G-computation

The g-formula identifies an interventional outcome distribution by averaging observed conditional outcome laws over the covariate distribution under suitable consistency, exchangeability, and positivity assumptions.

For treatment history ${\bar{A}}_t$, observed history $H_t$, and final potential outcome $Y(\bar{a})$, sequential exchangeability requiresat every treatment time. Together with consistency of potential outcomes and positivity in causal inference, it identifies longitudinal effects by G-computation.