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Likelihood inference in generalized linear mixed models with two components of dispersion using data cloning

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  • Torabi, Mahmoud

Abstract

This paper studies generalized linear mixed models (GLMMs) with two components of dispersion. The frequentist analysis of linear mixed model (LMM), and particularly of GLMM, is computationally difficult. On the other hand, the advent of the Markov chain Monte Carlo algorithm has made the Bayesian analysis of LMM and GLMM computationally convenient. The recent introduction of the method of data cloning has made frequentist analysis of mixed models also equally computationally convenient. We use data cloning to conduct frequentist analysis of GLMMs with two components of dispersion based on maximum likelihood estimation (MLE). The resultant estimators of the model parameters are efficient. We discuss the performance of the MLE using the well known salamander mating data, and also through simulation studies.

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  • Torabi, Mahmoud, 2012. "Likelihood inference in generalized linear mixed models with two components of dispersion using data cloning," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4259-4265.
    • Handle: RePEc:eee:csdana:v:56:y:2012:i:12:p:4259-4265
    DOI: 10.1016/j.csda.2012.04.008
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    1. J. G. Booth & J. P. Hobert, 1999. "Maximizing generalized linear mixed model likelihoods with an automated Monte Carlo EM algorithm," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(1), pages 265-285.
    2. Lele, Subhash R. & Nadeem, Khurram & Schmuland, Byron, 2010. "Estimability and Likelihood Inference for Generalized Linear Mixed Models Using Data Cloning," Journal of the American Statistical Association, American Statistical Association, vol. 105(492), pages 1617-1625.
    3. Hamilton, James D., 1986. "A standard error for the estimated state vector of a state-space model," Journal of Econometrics, Elsevier, vol. 33(3), pages 387-397, December.
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    Cited by:

    1. Anna Gottard & Giorgio Calzolari, 2014. "Alternative estimating procedures for multiple membership logit models with mixed effects: indirect inference and data cloning," Econometrics Working Papers Archive 2014_07, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    2. Pedro Chaim & Márcio Poletti Laurini, 2022. "Data Cloning Estimation and Identification of a Medium-Scale DSGE Model," Stats, MDPI, vol. 6(1), pages 1-13, December.

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