IDEAS home Printed from https://ideas.repec.org/a/taf/lstaxx/v52y2023i21p7709-7717.html
   My bibliography  Save this article

Bayesian bivariate bent-cable model for longitudinal data

Author

Listed:
  • Getachew A. Dagne

Abstract

Growth curve models are often used to describe a developmental course of a longitudinal response. This paper extends such models to assess multiphasic patterns of developmental trajectories for multivariate response variables. The multiphasic patterns are identified using a bivariate bent-cable model in the context of multivariate growth models. The approach allows for the simultaneous estimation of parameters of multiphasic changes in each response, and also takes into account the correlations among outcomes and random effects for repeated observations over time. The proposed methods are demonstrated using real data from an AIDS clinical study.

Suggested Citation

  • Getachew A. Dagne, 2023. "Bayesian bivariate bent-cable model for longitudinal data," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 52(21), pages 7709-7717, November.
  • Handle: RePEc:taf:lstaxx:v:52:y:2023:i:21:p:7709-7717
    DOI: 10.1080/03610926.2022.2053544
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03610926.2022.2053544
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/03610926.2022.2053544?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.

    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:taf:lstaxx:v:52:y:2023:i:21:p:7709-7717. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/lsta .

    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.