5 papers
Augmented Inverse Hybrid Weighting: Robust Inference under Deterministic and Random Distribution Shifts
Ying Jin, Dominik Rothenhäusler
Reweighting source samples to match a target covariate distribution is a standard response to distribution shift when generalizing evidence from one population to another. This str…
Robustness of Refugee-Matching Gains to Off-Policy Evaluation Choices
Kirk Bansak, Elisabeth Paulson, Dominik Rothenhäusler +3
Previous research has investigated the potential of refugee matching for boosting refugee outcomes, first considered by Bansak et al. (2018). This paper demonstrates the stability…
Distributionally robust and generalizable inference
Dominik Rothenhäusler, Peter Bühlmann
We discuss recently developed methods that quantify the stability and generalizability of statistical findings under distributional changes. In many practical problems, the data is…
Calibrated inference: statistical inference that accounts for both sampling uncertainty and distributional uncertainty
Yujin Jeong, Dominik Rothenhäusler
How can we draw trustworthy scientific conclusions? One criterion is that a study can be replicated by independent teams. While replication is critically important, it is arguably…
Causal inference in partially linear structural equation models
Dominik Rothenhäusler, Jan Ernest, Peter Bühlmann
We consider identifiability of partially linear additive structural equation models with Gaussian noise (PLSEMs) and estimation of distributionally equivalent models to a given PLS…