I am taking a basic biostats class for an epidemiology masters and we were recently told that log-binomial GLM is what we should be using instead of logistic regression because the coefficients are interpretable in terms of probability ratios (risk/prevalence).
Now, what gets me is that this just seems like we are buying into a larger problem out of laziness: a logit model can still estimate probabilities so it should allow for extraction of the corresponding ratios via the right manipulations. On the other hand, choosing a log link amounts to admitting larger than one probabilities and that seems like it would be an issue. I understand that for small p results will be very similar but it seems unnecessary when an adequate method seems to exist already.
Surely there is something I am missing here?