[R-sig-ME] Robust SEs in GLMMs

Sharon Poessel sharpoes at gmail.com
Tue Nov 25 18:55:56 CET 2014

Thanks Tim.  I've only briefly looked at that function, so I'll check it
out in more detail.


On Tue, Nov 25, 2014 at 10:19 AM, Tim Meehan <tmeeha at gmail.com> wrote:

> 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.
> Best,
> Tim
> 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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