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Developing a predictive method : a comparative study of the partial least squares vs. maximum likelihood techniques

Rodgers, Waymond (contributor); Pavlou, Paul A. (contributor) - 2006

Persistent link: https://www.econbiz.de/10003246814

Partial least squares : a versatile tool for the analysis of high-dimensional genomic data

Boulesteix, Anne-Laure (contributor); … - 2005

Partial Least Squares (PLS) is a highly efficient statistical regression technique that is well suited for the analysis of high-dimensional genomic data. In this paper we review the theory and applications of PLS both under methodological and biological points of view. Focusing on microarray...

Persistent link: https://www.econbiz.de/10003309967

Finite mixture partial least squares analysis : methodology and numerical examples

Ringle, Christian M.; Wende, Sven; Will, Alexander - In: Handbook of partial least squares : concepts, methods …, (pp. 195-218). 2010

Persistent link: https://www.econbiz.de/10003944610

Testing measurement invariance of composites using partial least squares

Hensler, Jörg; Ringle, Christian M.; Sarstedt, Marko - In: International marketing review 33 (2016) 3, pp. 405-431

Persistent link: https://www.econbiz.de/10011487000

Addressing endogeneity in international marketing applications of partial least squares structural equation modeling

Hult, G. Tomas M.; Hair, Joseph F.; Proksch, Dorian; … - In: Journal of international marketing 26 (2018) 3, pp. 1-21

Persistent link: https://www.econbiz.de/10011924475

Statistical inference with PLSc using bootstrap confidence intervals

Aguirre-Urreta, Miguel I.; Rönkkö, Mikko - In: Management information systems : mis quarterly 42 (2018) 3, pp. 1001-1020

Persistent link: https://www.econbiz.de/10011919706

Choosing PLS path modeling as analytical method in European management research : a realist perspective

Rigdon, Edward E. - In: European management journal 34 (2016) 6, pp. 598-605

Persistent link: https://www.econbiz.de/10011625062

Assessing the predictive performance of structural equation model estimators

Evermann, Joerg; Tate, Mary - In: Journal of business research : JBR 69 (2016) 10, pp. 4565-4582

Persistent link: https://www.econbiz.de/10011554711

Improving prediction with POS and PLS consistent estimations : an illustration

Mourad, Siham; Valette-Florence, Pierre - In: Journal of business research : JBR 69 (2016) 10, pp. 4675-4684

Persistent link: https://www.econbiz.de/10011554752

How to specify, estimate, and validate higher-order constructs in PLS-SEM

Sarstedt, Marko; Hair, Joseph F.; Cheah, Jun-Hwa; … - In: Australasian marketing journal 27 (2019) 3, pp. 197-211

Persistent link: https://www.econbiz.de/10012110334