Tag: treatment effect estimation

Researchers have introduced VFCI, a federated framework that trains causal inference models across institutions holding different features of the same ...

A new methodological study compares matching, weighting and stratification strategies for large-scale propensity score adjustment across four national healthcare databases, ...

Researchers have formally defined the five conditions under which comparing observed outcomes with model-predicted counterfactuals yields valid treatment effect estimates.

A large-scale empirical study shows that hyperparameter tuning, not the choice of algorithm, is the dominant factor in whether machine ...