2 citations · 3 across the 9 of their papers we have counts for
28 papers · 1 filter
Regression-Based Proximal Reconciliation of Conflicting Trials with Unmeasured Effect Modifiers
Daniel A Xu, Eric J Tchetgen Tchetgen, Enrique F Schisterman +2
Randomized controlled trials with similar protocols may yield conflicting findings when the distribution of relevant effect modifiers differs across study populations. Yet no forma…
How should we select test-negative controls? A causal perspective in the era of multiplex respiratory testing
Christopher B. Boyer, Kendrick Qijun Li, Xu Shi +2
The test-negative design (TND) is widely used to estimate vaccine effectiveness (VE) for respiratory pathogens by comparing vaccination odds among test-positive cases versus test-n…
A General Exposure-Mapping-Agnostic Framework for Causal Inference under Interference
Yihui He, Eric J. Tchetgen Tchetgen
We develop a general framework for design-based causal inference under interference in cluster experiments conducted via two-stage randomization on a network of interconnected unit…
Structural Nested Mean Models Under Parallel Trends Assumptions
Zach Shahn, Oliver Dukes, Meghana Shamsunder +3
We link and extend two approaches to estimating time-varying treatment effects on repeated continuous outcomes--time-varying Difference in Differences (DiD; see Roth et al. (2023)…
Causal Inference with a Hidden Treatment
Ying Zhou, Eric Tchetgen Tchetgen
In many causal inference settings, the treatment of interest is not directly observed; instead, one or more error-prone proxy measurements are available, creating a fundamental ide…
Exploiting independence constraints for efficient estimation of bounds on causal effects in the presence of unmeasured confounding
Ting-Hsuan Chang, Caleb H. Miles, Ilya Shpitser +2
Causal graphs may inform covariate adjustment for estimating causal effects and improve estimation efficiency by exploiting the graphical structure. In many applications, however,…