glmer does not converge, how inaccurate is using nAGQ = 0?
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
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