[R-sig-ME] Robust SEs in GLMMs

Tim Meehan tmeeha at gmail.com
Tue Nov 25 18:19:38 CET 2014

Hi Sharon,

Take a look at glmmPQL in the MASS package.  This function allows you to
model a binary response, with random effects, and temporally and spatially
correlated errors.  If you model the correlations, there is less of a need
for adjusting standard errors.


On Sun, Nov 23, 2014 at 2:04 PM, Sharon Poessel <sharpoes at gmail.com> wrote:

> 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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