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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. …
Ben Bolker's user avatar
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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 …
Ben Bolker's user avatar
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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"): …
Ben Bolker's user avatar
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