Structural Equation Modeling

Structural Equation Modeling (SEM), refers to a diverse set of mathematical models, computer algorithms, and statistical methods that fit networks of constructs to data. A structural equation model is a set of equations in which each variable is assigned a value that is an explicit function of other variables in the system. SEM includes confirmatory factor analysis, path analysis, partial least squares path analysis, LISREL and latent growth modeling. The term should not be confused with Structural Modeling in economics. Structural equation models are often used to assess unobservable ‘latent’ constructs. They often invoke a measurement model that defines latent variables using one or more observed variables, and a structural model that imputes relationships between latent variables.

Various methods in structural equation modeling have been used in the sciences, business, education, and other fields. Use of SEM methods in analysis is controversial because SEM methods generally lack widely accepted goodness-of-fit statistics and most SEM software offers little latitude for error analysis. This puts SEM at a disadvantage with respect to systems of regression equation methods, though the latter are limited in their ability to fit unobserved ‘latent’ constructs.

See also

Material

• PLS-SEM book: online resources and additional information
• Ed Rigdon’s Structural Equation Modeling Page
• The causal interpretation of structural equations (or SEM survival kit)

Papers

• Savalei, V., & Bentler, P. M. (2010). Structural equation modeling. Corsini encyclopedia of psychology.
• Pearl, J. (1998). Graphs, causality, and structural equation models. Sociological Methods & Research, 27(2), 226-284.
• Pearl, J. (2003). Causality: models, reasoning and inference. Econometric Theory, 19, 675-685.
• Bandalos, D. L. (2002). The effects of item parceling on goodness-of-fit and parameter estimate bias in structural equation modeling. Structural Equation Modeling, 9(1), 78-102.

Books

• Little, T. D. (2013). Longitudinal structural equation modeling. Guilford Press.
• Schumacker, R. E., & Lomax, R. G. (2004). A beginner’s guide to structural equation modeling. Psychology Press.
• Long, J. Scott (1993). Testing Structural Equation Models. Sage Publications (CA)
• Marcoulides, G. A., & Schumacker, R. E. (2013). Advanced structural equation modeling: Issues and techniques. Psychology Press.
• Ullman, J. B., & Bentler, P. M. (2003). Structural equation modeling. John Wiley & Sons, Inc..
• Santoso, S. (2011). Structural Equation Modeling. Elex Media Komputindo.