PLS-SEM Toolbox

Version 2.4 (1.16 MB) by Massimo Aria
Structural Equation Model through Partial Least Squares approach (PLS-SEM)
Updated 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.

Cite As

Massimo Aria (2024). PLS-SEM Toolbox (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2015a
Compatible with any release
Platform Compatibility
Windows macOS Linux
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Version Published Release Notes

update notes in the changelog file

Some minor fixes

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

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

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

Increased bootstrap speed.

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.

Updated the ECSI example

Corrected a bug in path_graph.m function

Corrected a bug in path_graph.m function