This resource has been updated - find the current version here: https://qubeshub.org/qubesresources/publications/833

This tutorial serves as a quick boot camp to jump-start your own analyses with linear mixed effects models. This text is different from other introductions by being decidedly conceptual; I will focus on why you want to use mixed models and how you should use them. While many introductions to this topic can be very daunting to readers who lack the appropriate statistical background, this text is going to be a softer kind of introduction... so, don’t panic!

The tutorial requires R – so if you haven’t installed it yet, go and get it! I also recommend reading tutorial 1 in this series before you go further.

Researchers should cite this work as follows:

• Winter, B. (2013). Linear models and linear mixed effects models in R with linguistic applications. arXiv:1308.5499. [http://arxiv.org/pdf/1308.5499.pdf]

1. data analysis
2. fixed effects
3. linear models
4. mixed models
5. R
6. random effects
7. regression
8. Resources @ QUBES - Teaching & Reference
9. statistics
10. Tutorial