glmmADMB

Dear list members,

I?m a PhD student in trouble. I?m running a mix effects model with a
dependent variable (PA: presence/absence, 0/1), one fixed explanatory and
continuous variable (AL: altitude), one fixed factor (PE: initially 16
levels, but reduced to 4 to reduce complexity) and one random term (2421
sites). Basically, the structure of a logistic regression but with a random
term to prevent temporal pseudoreplication.

model1<-glmmadmb(PA~PE+AL+(1|site), family="binomial")

My data are quite unbalanced becouse I?ve many more zeros than ones. I?ve
tried making a random selection of absences but I get similar problems than
when using the whole dataset.

I?m getting an output of results in R, but also getting a warning of lack
of convergence, such as:

Convergence failed:log-likelihood of gradient= -0.0195034


Can I trust my results in spite of the warning?

What other alternatives do you suggest?


I?ve tried with the classical lmer and glmer, and I also get convergence
problems as expected.

I?ve also tried with the MCMCglmm package, but I?ve problems with the
specification of the priors.


Any help is welcomed.


Silvia