ggcompare: Mean Comparison in 'ggplot2'

Add mean comparison annotations to a 'ggplot'. This package provides an easy way to indicate if two or more groups are significantly different in a 'ggplot'. Usually you do not need to specify the test method, you only need to tell stat_compare() whether you want to perform a parametric test or a nonparametric test, and stat_compare() will automatically choose the appropriate test method based on your data. For comparisons between two groups, the p-value is calculated by t-test (parametric) or Wilcoxon rank sum test (nonparametric). For comparisons among more than two groups, the p-value is calculated by One-way ANOVA (parametric) or Kruskal-Wallis test (nonparametric).

Version:	0.0.3
Depends:	R (≥ 4.1)
Imports:	ggplot2
Published:	2024-12-09
DOI:	10.32614/CRAN.package.ggcompare
Author:	Hao Wang [aut, cre]
Maintainer:	Hao Wang <wanghao8772 at gmail.com>
BugReports:	https://github.com/HMU-WH/ggcompare/issues/
License:	Artistic-2.0
URL:	https://hmu-wh.github.io/ggcompare/, https://github.com/HMU-WH/ggcompare/
NeedsCompilation:	no
Materials:	NEWS
CRAN checks:	ggcompare results

Documentation:

Reference manual:

ggcompare.pdf

Downloads:

Package source:	ggcompare_0.0.3.tar.gz
Windows binaries:	r-devel: ggcompare_0.0.3.zip, r-release: ggcompare_0.0.3.zip, r-oldrel: ggcompare_0.0.3.zip
macOS binaries:	r-release (arm64): ggcompare_0.0.3.tgz, r-oldrel (arm64): ggcompare_0.0.3.tgz, r-release (x86_64): ggcompare_0.0.3.tgz, r-oldrel (x86_64): ggcompare_0.0.3.tgz
Old sources:	ggcompare archive

Linking:

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