5 citations · 5 across the 5 of their papers we have counts for
5 papers
Structural mean models for instrumented difference-in-differences
Tat-Thang Vo, Ting Ye, Ashkan Ertefaie +5
In the standard difference-in-differences research design, the parallel trends assumption may be violated when the relationship between the exposure trend and the outcome trend is…
Robust Causal Inference of Drug-drug Interactions
Di Shu, Peisong Han, Sean Hennessy +1
There is growing interest in developing causal inference methods for multi-valued treatments with a focus on pairwise average treatment effects. Here we focus on a clinically impor…
Instrumented Difference-in-Differences
Ting Ye, Ashkan Ertefaie, James Flory +2
Unmeasured confounding is a key threat to reliable causal inference based on observational studies. Motivated from two powerful natural experiment devices, the instrumental variabl…
Technical Preprint: Rationale and Design of a Planned Observational Study to Evaluate the Impact of Hydrocodone Rescheduling on Opioid Prescribing After Surgery
Mark D. Neuman, Sean Hennessy, Dylan Small +6
In October 2014, the US Drug Enforcement Agency (DEA) reclassified hydrocodone from Schedule III to Schedule II of the Controlled Substances Act, resulting in a prohibition on refi…
Selection bias when using instrumental variable methods to compare two treatments but more than two treatments are available
Ashkan Ertefaie, Dylan Small, James H. Flory +1
Instrumental variable (IV) methods are widely used to adjust for the bias in estimating treatment effects caused by unmeasured confounders in observational studies. In this manuscr…