IDEAS home Printed from https://ideas.repec.org/a/spr/stpapr/v64y2023i6d10.1007_s00362-022-01378-w.html
   My bibliography  Save this article

Structural multilevel models for longitudinal mediation analysis: a definition variable approach

Author

Listed:
  • Chiara Maria

    (University of Palermo)

Abstract

Mediation analysis is used to assess the direct effect of an exposure on an outcome, and the indirect effect transmitted by a third intermediate variable. Longitudinal data are the most suited to address mediation, since they allow mediational effects to manifest over time. There exist several approaches to deal with longitudinal mediation analysis, and one of the most widely spread, especially in social and behavioural sciences, consists of using multilevel models. However, when applied to mediational settings, these models present some limitations that can be overcome moving to a structural perspective. In this paper we propose a new formalisation of multilevel models within a structural framework combining the reticular action model notation and the definition variable approach. We reconsider two multilevel mediation designs very frequent in longitudinal settings from this structural perspective, discuss the advantages and limitations of such an approach and provide an empirical example.

Suggested Citation

  • Chiara Maria, 2023. "Structural multilevel models for longitudinal mediation analysis: a definition variable approach," Statistical Papers, Springer, vol. 64(6), pages 2161-2182, December.
  • Handle: RePEc:spr:stpapr:v:64:y:2023:i:6:d:10.1007_s00362-022-01378-w
    DOI: 10.1007/s00362-022-01378-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00362-022-01378-w
    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/s00362-022-01378-w?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:stpapr:v:64:y:2023:i:6:d:10.1007_s00362-022-01378-w. 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.