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

Bruce H. W. S. 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.

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!

r
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() - 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() - HLMICCrWG() - regress()

• Mediation and Moderation Analyses

- PROCESS() (suggested) - med_summary() - lavaan_summary()

• Additional Toolbox for Statistics and Graphics

- grandmeancenter() - groupmeancenter() - 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() | √ | | | HLMICCrWG() | √ | (unnecessary) | | granger_test() | √ | √ | | granger_causality() | √ | √ |

Examples:

r
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")
modelsummary(list(lm1, lm2), std=TRUE, file="regstd.doc")

Learn More From Help Pages

r
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
...