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Dispersion parameter extension of precise generalized linear mixed model asymptotics

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  • Bhaskaran, Aishwarya
  • Wand, Matt P.

Abstract

We extend a recent asymptotic normality theorem for generalized linear mixed models to include the dispersion parameter. The maximum likelihood estimators of all model parameters have asymptotically normal distributions with asymptotic mutual independence between fixed effects, covariance and dispersion parameters.

Suggested Citation

  • Bhaskaran, Aishwarya & Wand, Matt P., 2023. "Dispersion parameter extension of precise generalized linear mixed model asymptotics," Statistics & Probability Letters, Elsevier, vol. 193(C).
    • Handle: RePEc:eee:stapro:v:193:y:2023:i:c:s0167715222002048
    DOI: 10.1016/j.spl.2022.109691
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    References listed on IDEAS

    as
    1. Bates, Douglas & Mächler, Martin & Bolker, Ben & Walker, Steve, 2015. "Fitting Linear Mixed-Effects Models Using lme4," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i01).
    2. Jiming Jiang & Matt P. Wand & Aishwarya Bhaskaran, 2022. "Usable and precise asymptotics for generalized linear mixed model analysis and design," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(1), pages 55-82, February.
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