[R-sig-ME] glmer does not converge, how inaccurate is using nAGQ = 0?

[Paolo Fraccaro]

Hi,

thanks for your suggestions. I left it going overnight still with nAGQ=1
and this time I got this warnings:

Warning messages:
1: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
  Model failed to converge with max|grad| = 0.00191069 (tol = 0.001,
component 4)
2: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
  Model is nearly unidentifiable: very large eigenvalue
 - Rescale variables?

Is the solution of increasing nAGQ still the best thing to do?

Many thanks,

Paolo

On 1 April 2015 at 23:06, Ken Beath <ken.beath at mq.edu.au> wrote:

> You could use a value of nAGQ that is higher, start with 5 and work up.
>
> How good the approximation is, depends. If you are having convergence
> problems it probably isn't.
>
> On 2 April 2015 at 01:23, Paolo Fraccaro <paolo.f.genova at gmail.com> wrote:
>
>> Hi
>>
>> I have a dataset of ~200k piece of hardware tested yearly for 10 years or
>> until failure (~15k). Therefore, the overall dataset size is ~2,000k. I'm
>> trying to fit a mixed effects logistic model with glmer, but the model
>> does not converge with the default settings. I tried to increase the
>> number of max iterations allowed (from 20 to 100) but still it does not
>> converge. I then set the nAGQ = 0 and obtained the less accurate estimate
>> of the model.
>>
>> My questions would be:
>> Do you have any idea of what parameters I could modify to try to make the
>> model converge?
>> How inaccurate is using nAGQ = 0?
>>
>> Many thanks.
>>
>> Paolo
>>
>> _______________________________________________
>> R-sig-mixed-models at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>
>
>
>
> --
>
> *Ken Beath*
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> Statistics Department
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