On two-stage estimation of structural instrumental variable models.

ABSTRACT: Two-stage least squares estimation is popular for structural equation models with unmeasured confounders. In such models, both the outcome and the exposure are assumed to follow linear models conditional on the measured confounders and instrumental variable, which is related to the outcome only via its relation with the exposure. We consider data where both the outcome and the exposure may be incompletely observed, with particular attention to the case where both are censored event times. A general class of two-stage minimum distance estimators is proposed that separately fits linear models for the outcome and exposure and then uses a minimum distance criterion based on the reduced-form model for the outcome to estimate the regression parameters of interest. An optimal minimum distance est

SUBMITTER: Choi BY 

PROVIDER: S-EPMC5793491 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature