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Structural accelerated failure time models for the effects of observed exposures on repeated events in a clinical trial
Author(s) -
Vandebosch An,
Goetghebeur Els,
Van Damme Lut
Publication year - 2004
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.1988
Subject(s) - marginal structural model , estimator , econometrics , statistics , variance (accounting) , causal inference , accelerated failure time model , repeated measures design , randomization , treatment effect , estimation , randomized controlled trial , marginal model , event (particle physics) , survival analysis , computer science , mathematics , medicine , regression analysis , economics , surgery , physics , accounting , management , quantum mechanics , traditional medicine
Structural accelerated failure time models form a unique tool for the analysis of causal effects of observed exposures in randomized trials. When actual exposure levels are not completely controlled they may be selective, i.e. depend on unmeasured prognostic factors. Nevertheless, consistent randomization‐based estimators have been derived for the effect of such exposures on a right‐censored survival outcome. In this paper, we extend the methodology to allow for estimation of the structural effect of an experimental vaginal gel on repeated occurrences of genital lesions. The marginal distribution of each ordered event is modelled assuming a common treatment effect. Estimation is possible by inverting α‐level tests using a robust variance estimator to allow for correlated repeated events. We discuss the logical constraints imposed by this model choice as well as new challenges posed on recensoring. Copyright © 2004 John Wiley & Sons, Ltd.