simglm: Simulate Models Based on the Generalized Linear Model

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: 0.7.1
Depends: R (≥ 3.3.0)
Imports: stats, methods, Matrix, rlang, dplyr, purrr, broom
Suggests: knitr, lme4, nlme, testthat, shiny, e1071, ggplot2, tidyr, geepack, rmarkdown
Published: 2018-07-25
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

Downloads:

Reference manual: simglm.pdf
Vignettes: Simulate generalized linear models with simglm - legacy code
Introduction to simglm - Legacy Code
Power with simglm - legacy code
Simulation Argument Details for 'simglm'
Tidy Simulation with 'simglm'
Unbalanced Data - legacy code
Package source: simglm_0.7.1.tar.gz
Windows binaries: r-devel: simglm_0.7.1.zip, r-release: simglm_0.7.1.zip, r-oldrel: simglm_0.7.1.zip
OS X binaries: r-release: simglm_0.7.1.tgz, r-oldrel: simglm_0.7.1.tgz
Old sources: simglm archive

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