3 papers
stat.ME2026
Federated Learning with Incomplete Data: When to Use Complete Cases and When to Weight
Jesus E. Vazquez, Yicheng Shen, Jason Akulian +4
Privacy constraints have driven the rise of federated learning (FL), which enables multi-site analyses without sharing individual participant data. Existing FL estimators largely a…
stat.ME2026
Self-separated and self-connected models for mediator and outcome missingness in mediation analysis
Trang Quynh Nguyen, Razieh Nabi, Fan Yang +2
Missing data is a common challenge in studying treatment effects. In the context of mediation analysis, this paper addresses missingness in the mediator and outcome, focusing on id…
stat.ME2025
Sensitivity Analysis when Generalizing Causal Effects from Multiple Studies to a Target Population: Motivation from the ECHO Program
Bolun Liu, Trang Quynh Nguyen, Elizabeth A. Stuart +22
Unobserved effect modifiers can induce bias when generalizing causal effect estimates to target populations. In this work, we extend a sensitivity analysis framework assessing the…