Structural equation modeling: A primer for health behavior researchers

Objective: To introduce the state of the art of structural equation modeling (SEM). Method: This primer is organized in a manner allowing readers to review any one of 5 freestanding sections. Results: SEM maintains several advantages over regression and other multivariate techniques. Through a 2-step modeling process, SEM strengthens research by allowing for the specification of complex, theory-driven models that can be tested with empirical data. Although use of SEM alone is not a magic solution, new software developments provide users with unparalleled flexibility for improving research. Conclusion: SEM must be thrust into the daily vocabulary and routine practice of health behavior researchers.