# Some New Random Effect Models for Correlated Binary Responses

Fodé Tounkara; Louis-Paul Rivest

Dependence Modeling (2014)

- Volume: 2, Issue: 1, page 73-87, electronic only
- ISSN: 2300-2298

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topFodé Tounkara, and Louis-Paul Rivest. "Some New Random Effect Models for Correlated Binary Responses." Dependence Modeling 2.1 (2014): 73-87, electronic only. <http://eudml.org/doc/268680>.

@article{FodéTounkara2014,

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.},

author = {Fodé Tounkara, Louis-Paul Rivest},

journal = {Dependence Modeling},

keywords = {Multivariate exchangeable copulas; Exchangeable binary data; Profile interval; Maximum likelihood; multivariate exchangeable copulas; exchangeable binary data; profile interval; maximum likelihood},

language = {eng},

number = {1},

pages = {73-87, electronic only},

title = {Some New Random Effect Models for Correlated Binary Responses},

url = {http://eudml.org/doc/268680},

volume = {2},

year = {2014},

}

TY - JOUR

AU - Fodé Tounkara

AU - Louis-Paul Rivest

TI - Some New Random Effect Models for Correlated Binary Responses

JO - Dependence Modeling

PY - 2014

VL - 2

IS - 1

SP - 73

EP - 87, electronic only

AB - 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.

LA - eng

KW - Multivariate exchangeable copulas; Exchangeable binary data; Profile interval; Maximum likelihood; multivariate exchangeable copulas; exchangeable binary data; profile interval; maximum likelihood

UR - http://eudml.org/doc/268680

ER -

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