Decision trees partition covariate space to detect positivity violations in causal inference, augmented by random forests to quantify violation robustness within each subspace.
The central role of the propensity score in observa- tional studies for causal effects
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ML 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
A discriminative approach for finding and characterizing positivity violations using decision trees
Decision trees partition covariate space to detect positivity violations in causal inference, augmented by random forests to quantify violation robustness within each subspace.