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stat.ME2026
Exploiting independence constraints for efficient estimation of bounds on causal effects in the presence of unmeasured confounding
Ting-Hsuan Chang, Caleb H. Miles, Ilya Shpitser +2
Causal graphs may inform covariate adjustment for estimating causal effects and improve estimation efficiency by exploiting the graphical structure. In many applications, however,…
stat.ME2023
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…