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>.
Last updated 8 months ago
cppopenmp
3.00 score 1 stars 546 downloadscrctStepdown - Univariate Analysis of Cluster Trials with Multiple Outcomes
Frequentist statistical inference for cluster randomised trials with multiple outcomes that controls the family-wise error rate and provides nominal coverage of confidence sets. A full description of the methods can be found in Watson et al. (2023) <doi:10.1002/sim.9831>.
Last updated 1 years ago
cppopenmp
1.00 score 1 scripts 298 downloads