SmartPLS 4.1.1.8: Advanced PLS-SEM Statistical Analysis Software
SmartPLS 4.1.1.8 is the latest version of the industry-leading software for Partial Least Squares Structural Equation Modeling (PLS-SEM). Released on March 1, 2026, this update introduces significant methodological advancements including importance-performance map analysis (IMPA) for linear regression and effect size sensitivity analysis for necessary condition analysis (NCA-ESSE) .
Key New Features in Version 4.1.1.8
| Feature | Description |
|---|---|
| Importance-Performance Map Analysis (IMPA) | Integrated IMPA for linear regression models, enabling researchers to identify factors with high importance but low performance for strategic prioritization |
| NCA Effect Size Sensitivity Analysis (NCA-ESSE) | Added effect size sensitivity analysis for necessary condition analysis, enhancing robustness assessment of necessary conditions |
| Enhanced NCA Permutation Display | Improved handling and clear presentation of N/A values in permutation results |
| Automated Deployment Support | Fixed console and unattended modes for Windows installers, enabling seamless automated deployments in enterprise environments |
Core Capabilities
PLS-SEM (Partial Least Squares)
-
Path Modeling: Comprehensive structural equation modeling with latent variables
-
Bootstrapping: Significance testing with customizable resampling
-
Blindfolding: Out-of-sample prediction for cross-validated redundancy
-
Importance-Performance Map Analysis (IPMA): Identify areas for strategic improvement
-
Moderation Analysis: Single, two-way, and three-way moderation effects
-
Mediation Analysis: Specific, total, and conditional indirect effects
CB-SEM (Covariance-Based SEM)
-
Model Estimation: Maximum likelihood and generalized least squares
-
Multigroup Analysis (MGA): Compare path coefficients across groups
-
Measurement Invariance Assessment: Verify comparability across groups
-
Model Comparison: Statistically compare competing models
Advanced Methods
-
GSCA (Generalized Structured Component Analysis): Alternative to PLS-SEM with bootstrapping and Gaussian copulas
-
Necessary Condition Analysis (NCA): Identify bottleneck conditions required for desired outcomes
-
Gaussian Copula: Address endogeneity issues in PLS-SEM and regression models
-
PLS-Predict & CVPAT: Out-of-sample prediction and model comparison
-
FIMIX-PLS: Finite mixture segmentation for unobserved heterogeneity
-
POS (Prediction-Oriented Segmentation): Identify heterogeneous groups based on prediction quality
Data Preparation Tools
-
Indicator Transformation: Recode, rescale, combine, or split indicators directly within software
-
Missing Value Handling: Mean replacement, casewise deletion, pairwise deletion
-
Data Import: CSV, Excel, TXT formats with automatic column detection

