• Epidemiology · Jul 2018

    Eliminating Survivor Bias in Two-stage Instrumental Variable Estimators.

    • Stijn Vansteelandt, Stefan Walter, and Eric Tchetgen Tchetgen.
    • From the Department of Applied Mathematics, Computer Sciences and Statistics, Ghent University, Ghent, Belgium.
    • Epidemiology. 2018 Jul 1; 29 (4): 536-541.

    AbstractMendelian randomization studies commonly focus on elderly populations. This makes the instrumental variables analysis of such studies sensitive to survivor bias, a type of selection bias. A particular concern is that the instrumental variable conditions, even when valid for the source population, may be violated for the selective population of individuals who survive the onset of the study. This is potentially very damaging because Mendelian randomization studies are known to be sensitive to bias due to even minor violations of the instrumental variable conditions. Interestingly, the instrumental variable conditions continue to hold within certain risk sets of individuals who are still alive at a given age when the instrument and unmeasured confounders exert additive effects on the exposure, and moreover, the exposure and unmeasured confounders exert additive effects on the hazard of death. In this article, we will exploit this property to derive a two-stage instrumental variable estimator for the effect of exposure on mortality, which is insulated against the above described selection bias under these additivity assumptions.

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