Design

We give graphical criteria for state variables to be 'valid' in off-policy learning in a framework that generalizes dynamic treatment regimes (DTRs) and Markov decision processes (MDPs).

We provide a unified review of various confounder selection criteria in the literature and the assumptions behind them.