On this page you can find the slides (.pptx), sample data (.Rdata), and code (.txt) from a workshop on mixed-effects modeling in R that we held at UCL on 18-20 May 2016. I try to be a slide minimalist, so I can't guarantee that the slides will make much sense on their own, but anyway they're here for posterity and just in case they're useful to anyone.

1. Intro to the general linear model; contrast coding; interactions (slides, code)
2. Using random effects; significance testing for mixed models (slides, code)
3. Maximal random effects and dealing with convergence failures (slides, code)
4. Logistic and ordinal models; effect size; power analysis; transformations (slides, code)
5. Confidence intervals and plotting (slides, code)

Sample datasets:

• eegdata.RData: sample wide-format data (for reshaping to long-format)
• enrich.RData: sample eye-tracking data (for illustrating convergence failures)
• File_S2.RData: sample self-paced reading data
• implicitpriming.RData: sample implicit priming data (for working with polytomous predictors)
• individualdifferences.RData: sample self-paced reading data with individual difference measures

by Stephen Politzer-Ahles. Last modified on 2016-05-25.