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rfriend

Overview

rfriend is an R package designed to streamline data analysis and statistical testing by wrapping complex or repetitive code into convenient, user-friendly functions prefixed with f_. Its primary focus is data exploration, statistical tests, and creating publication-ready output in multiple formats including PDF, Microsoft Word, and Excel.

The package helps you write shorter code while producing well-formatted summaries, visualizations, and statistical tests, automatically handling data transformations, assumption checking, and post hoc testing.

Features

• Summary Tables: f_summary() generates comprehensive summary tables.
• Data Transformations:
  • f_boxcox() for Box-Cox transformations (wrapping MASS/boxcox and rcompanion)
    
  • f_bestNormalize() wraps and extends normalization from the bestNormalize package.
• Visualizations: Easily create:
  • Boxplots (f_boxplot())
    
  • QQ-plots (f_qqnorm())
    
  • Histograms (f_hist())
    
  • Density plots
• Statistical Tests: Run and visualize tests on multiple variables and predictors, with automatic assumption checking and post hoc analysis:
  • ANOVA: f_aov()
    
  • Kruskal-Wallis: f_kruskal_test()
    
  • Generalized Linear Models: f_glm()
    
  • Chi-square Tests: f_chisq_test()
• Model Comparison: Compare models easily with f_model_comparison().
• Utilities:
  • f_clear() clears the workspace and restarts R.
    
  • f_setwd() sets working directory to the current script’s location.
    
  • f_theme() switches RStudio themes quickly.
    
  • f_factors() converts multiple dataframe columns to factors.

Installation

rfriend requires R (>= 4.4.0) and several dependencies (see DESCRIPTION for details). You can install the latest released version from CRAN with:

install.packages("rfriend")

If you want the latest development version (if available on GitHub):

# install.packages("devtools")

devtools::install_github("delde001/rfriend")

Basic Usage

library(rfriend)

# Summary of your dataset
  f_summary(your_dataframe)

# Run ANOVA on multiple response variables
  f_aov(response_var1 +  response_var1 ~ predictor1 * predictor2, data = your_dataframe)

# Create a boxplot of a variable
  data(mtcars)
  f_boxplot(hp + disp ~ gear*cyl,
             data=mtcars,
             boxplot_explanation = FALSE,
             output_type = "word"
             )

# Perform Box-Cox transformation
  transformed <- f_boxcox(your_dataframe$variable)

# Create a boxplot of a variable
  data(mtcars)
  f_boxplot(hp + disp ~ gear*cyl,
             data=mtcars,
             boxplot_explanation = FALSE,
             output_type = "word"
             )

# Perform Box-Cox transformation
transformed <- f_boxcox(your_dataframe$variable)

# Clear workspace and restart R
  f_clear()

For detailed usage and examples, please refer to the package vignettes and help files.

Known Issues

• When loading rfriend, you may see harmless warnings about S3 method overwrites related to nobs.fitdistr and nobs.multinom due to imported packages (MuMIn, rstatix). These do not affect the functionality.

Contributing

Contributions, bug reports, and feature requests are very welcome! Please open an issue or submit a pull request on GitHub.

Before contributing, please ensure:

• You have tested your changes locally.
• Code is properly documented using roxygen2.
• You follow the existing style and conventions.

License

This package is licensed under GPL-3.

Contact

Author and maintainer: Sander H. van Delden
Email: plantmind@proton.me

Feel free to reach out for support, feature requests, or collaborations.

Thank you for using rfriend!

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.