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Partial Least Squares Structural Equation Modeling

PLS-SEM er en variansbaseret tilgang til strukturel ligningsmodellering, udviklet af Herman Wold (1985), som estimerer latente variabelmodeller ved at maksimere den forklarede varians i afhængige variabler. I modsætning til kovariansbaseret SEM er PLS-SEM særligt nyttig til eksplorativ forskning, små til mellemstore stikprøver, komplekse modeller med mange konstruktioner og ikke-normale data.

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Kilder

  1. Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd ed.). Sage Publications. ISBN: 9781483377445
  2. Wold, H. (1985). Partial least squares. In S. Kotz & N. L. Johnson (Eds.), Encyclopedia of Statistical Sciences (Vol. 6, pp. 581-591). Wiley. ISBN: 9780471822622
  3. Chin, W. W. (2010). How to write up and report PLS analyses. In V. E. Vinzi, W. W. Chin, J. Henseler, & H. Wang (Eds.), Handbook of Partial Least Squares: Concepts, Methods and Applications (pp. 655-690). Springer. DOI: 10.1007/978-3-540-32827-8_29

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ScholarGate. (2026, June 3). Partial Least Squares Structural Equation Modeling. ScholarGate. https://scholargate.app/da/psychometrics/pls-sem

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ScholarGatePartial Least Squares Structural Equation Modeling (Partial Least Squares Structural Equation Modeling). Hentet 2026-06-15 fra https://scholargate.app/da/psychometrics/pls-sem · Datasæt: https://doi.org/10.5281/zenodo.20539026