IDEAS home Printed from https://ideas.repec.org/a/spr/stmapp/v34y2025i2d10.1007_s10260-025-00782-4.html
   My bibliography  Save this article

Improved joint modeling of longitudinal and survival data using a poisson regression approach

Author

Listed:
  • Yixiu Liu

    (University of Manitoba)

  • Mahmoud Torabi

    (University of Manitoba
    University of Manitoba)

  • Xuekui Zhang

    (University of Victoria)

  • Depeng Jiang

    (University of Manitoba)

Abstract

Data of repeated measurements (longitudinal) and time-to-events (survival) are commonly recorded in studies. The joint model (JM) of longitudinal and survival data, which allows simultaneously analysis of the two types of outcomes, has been extensively discussed recently. JMs are computationally intensive due to large number of parameters and the complexity of fitting the survival submodel. The centerpiece of the survival submodel is the piecewise constant proportional hazard (PCPH). An alternative to PCPH for analysing survival data is the auxiliary Poisson regression model. However, the use of this approach in JMs has not been discussed. In this study, we propose using the auxiliary Poisson model as the survival part in a JM within a Bayesian framework. We conducted comprehensive simulation studies to assess the performance of our proposed method under various conditions and compared it to a published R package for JMs called JMbayes. Additionally, we used data from the Manitoba Follow-Up Study to illustrate the advantages and feasibility of our proposed method. The findings have showed that using the auxiliary Poisson approach as the survival submodel is a very promising method for jointly modeling longitudinal and survival data, as it helps decrease the computing burden.

Suggested Citation

  • Yixiu Liu & Mahmoud Torabi & Xuekui Zhang & Depeng Jiang, 2025. "Improved joint modeling of longitudinal and survival data using a poisson regression approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 34(2), pages 325-344, May.
    • Handle: RePEc:spr:stmapp:v:34:y:2025:i:2:d:10.1007_s10260-025-00782-4
    DOI: 10.1007/s10260-025-00782-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10260-025-00782-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10260-025-00782-4?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
    ---><---

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

    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:spr:stmapp:v:34:y:2025:i:2:d:10.1007_s10260-025-00782-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.