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: 0.0.2
Depends: R (≥ 4.1)
Imports: ggplot2
Published: 2024-10-07
DOI: 10.32614/CRAN.package.ggcompare
Author: Hao Wang ORCID iD [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_0.0.2.tar.gz
Windows binaries: r-devel: ggcompare_0.0.2.zip, r-release: ggcompare_0.0.2.zip, r-oldrel: ggcompare_0.0.2.zip
macOS binaries: r-release (arm64): ggcompare_0.0.2.tgz, r-oldrel (arm64): ggcompare_0.0.2.tgz, r-release (x86_64): ggcompare_0.0.2.tgz, r-oldrel (x86_64): ggcompare_0.0.2.tgz
Old sources: ggcompare archive

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