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stat.ME2026
Adaptive discovery of effect modification in matched observational studies
Yu Gui, Dylan S Small, Zhimei Ren
Understanding effect modification -- how treatment effects vary across subpopulations -- is practically important in observational studies, as it helps identify which subgroups are…
stat.ME2026
The Role of Measured Covariates in Assessing Sensitivity to Unmeasured Confounding
Abhinandan Dalal, Iris Horng, Yang Feng +1
Sensitivity analysis is widely used to assess the robustness of causal conclusions in observational studies, yet its interaction with the structure of measured covariates is often…
stat.ME2026
Optimal Sample Splitting for Observational Studies
Qishuo Yin, Dylan S. Small
In observational studies of treatment effects, estimates may be biased by unmeasured confounders, which can potentially affect the validity of the results. Understanding sensitivit…