Events and Meetings of Italian Statistical Society, Advances in Latent Variables - Methods, Models and Applications

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Comparing Maximum Likelihood and PLS Estimators for Structural Equation Modeling with Formative Blocks
Pasquale Dolce, Natale Carlo Lauro

Last modified: 2013-06-14

Abstract


A common misunderstanding found in the literature is that only PLS-PM allows the estimation of SEM including formative blocks. However, if certain model specification rules are followed, the model is identified, and it is possible to estimate a Covariance-Based SEM with formative blocks.Due to the complexity of both SEM estimation techniques, we study, in the framework of the same simulation design, their relative performance, analysing the bias and the variability of the estimates.We find that both PLSPM and ML-SEM perform particularly well in terms of bias and efficiency of the parameter estimates when the variance of the disturbance in the formative block is small. As we increase the variance of the disturbance, the bias of the inner PLS estimates grows significantly, while the variability holds steady to a very low value. On the contrary, the inner ML estimates present a minor degree of bias, but the variability of grows drastically. Nevertheless, the two approaches behave almost equally in the formative outer block.

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