Easily simulates regression models, including both simple regression and generalized linear mixed models with up to three level of nesting. Power simulations that are flexible allowing the specification of missing data, unbalanced designs, and different random error distributions are built into the package.
| Version: | 0.6.0 |
| Depends: | R (≥ 3.3.0), stats, Matrix, dplyr, purrr, tidyr, tibble |
| Suggests: | knitr, lme4, nlme, testthat, shiny, e1071, ggplot2 |
| Published: | 2017-07-24 |
| Author: | Brandon LeBeau [aut, cre] |
| Maintainer: | Brandon LeBeau <lebebr01+simglm at gmail.com> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | simglm results |
| Reference manual: | simglm.pdf |
| Vignettes: |
Simulate generalized linear models with simglm Introduction to simglm Simulate Missing Data Power with simglm Unbalanced Data |
| Package source: | simglm_0.6.0.tar.gz |
| Windows binaries: | r-devel: simglm_0.6.0.zip, r-release: simglm_0.6.0.zip, r-oldrel: simglm_0.6.0.zip |
| OS X binaries: | r-release: simglm_0.6.0.tgz, r-oldrel: simglm_0.6.0.tgz |
| Old sources: | simglm archive |
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