2 citations · 4 across the 4 of their papers we have counts for
4 papers
Efficient estimation of weighted cumulative treatment effects by double/debiased machine learning
Shenbo Xu, Bang Zheng, Bowen Su +5
In empirical studies with time-to-event outcomes, investigators often leverage observational data to conduct causal inference on the effect of exposure when randomized controlled t…
Bias Formulas for Violations of Proximal Identification Assumptions
Raluca Cobzaru, Roy Welsch, Stan Finkelstein +2
Causal inference from observational data often rests on the unverifiable assumption of no unmeasured confounding. Recently, Tchetgen Tchetgen and colleagues have introduced proxima…
When Do Outcome Driven Treatments Break Parallel Trends?
Zach Shahn
Under what circumstances is it a threat to the parallel trends assumption required for Difference in Differences (DiD) studies if treatment decisions are based on past values of th…
A Note on Estimating Optimal Dynamic Treatment Strategies Under Resource Constraints Using Dynamic Marginal Structural Models
Ellen C Caniglia, Eleanor J Murray, Miguel A Hernan +1
Existing strategies for determining the optimal treatment or monitoring strategy typically assume unlimited access to resources. However, when a health system has resource constrai…