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multilevelmod: Model Wrappers for Multi-Level Models

Bindings for hierarchical regression models for use with the 'parsnip' package. Models include longitudinal generalized linear models (Liang and Zeger, 1986) <doi:10.1093/biomet/73.1.13>, and mixed-effect models (Pinheiro and Bates) <doi:10.1007/978-1-4419-0318-1_1>.

Version: 1.0.0
Depends: parsnip (≥ 1.0.0), R (≥ 2.10)
Imports: dplyr, lme4, purrr, rlang, tibble, withr
Suggests: covr, gee, ggplot2, knitr, nlme, rmarkdown, spelling, testthat, tidymodels
Published: 2022-06-17
Author: Max Kuhn ORCID iD [aut], Hannah Frick ORCID iD [aut, cre], RStudio [cph, fnd]
Maintainer: Hannah Frick <hannah at rstudio.com>
License: MIT + file LICENSE
URL: https://github.com/tidymodels/multilevelmod, http://multilevelmod.tidymodels.org/
NeedsCompilation: no
Language: en-US
Materials: README NEWS
In views: MixedModels
CRAN checks: multilevelmod results

Documentation:

Reference manual: multilevelmod.pdf
Vignettes: Get Started

Downloads:

Package source: multilevelmod_1.0.0.tar.gz
Windows binaries: r-devel: multilevelmod_1.0.0.zip, r-release: multilevelmod_1.0.0.zip, r-oldrel: multilevelmod_1.0.0.zip
macOS binaries: r-release (arm64): multilevelmod_1.0.0.tgz, r-oldrel (arm64): multilevelmod_1.0.0.tgz, r-release (x86_64): multilevelmod_1.0.0.tgz, r-oldrel (x86_64): multilevelmod_1.0.0.tgz
Old sources: multilevelmod archive

Reverse dependencies:

Reverse suggests: tidyAML

Linking:

Please use the canonical form https://CRAN.R-project.org/package=multilevelmod to link to this page.

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.
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