The application of structural equation models (SEMs) is common in marketing and the behavioral sciences. Accordingly, the exploration of more effective methods to estimate SEMs is also a popular area of research. Croon (2002) and Skrondal and Laake (2001) have each proposed a new method for estimating SEMs, but since these proposals nearly a decade ago, these methods have been mostly overlooked by applied researchers. We suggest that reasons for this oversight may include not only a lack of guidance in implementing these new methods but also the absence of a formal comparison to review these new methods relative to the more familiar maximum likelihood structural equation modeling (MLSEM) and partial least squares (PLS). In this paper, our goal was to make the Croon and Skrondal-Laake (SL) methods more accessible to applied researchers. We first provide a step-by-step illustration of how to implement the Croon and SL methods. We also present the first comprehensive evaluation of the new methods relative to MLSEM and PLS. From this evaluation, we can better appreciate the circumstances under which these new methods are preferable to MLSEM and PLS. Thus, we intend to help readers understand how and when to apply these new methods.

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Keywords Covariance structure model, LISREL, Monte Carlo simulation, Partial least squares, Structural equation modeling
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Journal International Journal of Research in Marketing
Lu, I, Kwan, E, Thomas, D.R. (D. Roland), & Cedzynski, M. (Marzena). (2011). Two new methods for estimating structural equation models: An illustration and a comparison with two established methods. International Journal of Research in Marketing, 28(3), 258–268. doi:10.1016/j.ijresmar.2011.03.006