Second term improvement to generalized linear mixed model asymptotics

Luca Maestrini, Aishwarya Bhaskaran, Matt. P Wand

    Research output: Contribution to journalArticlepeer-review

    Abstract

    A recent article by on generalized linear mixed model asymptotics derived the rates of convergence for the asymptotic variances of maximum likelihood estimators. If m denotes the number of groups and n is the average within-group sample size then the asymptotic variances have orders m-1 and (mn)-1, depending on the parameter. We extend this theory to provide explicit forms of the (mn)-1 second terms of the asymptotically harder-to-estimate parameters. Improved accuracy of statistical inference and planning are consequences of our theory.
    Original languageEnglish
    Pages (from-to)1077-1084
    Number of pages8
    JournalBiometrika
    Volume111
    Issue number3
    DOIs
    Publication statusPublished - 29 Jan 2024

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