title: A doubly robust estimator for the average treatment effect in the context of a mean-reverting measurement error.
abstract: One of the main limitations of causal inference methods is that they rely on the assumption that all variables are measured without error. A popular approach for handling measurement error is simulation-extrapolation (SIMEX). However, its use for estimating causal effects have been examined only in the context of an additive, non-differential, and homoscedastic classical measurement error structure. In this article we extend the SIMEX methodology, in the context of a mean reverting measurement error structure, to a doubly robust estimator of the average treatment effect when a single covariate is measured with error but the outcome and treatment and treatment indicator are not. Throughout this article we assume that an independent validation sample is available. Simulation studies suggest that our method performs better than a naive approach that simply uses the covariate measured with error.
authors.affiliation: Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 NWolfe St, E3031 BSPH, Baltimore, MD 21205, USAdlenis@jhsph.edu.
authors.forename: David
authors.initials: D
authors.lastname: Lenis
authors.affiliation: Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, 624 N. Broadway, Hampton House 806, Baltimore, MD 21205, USA.
authors.forename: Cyrus F
authors.initials: CF
authors.lastname: Ebnesajjad
authors.affiliation: Departments of Mental Health, Biostatistics and Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, 624 N. Broadway, Hampton House 839, Baltimore, MD 21205, USA.
authors.forename: Elizabeth A
authors.initials: EA
authors.lastname: Stuart
mesh_terms: D000293:Adolescent; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006801:Humans; D017063:Outcome Assessment, Health Care / Q000379:methods* / Q000592:standards*; D057216:Propensity Score
keywords: Average treatment effect (ATE); Causal inference; Doubly robust; Mean reverting measurement error; Measurement error; Propensity score; SIMEX