Estimating the causal effect of a time-varying treatment on time-to-event using structural nested failure time models

Simple item page
dc.creatorLok, J. J.
dc.creatorGill, R. D.
dc.creatorvan der Vaart, A. W.
dc.creatorRobins, J. M.
dc.date2004-09-09
dc.date.accessioned2026-07-07T08:06:27Z
dc.date.available2026-07-07T08:06:27Z
dc.descriptionIn this paper we review an approach to estimating the causal effect of a time-varying 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 effect of the treatment cannot simply be estimated by conditioning on the patient characteristics, as these may themselves be indicators of the treatment effect. 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 effect of a time-varying treatment, and present methods for estimating and testing the parameters of these models.
dc.identifierhttps://arxiv.org/abs/math/0409165
dc.identifierhttp://arxiv.org/abs/math/0409165
dc.identifierStatistica Neerlandica (2004), vol. 58, 271-295
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/130613
dc.subjectStatistics Theory
dc.subject62P10; 62M99
dc.titleEstimating the causal effect of a time-varying treatment on time-to-event using structural nested failure time models
dc.typetext

Files

Collections

arXiv