Abstract
Marginal structural models (MSMs) allow estimation of effect modification by baseline covariates, but they are less useful for estimating effect modification by evolving time-varying covariates. Rather, structural nested models (SNMs) were specifically designed to estimate effect modification by time-varying covariates. In their paper, Petersen et al. (Am J Epidemiol 2007;166:985-993) describe history-adjusted MSMs as a generalized form of MSM and argue that history-adjusted MSMs allow a researcher to easily estimate effect modification by time-varying covariates. However, history-adjusted MSMs can result in logically incompatible parameter estimates and hence in contradictory substantive conclusions. Here the authors propose a more restrictive definition of history-adjusted MSMs than the one provided by Petersen et al. and compare the advantages and disadvantages of using history-adjusted MSMs, as opposed to SNMs, to examine effect modification by time-dependent covariates. © The Author 2007. Published by the Johns Hopkins Bloomberg School of Public Health. All rights reserved.
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CITATION STYLE
Robins, J. M., Hernán, M. A., & Rotnitzky, A. (2007, November). Invited commentary: Effect modification by time-varying covariates. American Journal of Epidemiology. https://doi.org/10.1093/aje/kwm231
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