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.
However, there is no reason to cap the number of MC simulations at the sample size n
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ME 1years
2025 1verdicts
ACCEPT 1representative citing papers
citing papers explorer
-
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.