lme4/glmer convergence warnings
On 14-04-10 09:01 PM, Corey Sparks wrote:
Hello all, I?ve been seeing the aforementioned convergence errors for weeks in a course i?m teaching using lme4, so I decided to follow Ben?s advice on reporting the :
I?m fitting a binomial GLMM for small area estimation model building here: glmer(I(bmi>30)~povz+vachousz+baccz+blackz+hispanicz+factor(region)+(1|state)+(1|cofips), family="binomial", data=merged, weights=cntywt/mean(cntywt)) n=~240000, n_cofips=217, n_state=46 I get the warning: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, : Model failed to converge with max|grad| = 0.235915 (tol = 0.001) and the gradients: relgrad <- with(fit.1 at optinfo$derivs,solve(Hessian,gradient))
max(abs(relgrad))
[1] 0.0001631008
This is good (relative gradient is less than the 0.001 or 0.002 tolerance we would think to set as a default)
and when I use refit(), I get: fit.1<-refit(fit.1)
relgrad <- with(fit.1 at optinfo$derivs,solve(Hessian,gradient)) max(abs(relgrad))
[1] 2.369877e-06
This doesn't really matter so much (as long as we're getting below tolerance on the relative gradient, I don't care so much if we can decrease it still further by refitting).
For another model on a LMM, I get: fit.mix<-lmer(bmiz~agez+lths+coll+black+hispanic+other+(1|cofips), brfss_11) In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, : Model failed to converge with max|grad| = 0.00550412 (tol = 0.002) relgrad <- with(fit.mix at optinfo$derivs,solve(Hessian,gradient))
max(abs(relgrad))
[1] 8.099289e-08
ditto.
Hope this helps
Yes, this is encouraging (switching to relative gradients would clear everything up here)