bruceR

BRoadly Useful Convenient and Efficient R functions that BRing Users Concise and Elegant R data analyses.

The package includes easy-to-use functions for (1) basic use and analysis; (2) multivariate computation; (3) reliability and validity analysis; (4) multi-factor analysis of variance (ANOVA), simple-effect analysis, and post-hoc multiple comparison; and (5) advanced toolbox and tidy report of statistical models.

Author

包寒吴霜 | Bao H.-W.-S.

E-mail: baohws@foxmail.com

Website: psychbruce.github.io

ResearchGate | GitHub | 知乎

Citation

• Bao, H.-W.-S. (2021). bruceR: Broadly useful convenient and efficient R functions. R package version 0.x.x. https://CRAN.R-project.org/package=bruceR or https://github.com/psychbruce/bruceR

User Guide

Release Notes

Installation

## Method 1: Install from CRAN
install.packages("bruceR")

## Method 2: Install from GitHub
install.packages("devtools")
devtools::install_github("psychbruce/bruceR", force=TRUE, upgrade=FALSE)

Tips:

1. Please restart (close and reopen) RStudio before installation.
2. If you see a dialog asking "Do you want to install from sources the package which needs compilation?", it would be better to choose "No" (to save your time).
3. If you fail to install, please read carefully the warning messages and find out the key R package(s) causing the failure, manually uninstall and reinstall these R package(s), and then retry the main installation.
4. It would be better to update R to its latest version (v4.0+).
5. It would be better to download and install Rtools.exe on Windows system.

Package Dependency

bruceR depends on many important R packages.

Loading bruceR by library(bruceR) will also load these R packages for you:

• [Data]:

  • rio: Data import and export (for all file formats).
  • dplyr: Data manipulation and processing.
  • tidyr: Data cleaning and reshaping.
  • stringr: Toolbox for string operation (with regular expressions).
  • forcats: Toolbox for factor manipulation (for categorical variables).
  • data.table: Advanced data.frame with higher efficiency.

• [Stat]:

  • psych: Toolbox for psychological and psychometric research.
  • emmeans: Toolbox for estimated marginal means and contrasts.
  • effectsize: Indices of effect size and standardized parameters.
  • performance: Assessment of regression models performance.

• [Plot]:

  • ggplot2: Data visualization.
  • cowplot: Advanced toolbox for ggplot2 (arrange multiple plots and add labels).
  • see: Advanced toolbox for ggplot2 (extra geoms, scales, themes, and color palettes).

Main Functions in bruceR

1. Basic Use and Analysis

   • set.wd()
   • pkg_depend(), pkg_install_suggested()
   • formatF(), formatN()
   • Print(), Glue()
   • Describe(), Freq(), Corr(), cor_diff()
   • LOOKUP(), RANDBETWEEN()
   • %notin%, %partin%, %allin%, %nonein%, %anyin%

2. Multivariate Computation

   • RECODE(), RESCALE()
   • SUM(), MEAN(), STD(), MODE(), COUNT(), CONSEC()

3. Reliability and Validity Analysis

   • Alpha()
   • EFA()
   • CFA()

4. Multi-Factor ANOVA, Simple-Effect Analysis, and Post-Hoc Multiple Comparison

   • MANOVA()
   • EMMEANS()

5. Advanced Toolbox and Tidy Report of Statistical Models

   • grand_mean_center(), group_mean_center()
   • regress(), GLM_summary(), HLM_summary()
   • model_summary()
   • med_summary()
   • ccf_plot()
   • granger_test()

6. Theme for ggplot2

   • theme_bruce()

Learn More From Help Pages

library(bruceR)

## Overview
help("bruceR")
help(bruceR)
?bruceR

## See help pages of functions
## (use `?function` or `help(function)`)
?Describe
?Corr
?SUM
?MEAN
?MANOVA
?EMMEANS
?model_summary
?med_summary
?GLM_summary
?HLM_summary
...