[ADMB Users] Over-dispersed Mixed Effects Model Syntax in R

[Dave Robichaud]

Hello admb'ers.

I am having trouble interpreting the help files for glmm.admb in R.

I had a perfectly good model in lmer:

mCO1 = lmer(CO ~ Treat*Week + (1|Loc), family=poisson, data=dtr)

But I now see that my data are overdispersed, so I do not think poisson 
is the appropriate family.  I looked extensively on the web, and I see 
that lmer will not accept family = quasipoisson or family = 
negative.binomial.  Thus, I am once again shopping around for an 
appropriate analysis.

Now, I have stumbled upon the glmmADMB package, which claims to be more 
robust than glmmPQL.  I like that nested models can be compared (e.g., 
anova(fit2,fit)), but can't figure out what "group" means, or how to 
write the syntax for my command.

Can you help??

I should describe my data in more detail.  I have the following columns:

Loc	Treat		Week	CO
1	Control		1	10
2	Control		1	12
3	Control		1	 0
4	Control		1	 5
5	Modified	1	10
6	Modified	1	6
7	Modified	1	7
8	Modified	1	8
9	Modified	1	9
10	Modified	1	10
11	Modified	1	11
12	Modified	1	12
13	Modified	1	13
...    (9 weeks of data omitted to save space)
1	Control		11	 9
2	Control		11	 8
3	Control		11	 3
4	Control		11	 6
5	Modified	11	 9
6	Modified	11	 6
7	Modified	11	 5
8	Modified	11	10
9	Modified	11	 2
10	Modified	11	 4
11	Modified	11	 6
12	Modified	11	 9
13	Modified	11	 2

 From this, you will see that I have 4 Control sites and 7 Modified 
sites that are measured each week.  All 13 locations have different 
names, and Location is a random variable.  Location is a random variable.

My main goal is to look for an effect of Treatment.  But if there is a 
significant Week x Treatment interaction, I would examine the effect of 
Habitat separately for each Week.

Hopefully, the above helps to clarify my situation.

Thanks very much

Dave