Larry Han (Workshop in Applied Statistics)

This Week's Speaker

Larry Han (Northeastern), "Federated transfer learning for robust inference of causal effects"

Abstract

Federated or multi-site studies have distinct advantages over single-site studies, including increased generalizability, the ability to study underrepresented populations, and the opportunity to study rare exposures and outcomes. However, these studies are challenging due to the need to preserve the privacy of each individual's data and the heterogeneity in their covariate distributions. We propose a novel federated approach to derive valid causal inferences for a target population using multi-site data. We adjust for covariate shift and covariate mismatch between sites by developing multiply-robust and privacy-preserving nuisance function estimation. Our methodology incorporates transfer learning to estimate ensemble weights to combine information from source sites. We show that these learned weights are efficient and optimal under different scenarios. We showcase the finite sample advantages of our approach in terms of efficiency and robustness compared to existing approaches. Finally, we showcase the utility of our methodology for estimating COVID-19 vaccine efficacy (Moderna vs. Pfizer) across geographic regions, and variations in congenital heart surgery quality across racial/ethnic groups. Our findings have implications for the efficient allocation of scarce resources.

Paper 1: https://arxiv.org/abs/2112.09313
Paper 2: https://arxiv.org/abs/2203.00768

The Applied Statistics Workshop (Gov 3009) meets all academic year, Wednesdays, 12pm-1:30pm, in CGIS K354. This workshop is a forum for advanced graduate students, faculty, and visiting scholars to present and discuss methodological or empirical work in progress in an interdisciplinary setting. The workshop features a tour of Harvard's statistical innovations and applications with weekly stops in different fields and disciplines and includes occasional presentations by invited speakers.

More information is available at the Gov 3009 website: https://projects.iq.harvard.edu/applied.stats.workshop-gov3009

All interested Harvard affiliates are invited to attend.