A unified causal framework derives the efficient influence function for the DOOR probability and finds that cross-validated TMLE with Super Learner performs best in simulations.
The International Journal of Biostatistics , year =
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ML 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
A Unified Causal Inference Framework for the Desirability of Outcome Ranking Paradigm in Benefit-Risk Evaluation
A unified causal framework derives the efficient influence function for the DOOR probability and finds that cross-validated TMLE with Super Learner performs best in simulations.