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glmmrOptim
View on CRAN: Click
here
Download and install glmmrOptim package within the R console
Install from CRAN:
install.packages("glmmrOptim")
Install from Github:
library("remotes")
install_github("cran/glmmrOptim")
Install by package version:
library("remotes")
install_version("glmmrOptim", "0.3.6")
Attach the package and use:
library("glmmrOptim")
Maintained by
Sam Watson
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.glmmrOptim . https://github.com/samuel-watson/glmmrOptim/issues . https://github.com/samuel-watson/glmmrOptim . glmmrOptim results . glmmrOptim.pdf . glmmrOptim_0.3.6.tar.gz . glmmrOptim_0.3.6.zip . glmmrOptim_0.3.6.zip . glmmrOptim_0.3.6.zip . glmmrOptim_0.3.6.tgz . glmmrOptim_0.3.6.tgz . glmmrOptim_0.3.6.tgz . glmmrOptim_0.3.6.tgz . glmmrOptim_0.3.6.tgz . glmmrOptim_0.3.6.tgz . glmmrOptim archive . https://CRAN.R-project.org/package=glmmrOptim .
First Published: 2023-01-20
Latest Update: 2023-12-06
Description:
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 for a
detailed manual on model specification. A detailed discussion of the methods in this
package can be found in Watson and Pan (2022) .
How to cite:
Sam Watson (2023). glmmrOptim: Approximate Optimal Experimental Designs Using Generalised Linear Mixed Models. R package version 0.3.6, https://cran.r-project.org/web/packages/glmmrOptim. Accessed 29 Mar. 2025.
Previous versions and publish date:
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Other R packages that glmmrOptim depends,
imports, suggests or enhances
Complete documentation for glmmrOptim
Functions, R codes and Examples using
the glmmrOptim R package
Some associated functions: DesignSpace . GradRobustStep . apportion .
Some associated R codes: R6designspace.R . RcppExports.R . apportion.R . Full glmmrOptim package functions and examples
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