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Some New Random Effect Models for Correlated Binary Responses

Author

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  • Tounkara Fodé
  • Rivest Louis-Paul

    (Department of Mathematics and Statistics, Université Laval„ 1045 av. de la Médecine, Québec (Québec) G1V 0A6 Canada)

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.

Suggested Citation

  • Tounkara Fodé & Rivest Louis-Paul, 2014. "Some New Random Effect Models for Correlated Binary Responses," Dependence Modeling, De Gruyter, vol. 2(1), pages 1-15, December.
    • Handle: RePEc:vrs:demode:v:2:y:2014:i:1:p:15:n:6
    DOI: 10.2478/demo-2014-0006
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    References listed on IDEAS

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    1. Guangyong Zou & Allan Donner, 2004. "Confidence Interval Estimation of the Intraclass Correlation Coefficient for Binary Outcome Data," Biometrics, The International Biometric Society, vol. 60(3), pages 807-811, September.
    2. Martin S. Ridout & Clarice G. B. Demétrio & David Firth, 1999. "Estimating Intraclass Correlation for Binary Data," Biometrics, The International Biometric Society, vol. 55(1), pages 137-148, March.
    3. Shoukri, Mohamed M. & Kumar, Pranesh & Colak, Dilek, 2011. "Analyzing dependent proportions in cluster randomized trials: Modeling inter-cluster correlation via copula function," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1226-1235, March.
    4. Catalina Stefanescu & Bruce W. Turnbull, 2003. "Likelihood Inference for Exchangeable Binary Data with Varying Cluster Sizes," Biometrics, The International Biometric Society, vol. 59(1), pages 18-24, March.
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