Sam Pimentel: Design Sensitivity and Its Implications for Weighted Observational Studies

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Tuesday, May 13, 2025: Sam Pimentel (UC Berkeley)
Title: Design Sensitivity and Its Implications for Weighted Observational Studies
Discussant: Jacob Dorn (University of Pennsylvania)
Abstract: Sensitivity to unmeasured confounding is not typically a primary consideration in designing weighted treated-control comparisons in observational studies. We introduce a framework allowing researchers to optimize robustness to omitted variable bias at the design stage using a measure called design sensitivity. Design sensitivity, which describes the asymptotic power of a sensitivity analysis, allows transparent assessment of the impact of different weighted estimation strategies on sensitivity. We apply this general framework to two commonly-used sensitivity models, the marginal sensitivity model and the variance-based sensitivity model. By comparing design sensitivities, we interrogate how key features of weighted designs -- including definition of treatment, inclusion criteria, and handling of extreme weights -- impact robustness to unmeasured confounding, and how these impacts may differ for the two different sensitivity models. We illustrate the proposed framework on a study examining drivers of support for the 2016 Colombian peace agreement.