WatsonWoo / Practical-Applications-in-R-for-Psychologists

Lesson files for Practical Applications in R for Psychologists.

Practical Applications in R for Psychologists

_{Last updated 2021-01-12.}

This Github repo contains all lesson files for Practical Applications in R for Psychologists. The goal is to impart students with the basic tools to process data, describe data (w/ summary statistics and plots), and the foundations of building, evaluating and comparing statistical models in R, focusing on linear regression modeling (using both frequentist and Bayesian approaches).

These topics were taught in the graduate-level course Advanced Research Methods for Psychologists (Psych Dep., Ben-Gurion University of the Negev, Fall semester, 2020), laying the foundation for the topic-focused courses (Spring semester):

• Hierarchical linear models (HLM).
• Analysis of Factorial Designs (ANOVA)
• Structural equation modelling (SEM)
• Machine Learning (ML).

Notes:

• This repo contains only materials relating to Practical Applications in R. Though statistics are naturally discussed in many lessons, the focus is generally on the application and not on the theory.
• Please note that some code does not work on purpose and without warning, to force students to learn to debug.

Setup

You will need:

1. A fresh installation of R (preferably version 4.0 or above).
2. RStudio IDE (optional, but recommended).
3. The following packages, listed by lesson:

Lesson	Packages
01 intro
02 data wrangling	haven, tidyverse, readxl, dplyr, parameters, summarytools, psych, DescTools, finalfit, Hmisc, mice
03 plotting	dplyr, ggplot2, tidyr
04 hypothesis testing and power	psych, effectsize, BayesFactor, pwr, ggplot2
05 regression 101	effectsize, parameters, performance, ggeffects, psychTools
06 categorical predictors and model comparison	dplyr, parameters, emmeans, ggeffects, BayesFactor, bayestestR, performance
07 moderation and curvilinear	dplyr, parameters, performance, emmeans, ggeffects, interactions, ggplot2
08 generalized linear models	parameters, performance, ggeffects, emmeans
09 assumption checks and violations	ggeffects, performance, ggResidpanel, parameters, permuco, insight
10 ANOVA	afex, emmeans, effectsize, tidyr, car, parameters
11 mediation	mediation

_{(Bold denotes the first lesson in which the package was used.)}

You can install all the packages used by running:

# in alphabetical order:

pkgs <- c(
  "afex", "BayesFactor", "bayestestR", "car", "DescTools", "dplyr",
  "effectsize", "emmeans", "finalfit", "ggeffects", "ggplot2",
  "ggResidpanel", "haven", "Hmisc", "insight", "interactions",
  "mediation", "mice", "parameters", "performance", "permuco",
  "psych", "psychTools", "pwr", "readxl", "summarytools", "tidyr", "tidyverse"
)

install.packages(pkgs, dependencies = TRUE)

Package Versions

The package versions used here:

• afex 0.28-0 (CRAN)
• BayesFactor 0.9.12-4.2 (CRAN)
• bayestestR 0.8.0.1 (Dev)
• car 3.0-10 (CRAN)
• DescTools 0.99.39 (CRAN)
• dplyr 1.0.2 (CRAN)
• effectsize 0.4.1.2 (Dev)
• emmeans 1.5.2-1 (CRAN)
• finalfit 1.0.2 (CRAN)
• ggeffects 1.0.1 (Dev)
• ggplot2 3.3.2 (CRAN)
• ggResidpanel 0.3.0 (CRAN)
• haven 2.3.1 (CRAN)
• Hmisc 4.4-2 (CRAN)
• insight 0.11.1.1 (Dev)
• interactions 1.1.3 (CRAN)
• mediation 4.5.0 (CRAN)
• mice 3.12.0 (CRAN)
• parameters 0.10.1.1 (Dev)
• performance 0.6.0 (CRAN)
• permuco 1.1.0 (CRAN)
• psych 2.0.9 (CRAN)
• psychTools 2.0.8 (CRAN)
• pwr 1.3-0 (CRAN)
• readxl 1.3.1 (CRAN)
• summarytools 0.9.6 (CRAN)
• tidyr 1.1.2 (CRAN)
• tidyverse 1.3.0 (CRAN)