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) .


Reference manual

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install.packages("glmmrOptim")

0.5.1 by Sam Watson, 4 months ago


https://github.com/samuel-watson/glmmrOptim


Report a bug at https://github.com/samuel-watson/glmmrOptim/issues


Browse source code at https://github.com/cran/glmmrOptim


Authors: Sam Watson [aut, cre] , Yi Pan [aut]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports methods, Rcpp, digest

Depends on Matrix, glmmrBase

Linking to Rcpp, RcppEigen, RcppProgress, glmmrBase, SparseChol, BH, rminqa

System requirements: GNU make


See at CRAN