Course Resources

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D2MR Workflow & Course Guides

Guides and walkthroughs to get you through many of the gritty bits of D2M-R.¹

• Best Practices
  • A collection of best practices for programming in R (for D2M-R 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
• Setting up RStudio
  • Covers the RStudio settings you are most likely to want to tweak
• GitHub Submissions
  • Guide to submitting assignments via GitHub repos and GitHub Classroom
• Git & GitHub Assessment
  • Guidelines and recommendations for meeting the Git & GitHub learning objective requirements
• Research Workflow Assessment
  • Guidelines and recommendations for meeting the RStudio+Quarto Workflow learning objective requirements
• Creating APA Manuscripts with Quarto
  • Guide to setting up an RProject/repo with the apaquarto extension
• BibTeX References with Zotero & citr
  • Guide to citing sources in markdown in a Quarto-compatible workflow
  • Includes instructions for Zotero, the Better BibTeX extension, and the citr addin

Essentials

Software and packages you’ll need for this course:

• Slack
• 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
      • This isn’t an “essential” anymore if you’ve converted to Quarto, but can be a full alternative if you prefer, and it does have some nice convenience functions
    • 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

1. If you have stumbled upon this page without being 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 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.

2. 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/”.