How collinearity affects mixture regression results
By Jan-Michael Becker, Christian M. Ringle, Marko Sarstedt, Franziska Völckner. 2015
517 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Food Science, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/2c2dc7fb7dafad68527992ced166a855249c7ecf
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Marko Sarstedt
- Christian M. Ringle
- Joseph F. Hair
- Jeffrey J. Risher
- Jun-Hwa (Jacky) Cheah
- Jörg Henseler
- Hiram Ting
- R. Ho
In Food Science
- Joseph F. Hair
- Christian M. Ringle
- Marko Sarstedt
- Jeffrey J. Risher
- Jörg Henseler
- Jun-Hwa (Jacky) Cheah
- Hiram Ting
- Izaskun Agirre Aramburu
In Statistics and Probability
- Christian M. Ringle
- Joseph F. Hair
- Marko Sarstedt
- Jörg Henseler
- M. Hanafiah
- Siegfried P. Gudergan
- Josef A. Mazanec
- Amata Ring
Citations in the corpus
- When to use and how to report the results of PLS-SEM (2019, background): “However, collinearity issues can also occur at lower VIF values of 3 (Mason and Perreault, 1991; Becker et al., 2015).”
- Innovation performance: The effect of knowledge-based dynamic capabilities in cross-country innovation ecosystems (2021, unknown): “A variance-based structural equation modelling (SEM) technique, using the partial least squares (PLS) approach (Ringle et al. 2015) was used.”