Confirmatory Composite Analysis (CCA)
Confirmatory composite analysis (CCA) is a series of steps that can be executed with composite-based SEM methods, such as PLS-SEM or GSCA, to confirm both reflective and formative measurement models within a specific nomological network (Hair et al., 2018, Chapter 13; Hair et al., 2020; Henseler & Schuberth, 2020; Schuberth et al., 2018). Researchers use CCA when they want to test the quality of a measurement model in a confirmatory way, similar in spirit to confirmatory factor analysis (CFA) in CB-SEM, but suited to composite-based estimation. However, there is ongoing dispute in the literature over the proper execution of CCA and over how different views on the procedure relate to each other (for an introduction and a discussion of these different views, see Crittenden et al., 2020), which is why we do not generally recommend CCA as the primary measurement model evaluation approach.
CCA in SmartPLS
SmartPLS fully supports the execution of CCA in PLS-SEM. For an applied example, see Ciavolino et al. (2022), who use CCA for the Italian validation of the Interactions Anxiousness Scale.
Frequently Asked Questions
What is confirmatory composite analysis (CCA)?
CCA is a series of steps executed with composite-based SEM methods, such as PLS-SEM or GSCA, to confirm both reflective and formative measurement models within a specific nomological network.
Does SmartPLS support CCA?
Yes. SmartPLS fully supports the execution of CCA in PLS-SEM.
Should I use CCA to validate my measurement model?
There is ongoing dispute in the literature over the proper execution of CCA and over the different perspectives on the procedure. Because of this dispute, we do not generally recommend CCA as the primary measurement model evaluation approach.
How does CCA relate to confirmatory factor analysis (CFA)?
CCA plays a role for composite-based SEM methods that is similar to the role CFA plays for common factor-based methods: both aim to confirm a measurement model within a nomological network, but CCA is designed for composite estimation, such as PLS-SEM, while CFA is used in CB-SEM.
Related SmartPLS Methods
- Confirmatory tetrad analysis in PLS (CTA-PLS)
- Discriminant validity assessment (HTMT)
- Confirmatory factor analysis (CFA)
- CB-SEM
- PLS-SEM algorithm
References
- Ciavolino, E., Ferrante, L., Sternativo, G. A., Cheah, J.-H., Rollo, S., Marinaci, T., & Venuleo, C. (2022). A confirmatory composite analysis for the Italian validation of the Interactions Anxiousness Scale: A higher-order version. Behaviormetrika, 49(1), 23–46.
- Crittenden, V., Sarstedt, M., Astrachan, C., Hair, J., & Lourenco, C. E. (2020). Guest editorial: Measurement and scaling methodologies. Journal of Product & Brand Management, 29(4), 409–414.
- Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2018). Multivariate data analysis (8th ed.). Cengage.
- Hair, J. F., Howard, M. C., & Nitzl, C. (2020). Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research, 109, 101–110.
- Henseler, J., & Schuberth, F. (2020). Using confirmatory composite analysis to assess emergent variables in business research. Journal of Business Research, 120, 147–156.
- Schuberth, F., Henseler, J., & Dijkstra, T. K. (2018). Confirmatory composite analysis. Frontiers in Psychology, 9, Article 2541.
- More literature ...
Cite correctly
Please always cite the use of SmartPLS!
Ringle, Christian M., Wende, Sven, & Becker, Jan-Michael. (2024). SmartPLS 4. Bönningstedt: SmartPLS. Retrieved from https://www.smartpls.com
