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Mixed-effects models with random cluster sizes

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  • Jiang, Jiming

Abstract

Mixed effects models are often used in situations where responses are clustered. In this paper, we show that in the case of generalized linear mixed models where the cluster sizes are assumed to be independent random variables, whose joint distribution is unknown but does not depend on the parameters involved in the mixed model, the standard maximum likelihood estimation procedure assuming nonrandom cluster sizes can be applied without modification. Some extensions of the result are discussed.

Suggested Citation

  • Jiang, Jiming, 2001. "Mixed-effects models with random cluster sizes," Statistics & Probability Letters, Elsevier, vol. 53(2), pages 201-206, June.
    • Handle: RePEc:eee:stapro:v:53:y:2001:i:2:p:201-206
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    References listed on IDEAS

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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.
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