The paper derives d-separation conditions under which an experimental distribution can be recovered from selection-biased data, with or without external population distributions, and illustrates them on simulations.
had we set X to x′ in the unique background context u consistent with e, Y would (or would not) take valuey
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Recover Experimental Data with Selection Bias using Counterfactual Logic
The paper derives d-separation conditions under which an experimental distribution can be recovered from selection-biased data, with or without external population distributions, and illustrates them on simulations.