IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v77y2007i3p312-318.html
   My bibliography  Save this article

Chain graphs for multilevel models

Author

Listed:
  • Gottard, Anna
  • Rampichini, Carla

Abstract

In this paper, we propose a way to incorporate multilevel models within graphical models. We introduce three types of nodes for chain graphs to represent (1) individual within clusters, (2) clusters as latent variables and (3) interactive effects. In this way, the chain graph shows both the associations among individuals introduced by clusters and the random coefficients of a multilevel model. Then, independencies implied by the model can be read off the chain graph as well as the additional independence constraints under which the multilevel model reduces to a fixed effect regression model. The paper focuses on hierarchical Gaussian data structures, considering two-level models.

Suggested Citation

  • Gottard, Anna & Rampichini, Carla, 2007. "Chain graphs for multilevel models," Statistics & Probability Letters, Elsevier, vol. 77(3), pages 312-318, February.
  • Handle: RePEc:eee:stapro:v:77:y:2007:i:3:p:312-318
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-7152(06)00238-0
    Download Restriction: Full text for ScienceDirect subscribers only

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

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bruno ARPINO & Roberta VARRIALE, 2010. "Assessing The Quality Of Institutions’ Rankings Obtained Through Multilevel Linear Regression Models," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 5(1(11)_Spr), pages 7-22.

    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:eee:stapro:v:77:y:2007:i:3:p:312-318. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Haili He). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.