Detecting hidden confounding in observational data using multiple environments

27 May 2022

Papers citing "Detecting hidden confounding in observational data using multiple environments"

8 / 8 papers shown

Title
Big Data and the Computational Social Science of Entrepreneurship and Innovation Ningzi Li Shiyang Lai James Evans AILaw 19 0 0 13 May 2025
Falsification of Unconfoundedness by Testing Independence of Causal Mechanisms R. Karlsson Jesse H. Krijthe CML 47 0 0 10 Feb 2025
Detecting and Measuring Confounding Using Causal Mechanism Shifts Abbavaram Gowtham Reddy Vineeth N Balasubramanian CML 23 1 0 26 Sep 2024
Prediction-powered Generalization of Causal Inferences Ilker Demirel Ahmed M. Alaa Anthony Philippakis David Sontag OOD 29 2 0 05 Jun 2024
Do Finetti: On Causal Effects for Exchangeable Data Siyuan Guo Chi Zhang Karthika Mohan Ferenc Huszár Bernhard Schölkopf 16 2 0 29 May 2024
Benchmarking Observational Studies with Experimental Data under Right-Censoring Ilker Demirel E. Brouwer Zeshan Hussain Michael Oberst Anthony Philippakis David Sontag 36 4 0 23 Feb 2024
Hidden yet quantifiable: A lower bound for confounding strength using randomized trials Piersilvio De Bartolomeis Javier Abad Konstantin Donhauser Fanny Yang CML 25 7 0 06 Dec 2023
Combining Observational and Randomized Data for Estimating Heterogeneous Treatment Effects Tobias Hatt Jeroen Berrevoets Alicia Curth Stefan Feuerriegel M. Schaar CML 42 29 0 25 Feb 2022