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• W3214236169 abstract "Abstract We derive precise asymptotic results that are directly usable for confidence intervals and Wald hypothesis tests for likelihood-based generalized linear mixed model analysis. The essence of our approach is to derive the exact leading term behaviour of the Fisher information matrix when both the number of groups and number of observations within each group diverge. This leads to asymptotic normality results with simple studentizable forms. Similar analyses result in tractable leading term forms for the determination of approximate locally D-optimal designs." @default.
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• W3214236169 date "2021-11-14" @default.
• W3214236169 modified "2023-10-18" @default.
• W3214236169 title "Usable and Precise Asymptotics for Generalized Linear Mixed Model Analysis and Design" @default.
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• W3214236169 doi "https://doi.org/10.1111/rssb.12473" @default.
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