Literature DB >> 7662840

A full likelihood procedure for analysing exchangeable binary data.

E O George1, D Bowman.   

Abstract

A full-likelihood procedure is proposed for analyzing correlated binary data under the assumption of exchangeability. The binomial and beta-binomial models are shown to occur as special cases correspondingly, respectively, to the choice of degenerate and beta-mixing distributions. For a finite exchangeable binary sequence of random variables, expressions for the joint distribution, moments, and correlations of all orders are derived. Maximum likelihood estimates of the moments of all orders are computed and used to estimate correlations and the distribution of the number of responses in a cluster. In an application to developmental toxicology data analysis, the procedure introduced is compared with a beta-binomial and a generalized estimating equation procedure in which mean response and intralitter correlation are linked to dose.

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Year:  1995        PMID: 7662840

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  4 in total

1.  Sums of Exchangeable Bernoulli Random Variables for Family and Litter Frequency Data.

Authors:  Chang Yu; Daniel Zelterman
Journal:  Comput Stat Data Anal       Date:  2008-01-01       Impact factor: 1.681

2.  Maximum Likelihood Estimation of Titer via a Power Family of Four-Parameter Logistic Model.

Authors:  Hongmei Yang; Jeanne Holden-Wiltse; David J Topham; John Treanor
Journal:  J Biopharm Stat       Date:  2017-09-05       Impact factor: 1.051

3.  Modeling clustered binary data with excess zero clusters.

Authors:  John Kwagyan; Victor Apprey
Journal:  Stat Methods Med Res       Date:  2016-12-19       Impact factor: 3.021

4.  Markov counting models for correlated binary responses.

Authors:  Forrest W Crawford; Daniel Zelterman
Journal:  Biostatistics       Date:  2015-03-19       Impact factor: 5.279

  4 in total

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