I have a very basic question on post-estimation for probit/logistic regression models (frequentist). The non-linear character of the link functions requires us to do post-estimation for a sensible interpretation of the coefficients. What is often suggested is to use predicted probabilities, marginal effects, and/or simulation-based methods.
I see the advantages of simulation methods as they allow us to include estimation uncertainty.
Are you aware of any reasons to prefer marginal effects over predicted probabilities or vice versa?