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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.

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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.

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

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