A note on conditional aic for linear mixed-effects models
The conventional model selection criterion, the Akaike information criterion, aic , has been applied to choose candidate models in mixed-effects models by the consideration of marginal likelihood. Vaida & Blanchard (2005) demonstrated that such a marginal aic and its small sample correction are inappropriate when the research focus is on clusters. Correspondingly, these authors suggested the use of conditional aic . Their conditional aic is derived under the assumption that the variance-covariance matrix or scaled variance-covariance matrix of random effects is known. This note provides a general conditional aic but without these strong assumptions. Simulation studies show that the proposed method is promising. Copyright 2008, Oxford University Press.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 95 (2008)
Issue (Month): 3 ()
|Contact details of provider:|| Postal: |
Fax: 01865 267 985
Web page: http://biomet.oxfordjournals.org/
|Order Information:||Web: http://www.oup.co.uk/journals|
When requesting a correction, please mention this item's handle: RePEc:oup:biomet:v:95:y:2008:i:3:p:773-778. 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: (Oxford University Press)or (Christopher F. Baum)
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.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 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.