Covariate-assisted bounds on causal effects with instrumental variables.

ABSTRACT: When an exposure of interest is confounded by unmeasured factors, an instrumental variable (IV) can be used to identify and estimate certain causal contrasts. Identification of the marginal average treatment effect (ATE) from IVs relies on strong untestable structural assumptions. When one is unwilling to assert such structure, IVs can nonetheless be used to construct bounds on the ATE. Famously, Alexander Balke and Judea Pearl proved tight bounds on the ATE for a binary outcome, in a randomized trial with noncompliance and no covariate information. We demonstrate how these bounds remain useful in observational settings with baseline confounders of the IV, as well as randomized trials with measured baseline covariates. The resulting bounds on the ATE are nonsmooth functionals, and thus sta

SUBMITTER: Levis AW 

PROVIDER: S-EPMC12602419 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature