Response to Invited Commentary The Authors Respond to “Structural Equation Models and Epidemiologic Analysis”

Dr. VanderWeele has provided an insightful commentary (1) on our article (2) on the use of structural equation mod-eling (SEM) as a tool for epidemiologic analysis. In his commentary, he illustrates the degree to which strong as-sumptions are made when conducting SEM analyses. For example, as described for regression analysis, linearity as-sumptions are made across all relations with the outcome variable. Dr. VanderWeele gives alternative methods to SEM for causal and mediation analysis and argues that in light of these wider-ranging assumptions, SEM should pri-marily be used for exploratory analysis and hypothesis gen-eration when there are a broad number of effects to be investigated (1). While we agree that it is important to weigh the benefits of SEM against the limitations posed by broad assumptions, there is general consensus that an un