I’m happy to formally announce a major update to the simglm R package. In brief, the updated package contains a new more robust syntax for simulating data, adds parallel processing support for replicating the simulation (or power analysis) using the future.apply package/framework, and new updated vignettes showing off the many options available in the tidy simulation syntax.
The package can be installed with the following code:
install.packages("simglm") The package can then be loaded with:
The simglm package has an update on CRAN bumping the version up to 0.6.0. This update has added the ability to simulate count data (poisson) and also has fixed (I think) the Shiny app that comes with the package. As I have not posted about this package since the first CRAN release (v 0.5.0), I plan to give an overview of all that the package offers in addition to the new additions.
This is a quick note looking for any further feedback on the simglm package prior to CRAN submission later this week. The goal is to submit Thursday or Friday this week. The last few documentation finishing touches are happening now working toward a version 0.5.0 release on CRAN.
For those who have not seen this package yet, the aim is to simulate regression models (single level and multilevel models) as well as employ empirical power analyses based on Monte Carlo simulation.