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I was recently told that it is not allowed to include static covariates in mixed effect models. I can believe that this could be true, however, when I have time series data, and season is a grouping factor, then the differences between the static covariates in the different seasons should be tested, or not?

If it is not allowed, how could the effect of the static covariates then be tested for? only with a repeated measures anova?

sorry for this confusing question.

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I have never heard that about mixed effect models, and have done many mixed effect models that had static covariates. – Peter Flom Aug 25 '11 at 10:27
There should be something written about that in "Applied longitudinal analysis", by Fitzmaurice, Laird and Ware, Wiley & Sons, 2004 in Chapter 12. I do not have book (yet) so I can´t look it up. – Jens Aug 25 '11 at 13:30
@Jens, if you consider hierarchical structure of a mixed effects models, than static covariates are more than in spirit of multilevel models. You may look in John Fox cran.r-project.org/doc/contrib/Fox-Companion/… for some additional details. – Dmitrij Celov Aug 25 '11 at 14:16
Thank you Dmitrij, I will check out that appendix and I just got the respective book itself. Let´s see...I will dig in a bit deeper for more examples. At least, in the appendix Fox uses static covariates as fixed effects already. – Jens Aug 28 '11 at 8:39

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