Learn R Programming

bruceR (version 0.8.5)

bruceR-package: bruceR: BRoadly Useful Convenient and Efficient R functions

Description

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

Install the latest development version by devtools::install_github("psychbruce/bruceR")

Check updates in Release Notes.

Report bugs in GitHub Issues.

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

[Data]:

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]:

emmeans: Estimates of marginal means and multiple contrasts.
effectsize: Estimates of effect sizes and standardized parameters.
performance: Estimates of regression models performance.
lmerTest: Tests of linear mixed effects models (LMM, also known as HLM and multilevel models).

[Plot]:

ggplot2: Data visualization.
ggtext: Markdown/HTML rich text format for ggplot2 (geoms and themes).
cowplot: Advanced toolbox for ggplot2 (arrange multiple plots and add labels).
see: Advanced toolbox for ggplot2 (geoms, scales, themes, and color palettes).

Arguments

Main Functions in <code>bruceR</code>

(1) Basic R Programming

set.wd (alias: set_wd)

import, export

cc

pkg_depend, pkg_install_suggested

formatF, formatN

Print, Glue, Run

%allin%, %anyin%, %nonein%, %partin%

(2) Multivariate Computation

SUM, MEAN, STD, MODE, COUNT, CONSEC

RECODE, RESCALE

(3) Reliability and Factor Analyses

EFA / PCA

(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

model_summary

lavaan_summary

(7) Mediation and Moderation Analyses

(8) Additional Toolbox for Statistics and Graphics

grand_mean_center

group_mean_center

granger_causality