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stat.ME2026
Improving Variance Estimation for Covariate Adjustment with Binary Outcomes
Kaitlyn Lee, Alex Ocampo, Courtney Schiffman +3
Covariate adjustment is a general method for improving precision when estimating treatment effects in randomized trials and is recommended by the FDA in its 2023 guidance when base…
stat.ME2024★ 1 cited
Bridging Binarization: Causal Inference with Dichotomized Continuous Exposures
Kaitlyn J. Lee, Alan Hubbard, Alejandro Schuler
The average treatment effect (ATE) is a common parameter estimated in causal inference literature, but it is only defined for binary exposures. Thus, despite concerns raised by som…