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 language | English |
|---|---|
| Pages (from-to) | 1077-1084 |
| Number of pages | 8 |
| Journal | Biometrika |
| Volume | 111 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 29 Jan 2024 |
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