IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this paper

Analyzing categorical data from split-plot and other multi-stratum experiments

Listed author(s):
  • GOOS, Peter
  • GILMOUR, Steven G.

Many factorial experiments yield categorical response data. Moreover, the experiments are often run under a restricted randomization for logistical reasons and/or because of time and cost constraints. The combination of categorical data and restricted randomization necessitates the use of generalized linear mixed models. In this paper, we demonstrate the use of Hasse diagrams for laying out the randomization structure of a complex factorial design involving seven two-level factors, four three-level factors and a five-level factor, and three repeated observations for each experimental unit. The Hasse diagrams form the basis of the mixed model analysis of the ordered categorical data produced by the experiment. We also discuss the added value of categorical data over binary data and difficulties with the estimation of variance components and, consequently, with the statistical inference. Finally, we show how to deal with repeats in the presence of categorical data, and describe a general strategy for building a suitable generalized linear mixed model.

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.

File URL:
Download Restriction: no

Paper provided by University of Antwerp, Faculty of Applied Economics in its series Working Papers with number 2010021.

in new window

Length: 37 pages
Date of creation: Sep 2010
Handle: RePEc:ant:wpaper:2010021
Contact details of provider: Postal:
Prinsstraat 13, B-2000 Antwerpen

Web page:

More information through EDIRC

No references listed on IDEAS
You can help add them by filling out this form.

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:ant:wpaper:2010021. 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: (Joeri Nys)

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.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.