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stat.ME2026
Lost in Aggregation: The Causal Interpretation of the IV Estimand
Danielle Tsao, Krikamol Muandet, Frederick Eberhardt +1
Instrumental variable estimation has emerged as a standard approach to mitigating confounding bias in the social sciences and epidemiology, where conducting randomized experiments…
stat.ME2025
Data-Driven Adjustment for Multiple Treatments
Sara LaPlante, Sofia Triantafillou, Emilija Perković
Covariate adjustment is one method of causal effect identification in non-experimental settings. Prior research provides routes for finding appropriate adjustments sets, but much o…
stat.ME2023
Conditional Adjustment in a Markov Equivalence Class
Sara LaPlante, Emilija Perković
We consider the problem of identifying a conditional causal effect through covariate adjustment. We focus on the setting where the causal graph is known up to one of two types of g…