Michael Clark: Mixed Models with R tutorial: https://m-clark.github.io/mixed-models-with-R/
Tristan Mahr: Shrinkage in Mixed Models Blogpost: https://www.tjmahr.com/plotting-partial-pooling-in-mixed-effects-models/
A really lovely visualisation by Michael Freeman: http://mfviz.com/hierarchical-models/
Some handy datasets if you want some data to play with: https://multilevel-analysis.sites.uu.nl/datasets/
Lisa DeBruine created the excellent faux package which you can use to simulate some mixed factorial design data. You can find a tutorial here: https://debruine.github.io/faux/articles/sim_mixed.html
Hoffman, L., & Walters, R. W. (in press). Catching up on multilevel modeling. Forthcoming in Annual Review of Psychology (73).
Meteyard, L., & Davies, R. A. (2020). Best practice guidance for linear mixed-effects models in psychological science. Journal of Memory and Language, 112, 104092.
McNeish D, Stapleton LM, Silverman RD. On the unnecessary ubiquity of hierarchical linear modeling. Psychol Methods. 2017 Mar;22(1):114-140. doi: 10.1037/met0000078. Epub 2016 May 5. PMID: 27149401.
Sander Greenland, Principles of multilevel modelling, International Journal of Epidemiology, Volume 29, Issue 1, April 2000, Pages 158–167, https://doi.org/10.1093/ije/29.1.158
Bell, A., Fairbrother, M. & Jones, K. Fixed and random effects models: making an informed choice. Qual Quant 53, 1051–1074 (2019). https://doi.org/10.1007/s11135-018-0802-x
Bell, A., Jones, K. & Fairbrother, M. Understanding and misunderstanding group mean centering: a commentary on Kelley et al.’s dangerous practice. Qual Quant 52, 2031–2036 (2018). https://doi.org/10.1007/s11135-017-0593-5