[R-sig-ME] comparison between glmm.admb and lme4

[Brian Burke]

Hi all,
I have a situation where I will be using glmm.admb for some analyses 
(e.g., when I need a negative binomial distribution or zero inflation) 
and lme4 for others (e.g., when I have crossed random effects).  I would 
like to be able to compare the log likelihoods for all of the results, 
regardless of the package I use.  I decided to run a model from each 
package on the same data set, to see if they resulted in the same (or at 
least similar) log likelihoods.  The data are catch of salmon in over 
1100 trawls, many of which are zeros.  Results are below.  Both models 
result in parameter estimates that seem reasonable (and they are 
similar, but not identical, to each other).  Did the glmer really fit 
that much better or are the log likelihoods not technically comparable?

# Compare  glmm.admb and lme4
pois.admb <- glmm.admb(count ~ temp + I(temp^2) + depth + secchi + chl + 
month + year, random=~1, group="site", data=stations, family="poisson")

pois.glmer <- glmer(count ~ temp + I(temp^2) + depth + secchi + chl + 
month + year + (1|site), data=stations, family="poisson", REML=F) # I 
get the same nll whether I put in the REML statement or not


# Results in:
 > logLik(pois.admb)
'log Lik.' -2550.45 (df=NULL)
 > logLik(pois.glmer)
'log Lik.' -2474.079 (df=20)

Thanks!!
-Brian