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ggcompare  

Mean Comparison in 'ggplot2'
View on CRAN: Click here


Download and install ggcompare package within the R console
Install from CRAN:
install.packages("ggcompare")

Install from Github:
library("remotes")
install_github("cran/ggcompare")

Install by package version:
library("remotes")
install_version("ggcompare", "0.0.6")



Attach the package and use:
library("ggcompare")
Maintained by
Hao Wang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-10-02
Latest Update: 2024-12-09
Description:
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).
How to cite:
Hao Wang (2024). ggcompare: Mean Comparison in 'ggplot2'. R package version 0.0.6, https://cran.r-project.org/web/packages/ggcompare. Accessed 07 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:43), 0.0.1 (2024-10-02 18:50), 0.0.2 (2024-10-07 13:00), 0.0.3 (2024-12-09 07:00), 0.0.4 (2025-08-20 14:30), 0.0.5 (2025-09-24 14:40)
Other packages that cited ggcompare R package
View ggcompare citation profile
Other R packages that ggcompare depends, imports, suggests or enhances
Complete documentation for ggcompare
Functions, R codes and Examples using the ggcompare R package
Full ggcompare package functions and examples
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