Structural equation modeling (SEM) is a particular form of data analysis. According to this approach, a researcher begins with a model that specifies how multiple variables are related to each other. These theorized relationships are formalized into a set of equations that include the variables in question. These variables are then measured and their relations to each other are quantified. The test of the model involves an assessment of how well the equations can reproduce or “fit” the observed relations.

As a simple example, consider a model in which the researcher theorizes that variable A influences C because of its influence on B. Schematically, A → B → C. This model has two equations, one that predicts B using A and one that predicts C using ...