Structural equation modeling (SEM) provides scholars the opportunity to articulate, and then test, a system of relationships between variables. This statistical approach is useful in advancing health communication research because scholars have the opportunity to statistically test the overarching picture outlined by the theoretical structure of a set of variables. Certainly there are other statistical tests that may be more appropriate to the type of questions asked by scholars or the types of variables that are measured; indeed, SEM is not infallible and there is much room for the misuse of this technique, particularly as software becomes increasingly intuitive to use. Nevertheless, SEM generally has two advantages not available from other statistical tests: (1) the simultaneous analysis of an entire theoretical model that articulates a ...

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