Estimating the Causal Effect of a Time-Varying Treatment on Time-to-Event Using Structural Nested Failure Time Models (2003)
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BibTeX
@MISC{Robins03estimatingthe,
author = {James Robins and Judith Lok and Richard Gill and Aad Van Der Vaart},
title = {Estimating the Causal Effect of a Time-Varying Treatment on Time-to-Event Using Structural Nested Failure Time Models},
year = {2003}
}
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Abstract
In this paper we review an approach to estimating the causal e#ect of a timevarying treatment on time to some event of interest. This approach is designed for the situation where the treatment may have been repeatedly adapted to patient characteristics, which themselves may also be time-dependent. In this situation the e#ect of the treatment cannot simply be estimated by conditioning on the patient characteristics, as these may themselves be indicators of the treatment e#ect. This so-called time-dependent confounding is typical in observational studies. We discuss a new class of failure time models, structural nested failure time models, which can be used to estimate the causal e#ect of a time-varying treatment, and present methods for estimating and testing the parameters of these models.
