Bayesian analysis of correlated proportions (Journal article)

Kateri, M./ Papaioannou, T./ Dellaportas, P.

In this paper we present a Bayesian analysis of 2£2 contingency tables, corresponding to matched pairs designs. We provide Bayes and empirical Bayes estimates for the cell probabilities of these tables as well as the Bayes factor for testing the equality of correlated proportions. The approximate highest posterior density (HPD) region for the difference of the correlated proportions is also obtained. Finally, a Bayesian variable selection approach is applied to a hierarchical logistic regression model and posterior model probabilities for the equality of the correlated proportions are estimated. This latter approach has the feature that the posterior model probabilities depend on the maindiagonal cells.
Institution and School/Department of submitter: Πανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μαθηματικών
Keywords: Bayes factor, empirical bayes, Gibbs variable selection, hierarchical,logistic regression, highest posterior density region, matched pairs, Markov chain Monte,Carlo.
Appears in Collections:Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά)

Files in This Item:
File Description SizeFormat 
Kateri-2001-bayesian analysis of.pdf189.56 kBAdobe PDFView/Open    Request a copy

 Please use this identifier to cite or link to this item:
  This item is a favorite for 0 people.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.