Dear all,

I apologise if this is an obvious question, but I haven't been able to find reference to it in the literature so far. I was wondering whether it is possible to include an offset variable in a binomial GLM/GLMM, as well as in poisson models?



For example, I surveyed for my study species during a set time period and collected presence-absence data. On some nights the camera traps failed, so the no. trap nights is reduced, which could then influence detection.

Hence I would like to include trap night as an offset.



However, if it is possible to include the trap nights as an offset in a binomial model with logit link function, is it alright to just include it as below:



model<- glm(pres ~ a*b + c, offset=trapnight, family=binomial, data=data)



Or would it need to be transformed as in Poisson models with a log link when included in the formula:

model<- glm(count ~ a*b + c + offset(log(trapnight), family=poisson, data=data)



In this case, would the transformation be "offset(logit(trapnight))" or "offset(invlogit(trapnight))"



Thank you for your help,

Leila

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