PLS-SEM Toolbox

Versión 2.4 (1,16 MB) por Massimo Aria
Structural Equation Model through Partial Least Squares approach (PLS-SEM)
5.0
(2)
4,2K Descargas
Actualizado 19 feb 2016

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The PLS-SEM Toolbox provides the capability to estimate Structural Equation Models with Partial Least Squares algorithm (SEM-PLS, PLS-SEM or PLS Path Modeling).
Different setups for estimation of factor scores and weighting schemes can be used. Moreover, it comprises modular routines for computation of bootstrap confidence intervals, model parameters and several quality indices.
Numerous graphical outputs help to assess the model.
A well-known mobile phone dataset from marketing research is analyzed in the example to show the main characteristics of the toolbox.

Citar como

Massimo Aria (2026). PLS-SEM Toolbox (https://la.mathworks.com/matlabcentral/fileexchange/54147-pls-sem-toolbox), MATLAB Central File Exchange. Recuperado .

Compatibilidad con la versión de MATLAB
Se creó con R2015a
Compatible con cualquier versión
Compatibilidad con las plataformas
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Categorías
Más información sobre Conditional Mean Models en Help Center y MATLAB Answers.
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Versión Publicado Notas de la versión
2.4

update notes in the changelog file
2.3.0.0

Some minor fixes
2.2.0.0

- Added the function SMDesign_gui to draw the structural model using a GUI
2.1.0.0

Added a new function plspm_publish.m.
The function generates report of results in several formats (html, doc, ppt, xls, etc.)
2.0.0.0

New features:
-Overall model assessment: SRMR, TLI, FLI
-Heterotrait-Monotrait ratio of correlations (HTMT) criterium
-Rho by Dijkstra and Henseler
-All reliability indices in a single table
-A new table, showing the effect overview, has been added
1.3.1.0

Increased bootstrap speed.
1.3.0.0

Some improvements:
- Now, plspm function calculates also the Variance Inflaction Factors (VIFs) for model assessment of formative blocks;
- Now, bootstrap procedure calculates also t stats and pvalues for weights, loadings and path coefficients.
1.2.1.0

Updated the ECSI example
1.2.0.0

Corrected a bug in path_graph.m function
1.1.0.0

Corrected a bug in path_graph.m function
1.0.0.0