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Separation occurs when some classes of a categorical outcome can be perfectly distinguished by a linear combination of other variables.
15
votes
Binomial glmm with a categorical variable with full successes
This phenomenon is called complete separation. You can find quite a lot (now that you know its name) Googling around ... … for "bglmer 'complete separation'" finds:
Quiñones, A. …
4
votes
GLMM for count data using square root link in lme4
It looks very much like you have a case of complete separation:
there is only one landform (ridge) that has seedlings, while other had no seedlings at al
large estimates ($|\hat \beta|>10$), and … You can read more about complete separation elsewhere; it is more typically discussed in the context of logistic regression (in part because logistic regression is more widely used than count regression …
9
votes
How to deal with quasi-complete separation in a logistic GLMM?
In particular, the blme package for R (which is a thin wrapper around the lme4 package) does this, if you specify priors for the fixed effects as in the example here (search for "complete separation"): …