Combining composites and factors in PLS-SEM models: A multi-algorithm technique

The article below presents a multi-algorithm technique for combining latent variables estimated as composites or factors into a single model, in the context of structural equation modeling via partial least squares (PLS-SEM).

Kock, N. (2024). Combining composites and factors in PLS-SEM models: A multi-algorithm technique. Data Analysis Perspectives Journal, 5(4), 1-8.

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Abstract:

A multi-algorithm technique is presented for combining latent variables estimated as composites or factors into a single model, in the context of structural equation modeling via partial least squares. The multi-algorithm technique consists of three key steps: selecting composite-based or factor-based outer model analysis algorithms to be used for latent variable estimation; adding the latent variables estimated with the chosen composite-based or factor-based algorithms as new standardized variables; and creating and estimating a final model with the new variables added as single indicators of latent variables.

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A comparison of data analyses with WarpPLS and Stata: A study of trust and its role regarding internet use and subjective well-being

The article below provides a comparative assessment of analyses using the software packages WarpPLS and Stata, in the context of structural equation modeling via partial least squares (PLS-SEM), based on an illustrative study of trust and its role regarding internet use and subjective well-being.

Samak, A., Islam, M. R., & Hanke, D. (2024). A comparison of data analyses with WarpPLS and Stata: A study of trust and its role regarding internet use and subjective well-being. Data Analysis Perspectives Journal, 5(3), 1-6.

Link to full-text file for this and other DAPJ articles:

https://scriptwarp.com/dapj/#Published_Articles

Abstract:

This study investigates the mediating roles of social and institutional trust in the relationship between internet use and subjective well-being, using partial least squares (PLS)-based structural equation modeling (SEM). We compare WarpPLS 8.0 and Stata’s PLS-SEM package, utilizing data from the European Social Survey (ESS), round 8. Our results show consistent model fit and path coefficients across both tools, confirming the significant mediating effects of trust. WarpPLS stands out for its advanced model diagnostics, while Stata’s PLS-SEM excels in integrating with Stata’s broader data management and statistical analysis tools. This comparative analysis contributes to the SEM methodological literature.

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