Premature conclusions about the signal‐to‐noise ratio in structural equation modeling research

• Main Author: Schuberth, Florian
• Publication Date: 2023
• Other Authors: Schamberger, Tamara, Rönkkö, Mikko, Liu, Yide, Henseler, Jörg
• Format: Other
• Language: eng
• Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Download full: http://hdl.handle.net/10362/158813
• topic: composite model; covariance-based structural equation modeling; effect size; factor score regression; Henseler–Ogasawara specification; partial least squares structural equation modeling; regression analysis with weighted composites; sum scores; Statistics and Probability; Arts and Humanities (miscellaneous); Psychology(all)

Schuberth, F., Schamberger, T., Rönkkö, M., Liu, Y., & Henseler, J. (2023). Premature conclusions about the signal‐to‐noise ratio in structural equation modeling research: A commentary on Yuan and Fang (2023). British Journal of Mathematical and Statistical Psychology, 76(3), 682-694. https://doi.org/10.1111/bmsp.12304 --- Funding Information: Jörg Henseler served as a reviewer for Yuan and Fang's ( 2023 ) manuscript. He gratefully acknowledges financial support from FCT Fundação para a Ciência e a Tecnologia (Portugal), national funding through a research grant from the Information Management Research Center – MagIC/NOVA IMS (UIDB/04152/2020). We thank Hao Wu, Associate Editor of the British Journal of Mathematical and Statistical Psychology, for giving us the opportunity to write this commentary. Moreover, we thank Alexandra Elbakyan for her efforts in making science accessible. Finally, we thank Yves Rosseel for his support in replicating Yuan and Fang's results in lavaan. British Journal of Mathematical and Statistical Psychology