3 citations · 8 across the 17 of their papers we have counts for
4 papers · 1 filter
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…
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)…
Using negative controls to identify causal effects with invalid instrumental variables
Oliver Dukes, David B. Richardson, Zachary Shahn +2
Many proposals for the identification of causal effects require an instrumental variable that satisfies strong, untestable unconfoundedness and exclusion restriction assumptions. I…