5.5k citations · 6.2k across the 34 of their papers we have counts for
7 papers · 2 filters
Identifying Optimal Methods for Addressing Confounding Bias When Estimating the Effects of State-Level Policies
Beth Ann Griffin, Megan S. Schuler, Elizabeth M. Stone +6
Background: Policy evaluation studies that assess how state-level policies affect health-related outcomes are foundational to health and social policy research. The relative abilit…
A Causal Roadmap for Generating High-Quality Real-World Evidence
Lauren E Dang, Susan Gruber, Hana Lee +23
Increasing emphasis on the use of real-world evidence (RWE) to support clinical policy and regulatory decision-making has led to a proliferation of guidance, advice, and frameworks…
Improving efficiency in transporting average treatment effects
Kara E. Rudolph, Nicholas T. Williams, Elizabeth A. Stuart +1
We develop flexible, semiparametric estimators of the average treatment effect (ATE) transported to a new population ("target population") that offer potential efficiency gains. Tr…
Methods for Integrating Trials and Non-Experimental Data to Examine Treatment Effect Heterogeneity
Carly Lupton Brantner, Ting-Hsuan Chang, Trang Quynh Nguyen +3
Estimating treatment effects conditional on observed covariates can improve the ability to tailor treatments to particular individuals. Doing so effectively requires dealing with p…
Comparison of Methods that Combine Multiple Randomized Trials to Estimate Heterogeneous Treatment Effects
Carly Lupton Brantner, Trang Quynh Nguyen, Tengjie Tang +3
Individualized treatment decisions can improve health outcomes, but using data to make these decisions in a reliable, precise, and generalizable way is challenging with a single da…
Sensitivity analysis for principal ignorability violation in estimating complier and noncomplier average causal effects
Trang Quynh Nguyen, Elizabeth A. Stuart, Daniel O. Scharfstein +1
An important strategy for identifying principal causal effects, which are often used in settings with noncompliance, is to invoke the principal ignorability (PI) assumption. As PI…