Why se.fit differ in predict.glm and predict.glmmadmb?

Dear list,

I am running a GLM (family="binomial") without random effects using both 
glm and glmmadmb.

Summaries are almost identical, however when I used the predict function 
as follows:

predict(glm1,newdatos1,type="link",se.fit =T)

predict(admb1,newdatos1,type="link",se.fit =T)

I realized that se.fit differ a lot between them, admb se.fit resulted 
much much higher (fit is almost identical). This is just and example of 
what I found:

glm1$se.fit	admb1$se.fit
0.04290869	0.2676562
0.04435600	0.2733130
0.04095631	0.2728592
0.03402992	0.2718389
0.03000669	0.2713617
0.03633637	0.2722059

Maybe I'm missing something or I am making a big mistake. Any help with 
this?


Many thanks,

Alexandre Alonso


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