Here are some of our favourite resources for continuing to develop you R skills beyond the end of the workshop.

(Page still under development - more coming soon!!)

Data processing in R

  • DataCamp - interactive courses for programming in R (free introductory levels, ££ for more advanced)
  • CodeAcademy - interactive exercises for introductory R
  • Software Carpentry - similar-style materials to those we used in the course, but slightly more content, includes further information on writing your own functions and using R Markdown.
  • R for Data Science - textbook written by the author of the tidyverse himself, freely available online
  • Gorilla to Tidy Data - Emma’s tutorial for processing output files from the online experiment platform Gorilla

Cheat sheets

Cheat sheets are handy summaries of key tools. I used to print these and stick them by my desk for easy reference!

You’ll find cheatsheets for dplyr, tidyr, and ggplot2 here

Mixed effects models

Conceptual understanding

(Just because this deserved another plug!)

Tutorials

  • Bodo Winter’s tutorial - Parts 1 & 2
  • Violet Brown’s An approachable introduction to linear mixed effects modeling with implementation in R - pre-print
  • Singmann & Kellen (2019) - An introduction to mixed models for experimental psychology - pre-print of book chapter
  • Baayen, Davidson & Bates (2008) - Mixed-effects modeling with crossed random effects for subjects and items - paper published in the Journal of Memory and Language (Bates is one of the creators of the lme4 package)

Approaches

  • Meteyard & Davies (2020) - Best practice guidance for linear mixed-effects models in psychological science - paper published in the Journal of Memory and Language