1. Mixed Models: Theory and Applications with R. You can find their book’s website at https://www.eugened.org/mixed-models, and the PDF version of the book can be found
https://www.isical.ac.in/~arnabc/linmod/demidenko.pdf. This book is written by Prof. Eugene Demidenko, who works at Dartmouth College in the Department of Biomedical Science. I think this book emphasizes the application a lot.
2. Generalized, Linear, and Mixed Models. You can find this book from the https://onlinelibrary.wiley.com/doi/book/10.1002/0471722073; This book is written by Prof. Shayle R. Searle (a leader in the field of linear and mixed models in statistics who worked at Cornell) and Prof. Charles E. McCulloch (a professor of Biostatistics at UCSF). This book emphasizes the theoretical part of the model.
3. I also found a
https://biol609.github.io/Readings/McNeish_Kelley_PsychMethods_2019.pdf that summarizes and compares Fixed and Mixed-effect models.
McNeish, D., & Kelley, K. (2018). Fixed effects models versus mixed effects models for clustered data: Reviewing the approaches, disentangling the differences, and making recommendations.
Psychological Methods, 24(1), 20–35.
https://doi.org/10.1037/met0000182
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