In the frame of a longitudinal data analysis I need to write an R-code about mixed models. I know that there are many different names (mixed models, mixed-effect models, random effects,...) and would need to get first an overview helping me to choose the right one (in collaboration with a statistician) and finally to write the code.
Has anyone a recommendation?
Kind regards
Anne-Marie
One book that is common is Mixed-Effects Models in S and S-PLUS, José Pinheiro and Douglas Bates. It's related to the nlme package in R. But I haven't read it myself.
The other common package in R is lme4. The vignettes for this package may be a place to start. ( https://cran.r-project.org/web/packages/lme4/index.html ) .
For a quick practical introductory overview of what can be done with random effects modelling see :
http://www.bristol.ac.uk/media-library/sites/cmm/migrated/documents/repeated-measures.pdf
For much more detail and links to the free Lemma online course (Module 15) see http://www.bristol.ac.uk/cmm/software/mlwin/mlwin-resources.html#multipleresp
For a readable book and lots of links on how to do it in different software:
https://www.pilesofvariance.com/
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