Guides & Resources

D2MR Workflow & Course Guides

Guides and walk-throughs to get you through many of the gritty bits of D2MR.¹

Best Practices
- A collection of best practices for programming in R (for D2MR students)
Natalie’s Style Guide
- Just for reference of what a style guide might look like – you don’t have to use it!
Using RStudio with GitHub
- Simplified version of the complete guide from “R for the Rest of Us” below
Setting up RStudio
- Covers the RStudio settings you are most likely to want to tweak
Creating APA Manuscripts with Quarto

Resources

This list is updated regularly. Find a great resource that others might appreciate? Email Dr. Dowling to add to the list!

General

STAT545
- The course website for a similar (and much more comprehensive!) course originated at UBC by Jenny Bryan
R for Graduate Students
- A bookdown guide written by a PhD student with the grad student “true beginner” in mind

Documentation & References

Git & github

Git
How to Use Git/GitHub with R - Instructions for setting up your GitHub integration within RStudio, no GitHub Desktop required!
Git user manual - Look here if you want to use Git in the terminal or command line
Git cheat sheet
An introduction to Git and how to use it with RStudio
Happy Git and GitHub for the useR - A companion to STAT545 (see above)

R

R for Data Science, second edition by Hadley Wickham
Hands-On Programming with R by Garrett Grolemund
User-contributed cheatsheets
W3Schools R tutorial
Learn-R
Using R for psychological research - Personality Project

R Markdown

R Markdown for Scientists by Nicholas Tierney
R Markdown: The Definitive Guide by Yihui Xie, J. J. Allaire, and Garrett Grolemund
R Markdown cheatsheet

Quarto

Tidyverse and R Packages

ggplot2 and Visualization

Transitioning to R

Example datasets

Many/most datasets from these sources may be used for mini-projects in some capacity. Post a link in the Slack channel if you want to double check whether data you have in mind is a good fit.

Essentials

R
RStudio
GitHub
GitHub Desktop
- Not used in this class, but can be handy when RStudio’s Git pane is being finicky
R packages (install with the install.packages command)²
- tidyverse
  - Suite of packages for data manipulation and visualization, including ggplot2
- knitr
  - Dynamic report generation, necessary for Quarto/R markdown
- bibtex
  - Citation management in markdown
- DescTools
  - Tools for descriptive statistics
- Other useful packages:
  - papaja
    - Alternative to apaquarto for creating APA-style manuscripts
  - psych
    - Data analysis with psychologists’ common needs in mind
  - stats
    - Base R functions for statistical analysis, a nice complement to the psych package, but also has some conflicts with it, so be thoughtful the order you load them in
  - lme4
    - Fitting linear mixed-effects models
  - data.table
    - Fast data manipulation, not necessarily always the most cooperative with the tidyverse
  - ggpubr
    - Publication-ready plots
  - ggsci
    - Color palettes for ggplot2 based on journals, universities, and pop culture (my favorite is Futurama)
  - patchwork
    - Combine multiple ggplot2 plots into one
  - RColorBrewer
    - Color palettes for R
  - vcd
    - Visualizing categorical data

Footnotes

If you have stumbled upon this page without be a member of the class (hello!) you may or may not find these guides helpful, and you may even – very validly – disagree with how I present things. These guides are created specifically for the class From Data to Manuscript in R at the University of Chicago, which is a short, hands-on crash course with no prerequisites. They are by no means comprehensive, definitive, or universal.↩︎
If packages fail to install with the install.packages command, you can typically download them directly from the package’s GitHub page with remotes::install_github("crsh/papaja"). Replace crsh/papaja with whatever follows “github.com/”.↩︎