Statistical modeling of causal effects in continuous time
| dc.creator | Lok, Judith J. | |
| dc.date | 2004-10-11 | |
| dc.date | 2008-06-19 | |
| dc.date.accessioned | 2026-07-07T09:45:25Z | |
| dc.date.available | 2026-07-07T09:45:25Z | |
| dc.description | This article studies the estimation of the causal effect of a time-varying treatment on time-to-an-event or on some other continuously distributed outcome. The paper applies to the situation where treatment is repeatedly adapted to time-dependent patient characteristics. The treatment effect cannot be estimated by simply conditioning on these time-dependent patient characteristics, as they may themselves be indications of the treatment effect. This time-dependent confounding is common in observational studies. Robins [(1992) Biometrika 79 321--334, (1998b) Encyclopedia of Biostatistics 6 4372--4389] has proposed the so-called structural nested models to estimate treatment effects in the presence of time-dependent confounding. In this article we provide a conceptual framework and formalization for structural nested models in continuous time. We show that the resulting estimators are consistent and asymptotically normal. Moreover, as conjectured in Robins [(1998b) Encyclopedia of Biostatistics 6 4372--4389], a test for whether treatment affects the outcome of interest can be performed without specifying a model for treatment effect. We illustrate the ideas in this article with an example. | |
| dc.description | Published in at http://dx.doi.org/10.1214/009053607000000820 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org) | |
| dc.identifier | https://arxiv.org/abs/math/0410271 | |
| dc.identifier | http://arxiv.org/abs/math/0410271 | |
| dc.identifier | Annals of Statistics 2008, Vol. 36, No. 3, 1464-1507 | |
| dc.identifier | doi:10.1214/009053607000000820 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/163186 | |
| dc.subject | Statistics Theory | |
| dc.subject | 62P10 (Primary) 62M99 (Secondary) | |
| dc.title | Statistical modeling of causal effects in continuous time | |
| dc.type | text |