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glmmrOptim: Approximate Optimal Experimental Designs Using Generalised Linear Mixed Models
Optimal design analysis algorithms for any study design that can be represented or modelled as a generalised linear mixed model including cluster randomised trials, cohort studies, spatial and temporal epidemiological studies, and split-plot designs. See <https://github.com/samuel-watson/glmmrBase/blob/master/README.md> for a detailed manual on model specification. A detailed discussion of the methods in this package can be found in Watson, Hemming, and Girling (2023) <doi:10.1177/09622802231202379>.
Getting started
Browse package contents
Package details |
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| Author | Sam Watson [aut, cre], Yi Pan [aut] |
| Maintainer | Sam Watson <S.I.Watson@bham.ac.uk> |
| License | GPL (>= 2) |
| Version | 0.3.7 |
| URL | https://github.com/samuel-watson/glmmrOptim |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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