WarpPLS 4.0 now available: 3D graphs, new fit indices, causality assessment coefficients, and more!

Dear colleagues:

Version 4.0 of WarpPLS is now available, as a beta version. You can download and install it for a free trial from:

http://warppls.com

The full User Manual is also available for download from the web site above separately from the software.

Some important notes for users of previous versions:

- There is no need to uninstall previous versions of WarpPLS to be able to install and use this new version.

- Users of previous versions can use the same license information that they already have; it will work for version 4.0 for the remainder of their license periods.

- Project files generated with previous versions are automatically converted to version 4.0 project files. Users are notified of that by the software, and given the opportunity not to convert the files if they so wish.

- The MATLAB Compiler Runtime 7.14, used in this version, is the same as the one used in versions 2.0-3.0. Therefore, if you already have one of those versions of WarpPLS installed on your computer, you should not reinstall the Runtime.

WarpPLS is a powerful PLS-based structural equation modeling (SEM) software. Since its first release in 2009, its user base has grown steadily, now comprising more than 5,000 users in over 33 countries.

Some of its most distinguishing features are the following:

- It is very easy to use, with a step-by-step user interface guide.

- It identifies nonlinear relationships, and estimates path coefficients accordingly.

- It also models linear relationships, using standard PLS algorithms.

- It models reflective and formative variables, as well as moderating effects.

- It calculates P values, model fit indices, and collinearity estimates.

At the beginning of the User Manual you will see a list of new features in this version, some of which are listed below. The User Manual has more details on how these new features can be useful in SEM analyses.

- Users can now set inner and outer model algorithms separately, and are also allowed to set inner model algorithms for individual paths.

- New causality assessment coefficients are now reported, which can be used in the assessment of the plausibility and direction of hypothesized cause-effect relationships.

- Seven new model fit and quality indices have been added to the three previously available, bringing the total number of indices to ten.

- Many new graphs and related features are now available, including 3D graphs. Both multivariate and bivariate relationship graphs are now provided, for linear and nonlinear relationships, using standardized and unstandardized scales.

- Users can now segment curves based on increments in the first derivative of the predictor latent variables on each of their criteria latent variables. This provides an alternative to data segmentation approaches such as FIMIX-PLS, without any reduction in sample size.

Enjoy!