Proposes influence function projection exploiting graphical independence constraints for more efficient semiparametric estimation of bounds on average causal effects under sensitivity models for unmeasured confounding.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
stat.ME 1years
2026 1verdicts
UNVERDICTED 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Exploiting independence constraints for efficient estimation of bounds on causal effects in the presence of unmeasured confounding
Proposes influence function projection exploiting graphical independence constraints for more efficient semiparametric estimation of bounds on average causal effects under sensitivity models for unmeasured confounding.