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

[W Robert Long]

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