SmartPLS

SmartPLS
Original author(s) Christian M. Ringle, Sven Wende, Jan-Michael Becker
Developer(s) SmartPLS GmbH
Initial release 2005 (2005)
Stable release
SmartPLS 3.2.7 / September 18, 2017 (2017-09-18)
Operating system Windows and Mac
Platform Java
Available in English, German, Spanish, Portuguese, Italian, French, Chinese, Japanese, Persian, Arabic, Persian, Indonesian
Type Statistical analysis, multivariate analysis, structural equation modeling, partial least squares path modeling
License SmartPLS 2: Freeware, SmartPLS 3: Proprietary software
Website www.smartpls.com/smartpls2

SmartPLS is a software with graphical user interface for variance-based structural equation modeling (SEM) using the partial least squares (PLS) path modeling method.[1] Besides estimating path models with latent variables using the PLS-SEM algorithm,[2][3] the software computes standard results assessment criteria (e.g., for the reflective and formative measurement models, the structural model, and the goodness of fit)[4] and it supports additional statistical analyses (e.g., confirmatory tetrad analysis, importance-performance map analysis, segmentation, multigroup).[5] Since SmartPLS is programmed in Java, it can be executed and run on different computer operating systems such as Windows and Mac.[6]

See also

References

  1. ↑ Wong, K. K. K. (2013). Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24(1), pp. 1-32, p. 1, p. 15, and p. 30.
  2. ↑ Lohmöller, J.-B. (1989). Latent Variable Path Modeling with Partial Least Squares. Physica: Heidelberg, p. 29.
  3. ↑ Wold, H. O. A. (1982). Soft Modeling: The Basic Design and Some Extensions, in: K. G. Jöreskog and H. O. A. Wold (eds.), Systems Under Indirect Observations: Part II, North-Holland: Amsterdam, pp. 1-54, pp. 2-3.
  4. ↑ Ramayah, T., Cheah, J., Chuah, F., Ting, H., and Memon, M. A. (2016). Partial Least Squares Structural Equation Modeling (PLS-SEM) Using SmartPLS 3.0: An Updated and Practical Guide to Statistical Analysis, Singapore et al.: Pearson, pp. 59-148.
  5. ↑ Garson, G. D. (2016). Partial Least Squares Regression and Structural Equation Models, Statistical Associates: Asheboro, pp. 122-188.
  6. ↑ Temme, D., Kreis, H., and Hildebrandt, L. (2010). A Comparison of Current PLS Path Modeling Software: Features, Ease-of-Use, and Performance, in: V. Esposito Vinzi, W. W. Chin, J. Henseler, and H. Wang (eds.), Handbook of Partial Least Squares: Concepts, Methods and Applications, Springer: Berlin-Heidelberg, pp. 737-756, p.745.
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