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bruceR (version 0.8.8)

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

Description

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

Package homepage: https://psychbruce.github.io/bruceR/

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

Report bugs at GitHub Issues.

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_table

Print, Glue, Run

%^%

%notin%

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

(2) Multivariate Computation

add, added

.sum, .mean

SUM, MEAN, STD, MODE, COUNT, CONSEC

RECODE, RESCALE

LOOKUP

(3) Reliability and Factor Analyses

Alpha

EFA / PCA

CFA

(4) Descriptive Statistics and Correlation Analyses

Describe

Freq

Corr

cor_diff

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

TTEST

MANOVA

EMMEANS

(6) Tidy Report of Regression Models

model_summary

lavaan_summary

GLM_summary

HLM_summary

HLM_ICC_rWG

regress

(7) Mediation and Moderation Analyses

PROCESS

med_summary

(8) Additional Toolbox for Statistics and Graphics

grand_mean_center

group_mean_center

ccf_plot

granger_test

granger_causality

theme_bruce

show_colors

Details

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).