SmartPLS Algorithms and Techniques
- Blindfolding
- Bootstrapping
- Confirmatory Composite Analysis (CCA)
- Confirmatory Tetrad Analysis in PLS (CTA-PLS)
- Consistent Bootstrapping
- Consistent PLS-SEM
- Discriminant Validity Assessment and Heterotrait-monotrait Ratio of Correlations (HTMT)
- Goodness of Fit (GoF)
- Finite Mixture Partial Least Squares (FIMIX-PLS)
- Higher-order Models
- Importance-Performance Map Analysis (IPMA)
- Permutation
- Mediation
- Measurement Invariance Assessment (MICOM)
- Model Fit
- Moderation
- Multigroup Analysis (MGA)
- PLS Prediction-oriented Segmentation (PLS-POS)
- Nonlinear
- PLS-SEM Algorithm
- PLSpredict
- PLS-SEM and Bootstrapping Problems
- Prediction-oriented model selection
- Weighted PLS Algorithm (WPLS)
- endogeneity
- Regression
- NCA
- Regression
Other SmartPLS Functionalities
- Increase main memory assigned to SmartPLS
- Change Colors and Customize Styles
- Choose Your Language
- Composite, Common Factor and Mixed Models
- Copy & Paste vs. Duplicate
- Data Import
- Export Your SmartPLS Project
- How to Interpret Excess Kurtosis and Skewness
- Import Project from a Folder
- Import Project from Backup File
- Missing Values
- Outer Weights Initialization and Pre-specification
- Transfer SmartPLS Projects to Another Computer
- Workspace
- Comments in the modeling window
- Internet connection