@@ -55,7 +55,7 @@ There is a rich literature on problems that arise in similar settings. %, and ou
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%One can approach the challenges from different viewpoints, selection bias, missing data, , offline policy evaluation, and latent confounding sensitivity, analysis .
% COUNTERFACTUALS: FUNDAMENTAL PROBLEM
At its core, our task is to answer a `what-if' question, asking ``what would the outcome have been if a different decision had been made'' (a counterfactual), this is often mentioned as the `fundamental problem' in causal inference~\cite{holland1986statistics,bookofwhy}.
At its core, our task is to answer a `what-if' question, asking ``what would the outcome have been if a different decision had been made'' (a counterfactual), this is often mentioned as the `fundamental problem' in causal inference~\cite{holland1986statistics,bookofwhy}.
% SELECTION BIAS
Settings where data samples are chosen through some intricate filtering mechanism are said to exhibit {\it selection bias} (see, for example, \cite{hernan2004structural}).
