[ADMB Users] Warning message: Convergence failed:log-likelihood of gradient=...

[W Robert Long]

Hi all

I am using glmmADMB to fit a zero-inflated negative binomial model with 
random slopes and random intercepts. The model formula is

zi1 <- glmmadmb(Y ~ time*X1 + time*X2 +
	(time | Subject), data=final, family="nbinom2", zeroInflation=TRUE)

There are 4 time points and 85 subjects.

The outcome has some missing values, approx 20% are missing. The model 
runs fine with complete case data.

I had originally wanted to do multiple imputation, but I have yet to 
find a way of multiply imputing zero-inflated data in the context of 
this kind of multilevel/hierarchical model. So, I have implemented a 
random hot-deck imputation, which /appears/ to have worked well, 
however, around 50% of the completed datasets return this warning from 
glmmADMB:

  Convergence failed:log-likelihood of gradient= -XX.XXX

and the parameter estimates are not as expected. Also, occasionally 
(5-10% of the time) it returns the error:

The function maximizer failed (couldn't find STD file)

The remaining imputed datasets don't cause any problem and the parameter 
estimates are within the ranges expected.

All the imputed values are plausible, as you would expect from a 
hot-deck imputation and so far I can't identify what is causing these 
warnings and errors.

I would be grateful for any hints or advice about how to proceed.

Thanks
Robert Long