6 citations · 25 across the 12 of their papers we have counts for
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stat.AP2024★ 1 cited
Difference-in-Differences for Health Policy and Practice: A Review of Modern Methods
Shuo Feng, Ishani Ganguli, Youjin Lee +3
Difference-in-differences (DiD) is the most popular observational causal inference method in health policy, employed to evaluate the real-world impact of policies and programs. To…
stat.ME2024★ 3 cited
A Causal Framework for Evaluating Drivers of Policy Effect Heterogeneity Using Difference-in-Differences
Gary Hettinger, Youjin Lee, Nandita Mitra
Policymakers and researchers often seek to understand how a policy differentially affects a population and the pathways driving this heterogeneity. For example, when studying an ex…
stat.ME2024★ 4 cited
Multiply Robust Difference-in-Differences Estimation of Causal Effect Curves for Continuous Exposures
Gary Hettinger, Youjin Lee, Nandita Mitra
Researchers commonly use difference-in-differences (DiD) designs to evaluate public policy interventions. While methods exist for estimating effects in the context of binary interv…