Thanks, Ben. And thanks for cc'ing to r-sig-me. I look forward to what
anyone else has to say. For now, I'll take your advice and make the
requisite assumptions, document them, fit the model, add the covariances,
and test against bootMer().

FYI, the reason why I am doing this is because I am doing an individual
based model, and calibrating the sampling distribution of some of the
parameters with the predictive distribution of those parameters based on a
generalized linear mixed effects model.

*Ben Hanowell, MA, PhC, Research Assistant*

*Northwest Center for Public Health Practice*
University of Washington School of Public Health

Phone: 206.221.4962
1107 NE 45th Street, Suite 400
Seattle, WA 98105

Website <http://www.nwcphp.org/> |
Facebook<https://www.facebook.com/nwcpublichealth>


On Thu, Sep 12, 2013 at 12:29 PM, Ben Bolker <bbolker@gmail.com> wrote:

> On 13-09-12 03:06 PM, Benjamin Chabot-Hanowell wrote:
> > BACKGROUND
> >
> > Hello, Dr. Bolker. In the R-Sig-ME discussion below, you describe
> > how to construct crude standard errors for predictions of GLMMS
> > from lmer and glmmadmb.
> >
> > https://stat.ethz.ch/pipermail/r-sig-mixed-models/2011q2/016356.html
> >
> >  You referenced the wiki below in stating that you could simply add
> > in the among-group variance to the fixed effects variance.
> >
> > http://glmm.wikidot.com/faq
> >
> > QUESTION
> >
> > Is this still the case for a model from a binomial family with a
> > logit link function?
> >
>
>   I prefer not to answer questions like this offline, so I'm cc'ing
> back to r-sig-mixed-models.
>
>   To the extent that we are willing to assume that the error structure
> on the logit scale is Normally distributed, and that we are not
> worried about ignoring the uncertainty in the random effects
> parameters (i.e. we are conditioning on the estimates of RE
> variance-covariance matrices), if you do this procedure on the link
> (logit) scale and inverse-link-transform the resulting confidence
> intervals, I would think you would get reasonable answers.
>
>   You might want to do a quick check against the results of bootMer() ...
>
>   As always, corrections/caveats welcome from the rest of the community.
>
>   Ben Bolker
>
>

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