Sam Pimentel: Design Sensitivity and Its Implications for Weighted Observational Studies скачать в хорошем качестве

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

Subscribe to the channel to get notified when we release a new video. Like the video to tell YouTube that you want more content like this on your feed. See our website for future seminars: https://sites.google.com/view/ocis/home 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.