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prettyglm
View on CRAN: Click
here
Download and install prettyglm package within the R console
Install from CRAN:
install.packages("prettyglm")
Install from Github:
library("remotes")
install_github("cran/prettyglm")
Install by package version:
library("remotes")
install_version("prettyglm", "1.0.1")
Attach the package and use:
library("prettyglm")
Maintained by
Jared Fowler
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-06-24
Latest Update: 2023-09-06
Description:
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.
How to cite:
Jared Fowler (2021). prettyglm: Pretty Summaries of Generalized Linear Model Coefficients. R package version 1.0.1, https://cran.r-project.org/web/packages/prettyglm. Accessed 17 Apr. 2025.
Other packages that cited prettyglm R package
View prettyglm citation profile
Other R packages that prettyglm depends,
imports, suggests or enhances
Complete documentation for prettyglm
Functions, R codes and Examples using
the prettyglm R package
Some associated functions: actual_expected_bucketed . bank_data . clean_coefficients . cut3 . one_way_ave . predict_outcome . pretty_coefficients . pretty_relativities . splineit . titanic .
Some associated R codes: actual_expected_bucketed.R . bank.R . clean_coefficients.R . cut3.R . globals.R . one_way_ave.R . predict_outcome.R . pretty_coefficients.R . pretty_relativities.R . splineit.R . titanic.R . Full prettyglm package functions and examples
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