# A priori contrast for binomial GLM

after much reading I decided to write because I cannot find a solution to my question.

I already did a priori contrasts before for a continuous variable with normal distribution. Now I have another variable (burrow), which is binomial, and I can do the GLM for it. But when I do the a priori contrasts, it has no result in the cases where all data are 0 (is not that there are no data, they are just all 0 in a category (treat 30-30), and I want to compare this with others that have ones).

Data sructure is like this:

>head(burrow)

##day treat  sp  burrow

## 3   30-30 B      0
## 3   30-30 B      0
## 3   15-30 B      1
## 3   15-30 B      1
## 3   15-30 B      1
## 3   10-25 B      1


My model is this:

> model4B2<-glm(burrow~ treat, family=binomial(link="logit"), data=D4B)


And I did the contrast like this:

> require(multcomp)
> #Test contrasts 30 vs all (there are 4 categories to compare)
> k3010R1<-matrix(c(3,-1,-1,-1),1)
> t3010<-glht(model4B3.2,linfct=k3010R1)
> summary(t3010)


But is not working and I am sure it should work.

Could it be because my explanatory variable is cathegorical? Or is just not possible to do contrasts for binomial when you have all 0 in some cathegory?