Skip to contents

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

This package includes easy-to-use functions for:

  1. Basic R programming (e.g., set working directory to the path of currently opened file; import/export data from/to files in any format; print tables to Microsoft Word);
  2. Multivariate computation (e.g., compute scale sums/means/… with reverse scoring);
  3. Reliability analyses and factor analyses (PCA, EFA, CFA);
  4. Descriptive statistics and correlation analyses;
  5. t-test, multi-factor analysis of variance (ANOVA), simple-effect analysis, and post-hoc multiple comparison;
  6. Tidy report of statistical models (to R Console and Microsoft Word);
  7. Mediation and moderation analyses (PROCESS);
  8. Additional toolbox for statistics and graphics.


Han-Wu-Shuang (Bruce) Bao 包寒吴霜




User Guide

NEWS (Changelog)

Chinese Documentation for bruceR: I. Overview

Chinese Documentation for bruceR: II. FAQ


Please always set dep=TRUE to install ALL package dependencies for FULL features!

## Method 1: Install from CRAN
install.packages("bruceR", dep=TRUE)  # dependencies=TRUE

## Method 2: Install from GitHub
devtools::install_github("psychbruce/bruceR", dep=TRUE, force=TRUE)


  • Good practices:
    • Restart RStudio before installation.
    • Update R to the latest version (v4.0+).
    • Install Rtools.exe (it is not an R package) on Windows system.
  • If you see “Do you want to restart R prior to install?”, choose “Yes” for the first time and then choose “No”.
  • If you fail to install, please carefully read the warning messages and find out the R package(s) causing the failure, manually uninstall and reinstall these R package(s), and then retry the main installation.

Package Dependency

bruceR depends on many important R packages.

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

  • [Data]:

    • data.table: Advanced data.frame with higher efficiency.
    • dplyr: Data manipulation and processing.
    • tidyr: Data cleaning and reshaping.
    • stringr: Toolbox for string operation (with regular expressions).
    • ggplot2: Data visualization.
  • [Stat]:

    • emmeans: Estimates of marginal means and multiple contrasts.
    • lmerTest: Linear mixed effects modeling (multilevel modeling).
    • effectsize: Effect sizes and standardized parameters.
    • performance: Performance of regression models.
    • interactions: Interaction and simple effect analyses.

Main Functions in bruceR

  1. Basic R Programming

  2. Multivariate Computation

  3. Reliability and Factor Analyses

  4. Descriptive Statistics and Correlation Analyses

  5. T-Test, Multi-Factor ANOVA, Simple-Effect Analysis, and Post-Hoc Multiple Comparison

  6. Tidy Report of Regression Models

  7. Mediation and Moderation Analyses

  8. Additional Toolbox for Statistics and Graphics

Function Output

For some functions, the results can be saved to Microsoft Word using the file argument.

bruceR Function Output: R Console Output: MS Word
print_table() √ (basic usage)
Corr() √ (suggested)
Alpha() (unnecessary)
EFA() / PCA()
PROCESS() √ (partial)
model_summary() √ (suggested)
HLM_ICC_rWG() (unnecessary)


## Correlation analysis (and descriptive statistics)
Corr(airquality, file="cor.doc")

## Regression analysis
lm1 = lm(Temp ~ Month + Day, data=airquality)
lm2 = lm(Temp ~ Month + Day + Wind + Solar.R, data=airquality)
model_summary(list(lm1, lm2), file="reg.doc")
model_summary(list(lm1, lm2), std=TRUE, file="reg_std.doc")

Learn More From Help Pages


## Overview

## See help pages of functions
## (use `?function` or `help(function)`)