Abstract
The aim of this Methodological Brief to structural equation modeling (SEM) is to help readers become more aware of its uses and how to understand research using it. SEM provides many benefits over traditional multiple regression, including the ability to model multiple outcomes simultaneously and to account for measurement error. This Brief provides a general overview of the purposes of SEM and reviews how SEM can estimate models with both observed variables as well as their underlying constructs and how the adequacy of models is assessed in SEM. Finally, this Brief introduces path diagrams and latent variable models with an illustration of how to understand diagrams and standardized estimates.
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