Learning R for Researchers in Psychology

R is a powerful environment for statistical computing. Here is a selective list of resources on R with an emphasis on resources useful for researchers in psychology.

Psychology specific R resources

• R Notes for Experimental Psychology
• William Revelle’s Psychology R Site also see the package pscyh, and the online book and workshop resources
• Jonathan Baron and Yelin Li’s R for Psychology Experiments
• sem package: John Fox’s Page William Revelle’s resources; my post on SEM in R
• Mailing list for Psychology and R
• Edinburgh Psychology R-users
  
• Jason Locklin’s notes on standard experimental analyses in psychology

General Resources

• Quick-R: A fantastic resource to quickly check how to complete common analyses
• Dolph Schluter’s R Tips: Nice set of tips on R (particularly see “fit models” section)
• List of free online documentation on R
• R Reference Card: Lists many of the core commands in a compact way
• R in a few hours
• UCLA Short Courses on R: includes notes on moving from SPSS/Stata/SAS to R
• Michael Lavine: Introduction to Statistical Thought: Higher mathematical level; uses R to illustrate principles of probability, inference, modelling, etc.
• Delicious: Lists new R resources
• Cyclismo R Tutorial: Gives an introduction to basic statistics with R
• R Primer: A book introducing R and a little bit of statistics by Christopher Green
• Ecological Models and Data in R: Benjamin Bolker: An early draft of the book is available online. The book provides an introduction to model building for ecologists, but should also be relevant to researchers in psychology. It provides a fairly gentle introduction to statistical modelling.
• Shravan Vasishth and Michael Broe have an online book on simulations and statistics useful for social scientists.
• Dan Wright’s Psych 101 course with R, SPSS, and Excel
• SimpleR: A free online earlier version of what later went on to become a book. It introduces R and basic statistics.
• Ashworth R Resources: A course on R with Lecture notes, datasets, and tutorials. I particularly liked the material on the general linear model.
• R Tutorial
• R Clinic
• Data mining and R
• Blogs on R

Task Views
R includes many user contributed packages. In order to make these more accessible, many of them are listed under task views. The following Task Views are of particular relevance to researchers in pscyhology.

• Psychometric Models and Methods
• Social Sciences
• Multivariate

Books
R lists many of the increasing number books on R that are being released. Some of the books on R that I have enjoyed reading include the following:

• Software for Data Analysis (2008): John Chambers: This gives a sense of the philosophy and style of programming in R. It is an intermediate to advanced text.
• Data Manipulation with R: Phil Spector: This book is short, concise, and very clear. The examples are well chosen.
• Data Analysis and Graphics Using R – An Example-Based Approach: John Maindonald and John Braun: This provides a good introduction to R. It also covers many techniques useful in psychology introducing several interesting techniques that are not necessarily part of the standard psychology statistics curriculum.
• Books in the The Springer UseR Series tend be quite good.
• If you are coming from an SPSS or SAS background as is often the case in psychology, R for SAS and SPSS Users may make transferring your knowledge easier. There’s an early version of the book available for free online.

Getting Started

• Watch a video on what is R
• Download and install R
• The following Videos Part 1 and Part 2 provide a useful introduction. Here’s another video 
• Organise a user interface: My general advice: spend the first 10 to 20 hours using the basic R environment; then have a look at Tinn-R, JGR, and RCommander. If you decide you like it, I’d recommend using Eclipse with the StatET plug-in. See this tutorial for how to install and use. Here’s why I like it. New GUI options are changing all the time, so its worth keeping an eye out for new developments.