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math.ST2025
Selecting valid adjustment sets with uncertain causal graphs
Zhongyi Hu, Stéphanie van der Pas
Precise knowledge of causal directed acyclic graphs (DAGs) is assumed for standard approaches towards valid adjustment set selection for unbiased estimation, but in practice, the D…
math.ST2025
Finite sample-optimal adjustment sets in linear Gaussian causal models
Nadja Rutsch, Sara Magliacane, Stéphanie van der Pas
Traditional covariate selection methods for causal inference focus on achieving unbiasedness and asymptotic efficiency. In many practical scenarios, researchers must estimate causa…