[R-sig-ME] lme4/glmer convergence warnings

[W Robert Long]

I should perhaps also mention that of the 9 covariates, 3 are continous 
and I have tried standardising them. Of the remaining 6, 5 are binary 
and the last one is ordinal.

On 02/04/2014 11:28, W Robert Long wrote:
> Hi all
>
> I am running a simple random intercepts model using lme4 on
> approximately 70,000 observations, with 250 clusters. The code looks like
>
> glmer(Y~x1+x2+x3+x4+x5+x6+x7+x8+x9+(1|clusdID),
>      data=dt1, family=binomial(link=logit))
>
> and I receive the following warnings:
>
> Warning messages:
> 1: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
>    Model failed to converge with max|grad| = 4847.75 (tol = 0.001)
> 2: In if (resHess$code != 0) { :
>    the condition has length > 1 and only the first element will be used
> 3: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
>    Model is nearly unidentifiable: very large eigenvalue
>   - Rescale variables?;Model is nearly unidentifiable: large eigenvalue
> ratio
>   - Rescale variables?
>
> There are some small clusters (<10 obs per cluster), but even removing
> those, the warnings remain.
>
> Using Stata -xtmelogit- there are no warnings and the output is almost
> identical to glmer() so this gives me some comfort, yet I still worry
> about these warnings from glmer.
>
> I have tried setting nAGQ as high as 10, to no avail.
>
> Could anyone suggest what I can look for or change ? The data are
> confidential so I can't easily make a reprodicible example.
>
> Thanks in advance
> Robert Long
>
>
>