Reference books for mixed model I am looking for reference to get a better understanding and overview of the mixed models. My goal is to understand the basic concepts and the formulas behind different models (I am having a hard time understanding the proc mixed output in SAS). Below are some points that I would like to know:

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*How to correctly construct the mixed model in different situations and objectives.

*Fully understand the results of the models (can reproduce the results manually).

*How to calculate the sample size for my studies.

Can you suggest good books (ideally in SAS)? Or maybe just help me get some orientation.
 A: The only book that I'm familiar with that's specific for SAS is:
Stroup, W.W., Milliken, G.A., Claassen, E.A. and Wolfinger, R.D., 2018. SAS for mixed models: introduction and basic applications. SAS Institute.
This is a very good, albeit brief, online guide from UCLA
REPEATED MEASURES ANALYSIS USING SAS
A general mixed model theory and practice, and for other software, I can highly recommend the following books:
Demidenko, E., 2013. Mixed models: theory and applications with R. John Wiley & Sons.
Jiang, J. and Nguyen, T., 2021. Linear and generalized linear mixed models and their applications. Springer Nature.
McCulloch, C.E. and Searle, S.R., 2004. Generalized, linear, and mixed models. John Wiley & Sons.
Pinheiro, J. and Bates, D., 2006. Mixed-effects models in S and S-PLUS. Springer Science & Business Media.
Rabe-Hesketh, S. and Skrondal, A., 2008. Multilevel and longitudinal modeling using Stata. STATA press.
Raudenbush, S.W. and Bryk, A.S., 2002. Hierarchical linear models: Applications and data analysis methods. sage.
Snijders, T.A. and Bosker, R.J., 2011. Multilevel analysis: An introduction to basic and advanced multilevel modeling. sage.
Twisk, J.W., 2019. Applied mixed model analysis: a practical guide. Cambridge University Press.
