Combining sub-samples for improved statistical power in PLS-SEM: A constrained latent growth approach

The article below discusses how a researcher can combine sub-samples for improved statistical power in multigroup analyses, employing a constrained latent growth approach, in the context of structural equation modeling via partial least squares (PLS-SEM).

Cox, J. (2024). Combining sub-samples for improved statistical power in PLS-SEM: A constrained latent growth approach. Data Analysis Perspectives Journal, 5(1), 1-5.

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Abstract:

Often researchers gather data that contain or can be segmented into subsamples. Therefore, sometimes a question arises as to whether the data can be treated as one sample or as several distinct samples. In this paper, I discuss how to conduct a multigroup analysis in a structural equation model with partial least squares (PLS-SEM) and demonstrate how empirical data from two different countries can be treated as one sample when using WarpPLS 8.0 to achieve higher statistical power.

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