A semiparametric data fusion framework restores identification of mediation effects from separately observed mediator and outcome data using shared IVs under unmeasured confounding and no-interaction plus latent alignment conditions.
arXiv preprint arXiv:2510.20404 , year=
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
-
Semiparametric Mediation Analysis with Separately Observed Mediator and Outcome under Unmeasured Confounding
A semiparametric data fusion framework restores identification of mediation effects from separately observed mediator and outcome data using shared IVs under unmeasured confounding and no-interaction plus latent alignment conditions.