I read in this paper An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies, that
"If the outcome is dichotomous (self-report of the presence or absence of depression), the effect of treatment can be estimated as the difference between the proportion of subjects experiencing the event in each of the two groups (treated vs. untreated) in the matched sample. With binary outcomes, the effect of treatment can also be described using the relative risk..."
It seems to me that the difference of the proportions of subjects experiencing the event under treatment and non-treatment refers to the estimator for the Average Treatment Effect on the Treated (ATT), instead of the Average Treatment Effect (ATE).
Is calculating the ATE impossible under a binary outcome?