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Dependence Modeling

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Some New Random Effect Models for Correlated Binary Responses

Fodé Tounkara
  • Department of Mathematics and Statistics, Université Laval„ 1045 av. de la Médecine, Québec (Québec) G1V 0A6 Canada
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Louis-Paul Rivest
  • Department of Mathematics and Statistics, Université Laval„ 1045 av. de la Médecine, Québec (Québec) G1V 0A6 Canada
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2014-12-01 | DOI: https://doi.org/10.2478/demo-2014-0006

Abstract

Exchangeable copulas are used to model an extra-binomial variation in Bernoulli experiments with a variable number of trials. Maximum likelihood inference procedures for the intra-cluster correlation are constructed for several copula families. The selection of a particular model is carried out using the Akaike information criterion (AIC). Profile likelihood confidence intervals for the intra-cluster correlation are constructed and their performance are assessed in a simulation experiment. The sensitivity of the inference to the specification of the copula family is also investigated through simulations. Numerical examples are presented.

Keywords: Multivariate exchangeable copulas; Exchangeable binary data; Profile interval; Maximum likelihood

MSC: 62H05

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About the article


Received: 2014-05-12

Accepted: 2014-10-16

Published Online: 2014-12-01


Citation Information: Dependence Modeling, Volume 2, Issue 1, ISSN (Online) 2300-2298, DOI: https://doi.org/10.2478/demo-2014-0006.

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© 2014 Fodé Tounkara, Louis-Paul Rivest. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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