You might want to rethink about getting model averaged coefficients.  That
is a bunch of nonsense if you have any multicollinearity among the
predictors.  Model averaged predictions might be useful.

Brian

Brian S. Cade, PhD

U. S. Geological Survey
Fort Collins Science Center
2150 Centre Ave., Bldg. C
Fort Collins, CO  80526-8818

email:  cadeb@usgs.gov <brian_cade@usgs.gov>
tel:  970 226-9326



On Fri, Dec 13, 2013 at 10:37 AM, Stephen Jane <coachman7777@yahoo.com>wrote:

> Hello,
>
> I am using a negative binomial distribution in glmmADMB to fit a mixed
> model and then using the MuMIn package to get model averaged coefficients.
> As far as I can tell, this approach gives no estimates for the variance of
> the random effects.  I have been taking these from the top model according
> to AIC.  Is there a preferred approach to getting these?
>
> I would be grateful for any insights.
>
> Stephen Jane
>
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