The “Ten Commandments of SEM”

Structural equation modeling (SEM) is a confirmatory method that allows researchers to test hypothesized relationships between variables and probe the ways that they influence each other. Rightly done it can be a very useful approach to have in your toolbox of methods. Still, true to most complicated techniques there are few ways to do it correctly and many, many more ways to screw it up.

On the rare occasion that I need to review a paper that uses structural equation modeling I always refer to the ‘ten commandments’, listed below (Thompson, 2000). They are a simple series of statements that can help steer researchers during the analysis and reporting phases of an experiment using SEM or similar analysis. If you are unfamiliar with SEM they might read like gibberish, but for those in the know they read like truth. Good stuff.

1. Do not conclude that a model is the only model to fit the data.
2. Test respecified models with split-halves data or new data.
3. Test multiple rival models.
4. Use a two-step approach of testing the measurement model first, then the structural model.
5. Evaluate models by theory as well as statistical fit.
6. Report multiple fit indices.
7. Show you meet the assumption of multivariate normality.
8. Seek parsimonious models.
9. Consider the level of measurement and distribution of variables in the model.
10. Do not use small samples.

* Thompson, B. (2000). Ten commandments of structural equation modeling. p261-284 in L. Grimm & P. Yarnell, eds. Reading and understanding more multivariate statistics. Washington, DC: American Psychological Association.

January 22, 2009 • Posted in: Statistics

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