3 papers
stat.ME2024
A causal inference framework for spatial confounding
Brian Gilbert, Abhirup Datta, Joan A. Casey +1
Over the past few decades, addressing "spatial confounding" has become a major topic in spatial statistics. However, the literature has provided conflicting definitions, and many p…
stat.ME2024
Consistency of common spatial estimators under spatial confounding
Brian Gilbert, Elizabeth L. Ogburn, Abhirup Datta
This paper addresses the asymptotic performance of popular spatial regression estimators of the linear effect of an exposure on an outcome under ``spatial confounding" -- the prese…
stat.ME2024
Augmented balancing weights as linear regression
David Bruns-Smith, Oliver Dukes, Avi Feller +1
We provide a novel characterization of augmented balancing weights, also known as automatic debiased machine learning (AutoDML). These popular doubly robust or de-biased machine le…