The debate concerning procedures and techniques of data treatment is relevant in the context of production and progress of knowledge in a broad range of subject areas. In the past decade, a framework of data treatment methods denominated Structural Equation Modeling received a great deal of attention from researchers. This data treatment procedure has its historical origins related to different areas of knowledge like biometrics, econometrics and psychometrics. As a consequence of its unique characteristics, scientific report in Structural Equation Modeling should consider various relevant aspects, like the theoretical definition of the model to be tested, the specification and identification of the model, as well as estimation and measurement aspects of the adequation indices. Several of these elements are presented and discussed in the present article, focusing on the possibilities of practical application in the field of Psychology and related sciences. In addition, future perspectives and limitations of Structural Equation Modeling are also discussed.
structural equation modeling; multivariate data analysis; multiple equation models
