Bayesian causal computation for sample estimands requires joint posterior sampling of cross-world counterfactuals while many population estimands need only parameter posteriors, and common procedures can silently target the wrong one.
It departs from the procedure described in Section A.2 in two important ways
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Untangling Sample and Population Level Estimands in Bayesian Causal Computation
Bayesian causal computation for sample estimands requires joint posterior sampling of cross-world counterfactuals while many population estimands need only parameter posteriors, and common procedures can silently target the wrong one.