Mixed-effect models, or multilevel models, refer to a class of statistical models used to analyze correlated data. By “correlated” we mean data that is not independent. Such data include repeated measurements on the same subjects, or subjects observed in clusters, such as students in classrooms or plants in different plots. In this workshop we introduce the basics of linear mixed-effect modeling with an emphasis on implementation and interpretation. Examples will be given in R using the lme4 package. Previous experience with R and linear regression will be helpful but not required.

Our policy is that we do not record live workshops in order to encourage robust Q&A. However, you can always find the full workshop materials for all of our workshops at: https://library.virginia.edu/data/training/past-workshops which allows you to work through the material at your own pace. We also encourage you to reach out to the instructor at any time for a one-on-one consult, and for specific or general questions about any of the topics we cover.