SmartPLS 3.2.9 Lifetime License

RM70.00

SmartPLS is a software with graphical user interface for variance-based structural equation modeling (SEM) using the partial least squares (PLS) path modeling method.[1][2][3][4][5] 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 3.2.9, released 2020-01-08

  • Feature: Descriptive statistics for latent variable scores, residuals, and prediction errors
  • Feature: Preferences option to hide leading zeros in the results output
  • Feature: Implementation of consistent PLS-MGA and permutation
  • Localization: Translation to Urdu
  • Localization: Update of the existing language versions
  • Improved: Added specific indirect effects to the PLS-MGA and permutation results
  • Improved: PLS-MGA two-tailed p-values
  • Improved: Added intercepts for unstandardized coefficients IPMA results
  • Improved: Software speed and performance
  • Improved: Blindfolding missing data treatment (i.e., it does not support pairwise deletion anymore)
  • Improved: Added construct level results (e.g., R²) in the modeling window of bootstrapping
  • Improved: Descriptive statistics for indicator data (e.g., group-specific outcomes)
  • Improved: Excel export of results
  • Fixed: PLSpredict LV predictions
  • Fixed: Changing the sort order in the result tables (e.g., by variable name)
  • Fixed: Pairwise deletion to treat missing values
  • Fixed: Highlighting of p-values for PLS-MGA results
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