Figure 2.

Given an observational dataset with patient features $X_i$, assigned treatments $T_i$ and factual outcomes $Y_i$ jointly sampled from the distribution ${\mathbb{P}}_{\theta }$, validation is needed (e.g. Alaa and van der Schaar 2019) to select the causal inference method, out of the large number available (e.g. Causal Forests (Athey and Imbens 2016), NSGP (Alaa and van der Schaar 2019), and GANITE (Yoon et al. 2018)) that will achieve the best estimate of the individualized treatment effects.