Wednesday, January 22, 2020
WarpPLS 7.0 beta now available: HTMT, new moderating effects features, and more!
Dear colleagues:
Version 7.0 of WarpPLS is now available, as a beta version. You can download and install it for a free trial from:
https://warppls.com
Below is a summary of this version’s new features.
HTMT ratios. The sub-option “'Discriminant validity coefficients (extended set)”, under the menu option “Explore additional coefficients and indices”, now allows you to inspect the heterotrait-monotrait (HTMT) ratios calculated by the software. These ratios have been proposed for discriminant validity assessment, particularly in the context of composite-based SEM via classic PLS algorithms; as opposed to factor-based SEM via modern algorithms that estimate factors (which have been available from this software for quite some time now). Discriminant validity is a measure of the quality of a measurement instrument; the instrument itself is typically a set of question-statements. A measurement instrument has good discriminant validity if the question-statements (or other measures) associated with each latent variable are not confused by the respondents, in terms of their meaning, with the question-statements associated with other latent variables.
Discriminant validity coefficients (extended set). The HTMT ratios are provided along with other coefficients that are useful for discriminant validity assessment, in one single combined set of outputs. These other coefficients are correlations among latent variables and square roots of AVEs, structure loadings and cross-loadings, and full collinearity VIFs. For the HTMT ratios, the following coefficients are also provided: P values, and 90% confidence intervals.
There is a short video that illustrates the discriminant validity coefficients (extended set) ().
Graphical user interface optimization. Several elements of the graphical user interface, such as screens and warning messages, have been optimized so that users can perform SEM analysis tasks with only a few clicks – and in a straightforward fashion. For example, automatic re-analyses are now conducted whenever any of the several SEM analysis settings are changed, with the results becoming immediately available to users. Also, new menu options are now available to facilitate tasks; e.g., users can now open or create a project through the “Open or create project (Step 1)” menu option available under the “Project” menu option. This new “Open or create project (Step 1)” option allows users to open or create a project file, providing an alternative path for executing Step 1.
Fractional splits for 2D moderating effects graphs. Users can now set “fractional” splits for 2D moderating effects graphs, through a new “Split” menu option. The default is 0.5, which splits the sample in the middle when drawing the lines for the effects and the “low” and “high” values of the moderating variable. For instance, if you set the fractional split to 0.1, the software splits the sample in 10% (of the sample) to the left and 90% to the right, respectively for the “low” and “high” values of the moderating variable. This new and powerful fractional split feature enables users to significantly expand their options for illustrating moderating effects in 2D graphs. In the previous version of the software the split was set at 0.5 (i.e., in the middle), with no way to modify it.
There is a short video that illustrates the fractional splits for 2D moderating effects graphs ().
New moderating effects calculation options. Users can now choose among three options for moderating effects calculation: “Two Stages”, “Variable Orthogonalization”, and “Indicator Products”. This is done through the new “View or change moderating effects settings” menu option, under the “Settings” menu option on the software’s main window. The default moderating effects calculation option is “Two Stages”, whereby latent variable scores are calculated first and then used in a second stage for the creation of the interaction variable that implements the moderating effect. The “Variable Orthogonalization” option implements a similar procedure, but stochastically departs from a random variable, which is fully orthogonal to the latent variables in the model, for the creation of the interaction variable that implements the moderating effect. The “Indicator Products” option employs indicator products for the creation of the interaction variable that implements the moderating effect; this was the only option available in the previous version of the software.
There is a short video that illustrates the new moderating effects calculation options ().
Incremental code optimization. This is conducted in each new version of this software. At several points the code was optimized for speed, stability, and coefficient estimation precision. This led to incremental gains in speed even as a number of new features were added. Several of these new features required new and complex calculations, mostly to generate coefficients that were not available before.
Enjoy!
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