[R-sig-ME] Robust SEs in GLMMs

[Sharon Poessel]

When computing resource selection functions for animal telemetry data with
a binary response variable, where the 1s represent animal location data,
which are spatially and temporally correlated, and the 0s represent random
locations, which are not correlated, it is recommended to calculate robust,
or empirical, standard errors instead of using the model-based standard
errors to account for this differing correlation structure.  As far as I
can tell, none of the glmm packages in R calculate these robust SEs.  Does
anyone know of a way to use glmms that calculate these?  Thanks.

Sharon

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