SmartPLS 3.2.8 Lifetime License

SmartPLS is a software with graphical user interface for variance-based structural equation modeling (SEM) using the partial least squares (PLS) path modeling method. Users can estimate models with their data by using basic PLS-SEM, weighted PLS-SEM (WPLS), consistent PLS-SEM (PLSc-SEM), and sumscores regression algorithms. The software computes standard results assessment criteria (e.g., for the reflective and formative measurement models and the structural model, including the HTMT criterion, bootstrap based significance testing, PLSpredict, and goodness of fit) and it supports additional statistical analyses (e.g., confirmatory tetrad analysis, higher-order models, importance-performance map analysis, latent class segmentation, mediation, moderation, measurement invariance assessment, multigroup analysis). Since SmartPLS is programmed in Java, it can be executed and run on different computer operating systems such as Windows and Mac.

Version 3.2.8, released 2018-11-22

• Feature: Implementation of predictive model selection criteria for PLS and PLSc
• Feature: New unique case identifier (i.e., a fixed number for each observation in the dataset, which is useful, for example, when using the casewise deletion option, multigroup or segmentation analyses)
• Improved: Inclusion of all specific indirect effects for the mediator analysis
• Improved: Color highlighting of significant p-values in bootstrapping, permutation, and multigroup analysis (MGA)
• Improved: Results presentation for bootstrapped fit indices
• Improved: Software activation procedure
• Localization: Translation to Korean (100%)
• Localization: Translation to Malay (100%)
• Localization: Translation to Polish (>20%)
• Localization: Translation to Rumanian (>50%)
• Localization: Correction of incompletions and little issues in the different language translations
• Fixed: Residual correlation instead of covariance for PLSc
• Fixed: Bootstrapping sometimes stopped when using “complete bootstrapping” with repeated indicators due to problems in the fit calculation for these models
• Removed: Lohmöller’s initial weighting scheme (complexity reduction)
• Removed: Bootstrap sign change options (i.e., individual sign changes, construct level sign changes; complexity reduction)
• Removed: Double bootstrapping (increased bootstrapping performance; complexity reduction)
• Removed: d_g1 version of the exact fit measures (complexity reduction)