A semiparametric instrumental variable approach to optimal treatment regimes under endogeneity.

ABSTRACT: There is a fast-growing literature on estimating optimal treatment regimes based on randomized trials or observational studies under a key identifying condition of no unmeasured confounding. Because confounding by unmeasured factors cannot generally be ruled out with certainty in observational studies or randomized trials subject to noncompliance, we propose a general instrumental variable approach to learning optimal treatment regimes under endogeneity. Specifically, we establish identification of both value function E[YD(L)] for a given regime D and optimal regimes argmaxDE[YD(L)] with the aid of a binary instrumental variable, when no unmeasured confounding fails to hold. We also construct novel multiply robust classification-based estimators. Furthermore, we propose to identify and est

SUBMITTER: Cui Y 

PROVIDER: S-EPMC8118566 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature