Relation between three classes of structural models for the effect of a time-varying exposure on survival
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Author(s)
Young, Jessica G.
Hernan, Miguel Angel
Picciotto, Sally
Robins, James A.
Date Issued
November 2009
Journal
Lifetime Data Analysis
Publisher
Springer Science + Business Media B.V.
Citation
Young, Jessica G. et al. “Relation between three classes of structural models for the effect of a time-varying exposure on survival.” Lifetime Data Analysis 16 (2009): 71-84.
Version
Author's final manuscript
Abstract
Standard methods for estimating the effect of a time-varying exposure on survival may be biased in the presence of time-dependent confounders themselves affected by prior exposure. This problem can be overcome by inverse probability weighted estimation of Marginal Structural Cox Models (Cox MSM), g-estimation of Structural Nested Accelerated Failure Time Models (SNAFTM) and g-estimation of Structural Nested Cumulative Failure Time Models (SNCFTM). In this paper, we describe a data generation mechanism that approximately satisfies a Cox MSM, an SNAFTM and an SNCFTM. Besides providing a procedure for data simulation, our formal description of a data generation mechanism that satisfies all three models allows one to assess the relative advantages and disadvantages of each modeling approach. A simulation study is also presented to compare effect estimates across the three models.
MIT Department
Harvard University--MIT Division of Health Sciences and Technology
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1007/s10985-009-9135-3
