Torben Martinussen, Ph.D
Estimation of direct effect for survival data using the Aalen additive hazards model
Was |
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Wann |
07.05.2010 von 09:30 bis 10:45 |
Wo | IMBI, Stefan-Meier-Str.26 |
Name | Kristin Ohneberg |
Kontakttelefon | 07612037701 |
Termin übernehmen |
vCal iCal |
Torben Martinussen
Associate Professor
University of Copenhagen
We are interested in estimating the direct effect of an exposure variable X on a survival outcome T. In case of an intermediate variable K and an unobserved confounder U for the effect of K on T standard regression techniques will render a biased estimate of the direct effect of X on T. This problem may be solved with the inclusion of additional information, L, that removes the effect of U on K. However, if L is also affected by X then standard methods are still not appropriate. Marginal structural models have been suggested to tackle this problem but they need estimation of specific weights that may be quite unstable. To overcome this problem, Goetgeluk et al. (JRSSB, 2009) suggested a so-called G-estimation approach in the case of an un-censored response variable. In this talk I show how to generalize their approach to the setting of survival data. I start out by describing the dynamic path analysis approach and point out that it may give wrong answers in case of an un-measured confounder.