Hello, I have a general question concerning GLMM conceptualization.  I
would like to model animal counts as a function of characteristics of the
sampling location and also characteristics of the site containing the
sampling locations, with a random effect of site because there are multiple
sampling locations per site.  However, the characteristics of the site are
not replicated, such that site ID has a 1-to-1 relationship with each site
characteristic.  If I add a random effect of site, how is the random effect
of site ID partitioned from the fixed effect of site characteristics?

While most examples I've seen of GLMM use characteristics of the site that
don't have a 1-to-1 relationship with site ID (either because there are
multiple sites for every value of the characteristics or because there are
multiple values of the characteristics for each site), I have also seen
examples (e.g. chapter 19 in Zuur et al. 2009) that DO have a 1-to-1
relationship between site ID and site characteristic.  So is it generally
acceptable to "confound" fixed and random effects?  And if so, I would like
to know, conceptually, how the model can partition effect between the
random-effect of site ID and the fixed-effects of site characteristics.

Thanks,
Philip Shirk

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