A nonparametrically efficient estimator for network quantile causal effects under partial interference achieves parametric convergence rates via three-way cross-fitting and flexible nuisance estimation.
(2023), Doubly robust estimation of direct and indirect quantile treatment effects with machine learning, arXiv preprint arXiv:2307.01049\/
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ME 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Nonparametric efficient inference for network quantile causal effects under partial interference
A nonparametrically efficient estimator for network quantile causal effects under partial interference achieves parametric convergence rates via three-way cross-fitting and flexible nuisance estimation.