with dichotomous outcomes. We evaluate the effectiveness of five adaptive procedures and three randomization methods for assigning patients to different therapies. The primary objective is to identify an optimal treatment allocation policy that maximizes the proportion of successful outcomes in a trial. By comparing the performance of adaptive and randomized procedures, this research provides valuable insights for enhancing treatment allocation strategies in clinical trials, ultimately aiming to improve the overall success rates of therapeutic interventions.

Suggested Citation

  • Chien-Tai Lin & Yun-Wei Li & Yi-Jun Hong, 2024. "A Simulation Study on Adaptive Assignment Versus Randomizations in Clinical Trials," Mathematics, MDPI, vol. 13(1), pages 1-20, December.
    • Handle: RePEc:gam:jmathe:v:13:y:2024:i:1:p:44-:d:1554004
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/13/1/44/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/13/1/44/
    Download Restriction: no
    ---><---

    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:gam:jmathe:v:13:y:2024:i:1:p:44-:d:1554004. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.