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Multilevel models (mixed effects models) are the statistical tool of choice for analyzing multilevel data (Searle et al, 2009). These models account for the correlated nature of observations within higher level units by adding group-level error terms that augment the singular residual error of a standard OLS regression. Multilevel and mixed effects models often require specialized data pre-processing and further post-estimation derivations and graphics to gain insight into model results. The package presented here, 'mlmtools', is a suite of pre- and post-estimation tools for multilevel models in 'R'. Package implements post-estimation tools designed to work with models estimated using 'lme4”s (Bates et al., 2014) lmer() function, which fits linear mixed effects regression models. Searle, S. R., Casella, G., & McCulloch, C. E. (2009, ISBN:978-0470009598). Bates, D., Mächler, M., Bolker, B., & Walker, S. (2014) <doi:10.18637/jss.v067.i01>.
Version: | 1.0.2 |
Depends: | R (≥ 3.5.0) |
Imports: | lme4, stats, ggplot2 |
Published: | 2022-10-26 |
DOI: | 10.32614/CRAN.package.mlmtools |
Author: | Laura Jamison [aut, cre], Jessica Mazen [aut], Erik Ruzek [aut], Gus Sjobeck [ctb] |
Maintainer: | Laura Jamison <lj5yn at virginia.edu> |
License: | GPL (≥ 3) |
NeedsCompilation: | no |
Materials: | README |
In views: | MixedModels |
CRAN checks: | mlmtools results |
Reference manual: | mlmtools.pdf |
Package source: | mlmtools_1.0.2.tar.gz |
Windows binaries: | r-devel: mlmtools_1.0.2.zip, r-release: mlmtools_1.0.2.zip, r-oldrel: mlmtools_1.0.2.zip |
macOS binaries: | r-release (arm64): mlmtools_1.0.2.tgz, r-oldrel (arm64): mlmtools_1.0.2.tgz, r-release (x86_64): mlmtools_1.0.2.tgz, r-oldrel (x86_64): mlmtools_1.0.2.tgz |
Old sources: | mlmtools archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.