Beyond reweighting: On the predictive role of covariate shift in effect generalization.

ABSTRACT: Many existing approaches to generalizing statistical inference amid distribution shift operate under the covariate shift assumption, which posits that the conditional distribution of unobserved variables given observable ones is invariant across populations. However, recent empirical investigations have demonstrated that adjusting for shifts in observed variables (covariate shift) is often insufficient for generalization. In other words, covariate shift does not typically "explain away" the distribution shift between populations. As such, addressing the unknown yet nonnegligible shift in the unobserved variables given observed ones (conditional shift) is crucial for generalizable inference. In this paper, we present empirical evidence from two large-scale multisite replication studies indi

SUBMITTER: Jin Y 

PROVIDER: S-EPMC12625858 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature