The following course notes are from my survey course in Mixed-Effects Models for graduate students. The materials were created in R markdown to supplement the verbal lectures. The course is applied and for a deep review of the theory & equations seek elsewhere. Basically, the goal was to learn how to model, plot, table, and report the results in a paper.
Warnings: These notes are likely full of errors (statistical, code, or grammatical). Corrections & Comments are appreciated!
Materials I did not always cite the specific textbooks through the notes (references below), but papers will be cited where they are used. I have also used functions and data from the web and I give the links.
Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences.
Finch, W. H., Bolin, J. E., & Kelley, K. (2014). Multilevel modeling using R. Crc Press.
West, B., Welch, K., Galecki, A. & Gillespie, B. (2014). Linear mixed models: a practical guide using statistical software. Boca Raton, FL: CRC Press/Taylor and Francis Group.
How to download the materials:
You can download each of the lectures, by clicking the Code button at the top right of each lecture. These can be opened in Rstudio. You can find details on how to work these types of files here.
Each lecture has in-class assignment & homework component (all in R markdown files) which used simulated or real data sets about in-progress or published psychological studies. I have not included these because of some of the data sources, but I am happy to provide (most of) them to any instructor interested.