This video series will cover these topics:
(a) What is a mixed effects model?
(b) Creating data that is suitable for a mixed effects model
(c) How to fit mixed effects models in R using lme4
(d) Diagnostic tests to check if regression assumptions are satisfied
(e) Remediation if assumptions are violated (robust standard errors, weighted regression)
EDIT--I've been slow in posting the other videos, so here is the draft R code. I think I was still doing final edits; please let me know in the comments if you find any errors:
https://docs.google.com/document/d/18vQ9DXPPYV-WSMKiVtUoG_5Sz0JudSC986meb0_g_rQ/
For more advanced treatment of mixed effects models and their assumptions, I REALLY recommend this series from Mikko Rönkkö. There's a ton of great explanations on his channel!
https://www.youtube.com/watch?v=dx8lZnoY8hU&list=PL6tc6IBlZmOVEofGo-Yz4MpdOp5K8yk_T&pp=iAQB