I was teaching assistant of this course when Jeff Gill taught it at Washington University in Saint Louis (School of Public Health). Then, I taught this course as a Postdoc at the University of Virginia and then twice at Michigan State University when I was an Assistant Professor (tenure-track).
Some of the material is from Gelman and Hill's excellent book on Hierarchical Modeling. Some of the code on the book and on Gelman's website needs some changing (partly because R and packages have change over time) for it to work. The key aspects of the code on the book works; it's usually bugs here and there. Some of the code was fixed by Jeff Gill and I took that and also did my own additions.
Lab 1: Linear and Generalized Linear Regression (G & H, Chapters 1 to 4)
Lab 2: Basics of Multilevel Modeling (G & H Chapter 12)
Lab 3: Group Level Predictors and Other Complexities (G & H Chapter 13)
Lab 4: Cross-Level Interactions & Visualization in Hierarchical Modeling
I developed this Lab; it uses MC simulations for visualization and shows how to calculate/graph marginal effects. I replicate a paper's analysis end-to-end and show problem points and better ways to provide evidence in support of the hypotheses.
Lab 5: Hierarchical Logit Modeling (G & H Chapter 14) and Multilevel Regression Post-Stratification
To be continued... I need to add more labs