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.
@article{bwmeta1.element.doi-10_2478_demo-2014-0006,
author = {Fod\'e Tounkara and Louis-Paul Rivest},
title = {Some New Random Effect Models for Correlated Binary Responses},
journal = {Dependence Modeling},
volume = {2},
year = {2014},
zbl = {1328.62312},
language = {en},
url = {http://dml.mathdoc.fr/item/bwmeta1.element.doi-10_2478_demo-2014-0006}
}
Fodé Tounkara; Louis-Paul Rivest. Some New Random Effect Models for Correlated Binary Responses. Dependence Modeling, Tome 2 (2014) . http://gdmltest.u-ga.fr/item/bwmeta1.element.doi-10_2478_demo-2014-0006/
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