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:

  • 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.


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


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.

  • $\begingroup$ Thank you Robert for the list :) $\endgroup$ Aug 6 at 8:33

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