Broadly Useful Convenient and Efficient R Functions • bruceR

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

This package includes easy-to-use functions for:

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);
Multivariate computation (e.g., compute scale sums/means/… with reverse scoring);
Reliability analyses and factor analyses (PCA, EFA, CFA);
Descriptive statistics and correlation analyses;
t-test, multi-factor analysis of variance (ANOVA), simple-effect analysis, and post-hoc multiple comparison;
Tidy report of statistical models (to R Console and Microsoft Word);
Mediation and moderation analyses (PROCESS);
Additional toolbox for statistics and graphics.

Author

Han-Wu-Shuang (Bruce) Bao 包寒吴霜

📬 baohws@foxmail.com

📋 psychbruce.github.io

Citation

Bao, H.-W.-S. (2021). bruceR: Broadly useful convenient and efficient R functions. https://CRAN.R-project.org/package=bruceR
- Note: This is the original citation. Please refer to the information when you library(bruceR) for the APA-7 format of the version you installed.

User Guide

NEWS (Changelog)

Chinese Documentation for bruceR: I. Overview

Chinese Documentation for bruceR: II. FAQ

Installation

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
install.packages("devtools")
devtools::install_github("psychbruce/bruceR", dep=TRUE, force=TRUE)

Tips:

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`

Basic R Programming
- cc() (suggested)
- set.wd() (alias: set_wd()) (suggested)
- import(), export() (suggested)
- pkg_depend(), pkg_install_suggested()
- formatF(), formatN()
- print_table()
- Print(), Glue(), Run()
- %^%
- %notin%
- %allin%, %anyin%, %nonein%, %partin%
Multivariate Computation
- add(), added() (suggested)
- .sum(), .mean() (suggested)
- SUM(), MEAN(), STD(), MODE(), COUNT(), CONSEC()
- RECODE(), RESCALE()
- LOOKUP()
Reliability and Factor Analyses
- Alpha()
- EFA() / PCA()
- CFA()
Descriptive Statistics and Correlation Analyses
- Describe()
- Freq()
- Corr()
- cor_diff()
- cor_multilevel()
T-Test, Multi-Factor ANOVA, Simple-Effect Analysis, and Post-Hoc Multiple Comparison
- TTEST()
- MANOVA()
- EMMEANS()
Tidy Report of Regression Models
- model_summary() (suggested)
- lavaan_summary()
- GLM_summary()
- HLM_summary()
- HLM_ICC_rWG()
- regress()
Mediation and Moderation Analyses
- PROCESS() (suggested)
- med_summary()
Additional Toolbox for Statistics and Graphics
- grand_mean_center()
- group_mean_center()
- ccf_plot()
- granger_test()
- granger_causality()
- theme_bruce()
- show_colors()

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)
`Describe()`	√	√
`Freq()`	√	√
`Corr()`	√	√ (suggested)
`Alpha()`	√	(unnecessary)
`EFA()` / `PCA()`	√	√
`CFA()`	√	√
`TTEST()`	√	√
`MANOVA()`	√	√
`EMMEANS()`	√	√
`PROCESS()`	√	√ (partial)
`model_summary()`	√	√ (suggested)
`med_summary()`	√	√
`lavaan_summary()`	√	√
`GLM_summary()`	√
`HLM_summary()`	√
`HLM_ICC_rWG()`	√	(unnecessary)
`granger_test()`	√	√
`granger_causality()`	√	√

Examples:

## 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

library(bruceR)

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

## See help pages of functions
## (use `?function` or `help(function)`)
?cc
?add
?.mean
?set.wd
?import
?export
?Describe
?Freq
?Corr
?Alpha
?MEAN
?RECODE
?TTEST
?MANOVA
?EMMEANS
?PROCESS
?model_summary
?lavaan_summary
?GLM_summary
?HLM_summary
...

bruceR