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Journal of Environmental and Public HealthVolume 2011 2011, Article ID 435078, 12 pages

Research Article

Children-s Hospital Boston and Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA

Boston University School of Public Health, 801 Massachusetts Avenue 3rd Floor, Boston, MA 02118, USA

Received 15 October 2010; Revised 14 February 2011; Accepted 24 February 2011

Academic Editor: Pam R. Factor-Litvak

Copyright © 2011 Emily A. Blood and Debbie M. Cheng. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Linear mixed models LMMs are frequently used to analyze longitudinal data. Although these models can be used to evaluate mediation, they do not directly model causal pathways. Structural equation models SEMs are an alternative technique that allows explicit modeling of mediation. The goal of this paper is to evaluate the performance of LMMs relative to SEMs in the analysis of mediated longitudinal data with time-dependent predictors and mediators. We simulated mediated longitudinal data from an SEM and specified delayed effects of the predictor. A variety of model specifications were assessed, and the LMMs and SEMs were evaluated with respect to bias, coverage probability, power, and Type I error. Models evaluated in the simulation were also applied to data from an observational cohort of HIV-infected individuals. We found that when carefully constructed, the LMM adequately models mediated exposure effects that change over time in the presence of mediation, even when the data arise from an SEM.

Author: Emily A. Blood and Debbie M. Cheng



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