Approximate Optimal Experimental Designs Using Generalised Linear Mixed Models R package glmmrOptim version 0.5.1 CRAN Task View: MixedModels (https://CRAN.R-project.org/view=MixedModels) 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>. Software Depends: R (>= 3.4.0), Matrix, glmmrBase Imports: methods, Rcpp (>= 1.0.7), digest LinkingTo: Rcpp (>= 1.0.7), RcppEigen, RcppProgress, glmmrBase (>= 1.0.0), SparseChol (>= 0.2.1), BH, rminqa (>= 0.2.2) Sam Watson <S.I.Watson@bham.ac.uk> Comprehensive R Archive Network (CRAN) Sam Watson [aut, cre], Yi Pan [aut] GPL (>= 2) 2026-06-07 application/tgz https://CRAN.R-project.org/package=glmmrOptim doi:10.32614/CRAN.package.glmmrOptim