A general instrumental variable framework for regression analysis with outcome missing not at random.

ABSTRACT: The instrumental variable (IV) design is a well-known approach for unbiased evaluation of causal effects in the presence of unobserved confounding. In this article, we study the IV approach to account for selection bias in regression analysis with outcome missing not at random. In such a setting, a valid IV is a variable which (i) predicts the nonresponse process, and (ii) is independent of the outcome in the underlying population. We show that under the additional assumption (iii) that the IV is independent of the magnitude of selection bias due to nonresponse, the population regression in view is nonparametrically identified. For point estimation under (i)-(iii), we propose a simple complete-case analysis which modifies the regression of primary interest by carefully incorporating the IV

SUBMITTER: Tchetgen Tchetgen EJ 

PROVIDER: S-EPMC5569006 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature