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Testing the Validity of Reflective and Formative Latent Variables in PLS-SEM Using WarpPLS

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Testing the Validity of Reflective and Formative Latent Variables in PLS-SEM Using WarpPLS

PLS-SEM is typically analyzed and interpreted in three sequential stages. The process begins with the analysis of the measurement model, which focuses on assessing the validity and reliability of the model. This stage is followed by the examination of model fit and quality indices. The final stage involves analyzing the structural model, which examines the relationships among latent variables used to address research hypotheses, including direct effects, indirect effects, and moderating effects.

For guidance on the validity assessment of reflective latent variables using WarpPLS, refer to Amora (2021). For the validity of formative latent variables, including both first-order and higher-order latent variables, consult Amora (2023).

 
References:

Amora, J. T. (2021). Convergent validity assessment in PLS-SEM: A loadings-driven approach. Data Analysis Perspectives Journal, 2(3), 1-6.
https://scriptwarp.com/dapj/2021_DAPJ_2_3/Amora_2021_DAPJ_2_3_ConvergentValidity.pdf



Amora, J. T. (2023). On the validity assessment of formative measurement models in PLS-SEM. Data Analysis Perspectives Journal, 4(2), 1-7.
https://scriptwarp.com/dapj/2023_DAPJ_4_2/Amora_2023_DAPJ_4_2_FormativeAssessment.pdf

 




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