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prettyglm: Pretty Summaries of Generalized Linear Model Coefficients

One of the main advantages of using Generalised Linear Models is their interpretability. The goal of 'prettyglm' is to provide a set of functions which easily create beautiful coefficient summaries which can readily be shared and explained. 'prettyglm' helps users create coefficient summaries which include categorical base levels, variable importance and type III p.values. 'prettyglm' also creates beautiful relativity plots for categorical, continuous and splined coefficients.

Version: 1.0.1
Depends: R (≥ 4.1.0)
Imports: broom, car, dplyr, forcats, kableExtra, knitr, methods, plotly, RColorBrewer, stringr, tibble, tidycat, tidyr, tidyselect, vip
Suggests: rmarkdown, testthat
Published: 2023-09-06
DOI: 10.32614/CRAN.package.prettyglm
Author: Jared Fowler [cre, aut]
Maintainer: Jared Fowler <jared.fowler8 at gmail.com>
License: GPL-3
URL: https://jared-fowler.github.io/prettyglm/
NeedsCompilation: no
Materials: README NEWS
CRAN checks: prettyglm results

Documentation:

Reference manual: prettyglm.pdf
Vignettes: prettyglm: Beautiful Visualisations for Generalized Linear Models

Downloads:

Package source: prettyglm_1.0.1.tar.gz
Windows binaries: r-devel: prettyglm_1.0.1.zip, r-release: prettyglm_1.0.1.zip, r-oldrel: prettyglm_1.0.1.zip
macOS binaries: r-release (arm64): prettyglm_1.0.1.tgz, r-oldrel (arm64): prettyglm_1.0.1.tgz, r-release (x86_64): prettyglm_1.0.1.tgz, r-oldrel (x86_64): prettyglm_1.0.1.tgz
Old sources: prettyglm archive

Linking:

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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.