 :: Partial Least Squares  Path Modeling  Free Statistics Software (Calculator) :: 


All rights reserved. The noncommercial (academic) use of this software is free of charge. The only thing that is asked in return is to cite this software when results are used in publications.
This free online software (calculator) computes Path Models with Latent Variables by the Partial Least Squares Approach. There is a maximum of 8 latent variables that can be defined. The relationship between the latent variables is defined through a lower triangular matrix (column variables have an impact on row variables). Load the default data set to see a working example of the PLSPM.
Enter (or paste) a matrix (table) containing all data (time) series. Every column represents a different variable and must be delimited by a space or Tab. Every row represents a period in time (or category) and must be delimited by hard returns. The easiest way to enter data is to copy and paste a block of spreadsheet cells. Please, do not use commas or spaces to seperate groups of digits!
Click here to edit the underlying code of this R Module.Source code of R module  

Cite this software as:  Wessa P., 2014, Partial Least Squares  Path Modeling (v1.0.9) in Free Statistics Software (v1.1.23r7), Office for Research Development and Education, URL http://www.wessa.net/rwasp_partial_least_squares.wasp/   The R code is based on :   Tenenhaus, M., Esposito Vinzi, V., Chatelin Y.M., and Lauro, C. (2005) PLS path modeling. Computational Statistics & Data Analysis, 48, pp. 159205.   Tenenhaus, M., and Pages, J. (2001) Multiple factor analysis combined with PLS path modelling. Application to the analysis of relationships between physicochemical variables, sensory profiles and hedonic judgements. Chemometrics and Intelligent Laboratory Systems, 58, pp. 261273.   Tenenhaus, M., and Hanafi, M. A bridge between PLS path modeling and multiblock data analysis. Handbook on Partial Least Squares (PLS): Concepts, methods, and applications. Springer: In press.   Lohmoller, J.B. (1989) Latent variables path modelin with partial least squares. Heidelberg: PhysicaVerlag.   Wold, H. (1985) Partial Least Squares. In: Kotz, S., Johnson, N.L. (Eds.), Encyclopedia of Statistical Sciences, Vol. 6. Wiley, New York, pp. 581591.  Wold, H. (1982) Soft modeling: the basic design and some extensions. In: K.G. Joreskog & H. Wold (Eds.), _Systems under indirect observations: Causality, structure, prediction, Part 2, pp. 154. Amsterdam: Holland.     

To cite Wessa.net in publications use: Wessa, P. (2017), Free Statistics Software, Office for Research Development and Education, version 1.1.23r7, URL http://www.wessa.net/
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