[R-sig-ME] lme4, failure to converge with a range of optimisers, trust the fitted model anyway?

[Ken Beath]

On 5 April 2015 at 20:12, Hans Ekbrand <hans.ekbrand at gmail.com> wrote:

> On Sun, Apr 05, 2015 at 07:31:25PM +1000, Ken Beath wrote:
> > No, you need to treat this still as binomial data, using cbind(y,n-y) as
> > the response where y is the number of positives in each group, and n is
> the
> > total in each group.
>
> OK, I'll try that. What is the interpretion of the outcome in this
> case, is it still the logit of the probability of the outcome?
>
>
Yes.


> > I suggest reading one of the books that discusses
> > fitting logistic models in R, most advanced texts have a
> > section. Introductory Statistics with R by Peter Dalgaard has the section
> > available in Amazon.
>
> I actually already have that one, quite good.
>
> > You also still need a random effect for the cluster.
> >
> > While I'm thinking of it, should clusters and country random effects have
> > been crossed. Generally the sampling is setup so that clusters are nested
> > within countries which requires a different syntax.
>
> I'm sorry but I haven't been clear on this, but the clusters are
> nested within countries, so there are no crossed random effects to be
> found.
>
>
The  random effect then needs to be included as (1|country/clusterID)

-- 

*Ken Beath*
Lecturer
Statistics Department
MACQUARIE UNIVERSITY NSW 2109, Australia

Phone: +61 (0)2 9850 8516

Building E4A, room 526
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