[R-sig-ME] Number of Iterations lme4

[Jakob Gährken]

Hello,
I was asked to forward my question to this mailing list. I would be glad 
to get some hints regarding my questions below:

I am an quit inexperienced R user but I try hard to learn fast. My 
problem is that while I try to run lme4 with the model:
model1 = glmer(Survival ~ Kohorte+KJ+Saison+KAE+(1|ID), family = 
binomial(link = "logit"), 
data=phenos,control=glmerControl(optimizer="bobyqa",optCtrl=list(maxfun=1e6)))
I always get the warning :

1:In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
    Model failed to converge with max|grad| = 0.75662 (tol = 0.001, component 2)
2:In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
    Model failed to converge: degenerate  Hessian with 1 negative eigenvalues

I know that my data has the promblem that the binary response variable has a skewed distribution (1.933 "0" vs. 68.031 "1"). And that this could be the reason for the converging problem and that I might look for alternatives.(btw. do you consider some kind of minimum proportion for the "minor observation" in this case "0" (2.8%) when you fit a model e.g. for diseases with low incidence)
But beside of the reason for the converging problem I am wondering because I tried to change the number of iterations using  : control=glmerControl(optCtrl=list(maxfun=...)).The used time which leads to the error message and also the  ...with max|grad| = 0.75662...are  always the same - no matter what value for maxfun I choose. So I am not sure how to control the number of iterations that are really done by R and whether the amount changes with different defined maxfun values in my case.

Thank you for your time and looking forward hearing from you,

Jakob Gährken



	[[alternative HTML version deleted]]