Advanced Analyses
Regression, MaxDiff, Choice Modeling, and more.
Choice Modeling
Advanced Methods
Dimension Reduction
- Dimension Reduction - t-SNE
- Dimension Reduction - Principal Components Analysis
- Dimension Reduction - Multidimensional Scaling (MDS)
- Dimension Reduction - Diagnostic - Moonplot
- Dimension Reduction - Diagnostic - Goodness of Fit Plot
- Dimension Reduction - Diagnostic - Component Plot
Segmentation
- Latent Class Analysis
- Analyzing other data by Groups/Segments
- The difference between Trees, CHAID, CART and other tree-based models
- Two Step Cluster
- Model-Based Cluster Analysis
- Latent Class Analysis and Mixture Models
Regression
- Binary Logit
- Driver (Importance) Analysis
- Linear Regression
- Multicollinearity
- Multinomial Logistic Discriminant Analysis
- Multinomial Logit Regression
MaxDiff
- MaxDiff Technical Resources
- Advanced MaxDiff Experimental Designs
- Analyzing MaxDiff Using Standard Logit Models
- Analyzing MaxDiff Using the Rank-Ordered Logit Models With Ties
- Anchored MaxDiff
- Marketing - MaxDiff - Diagnostic - Parameter Statistics Table
Text Analysis
- Text Analysis - Semi-Automatic Categorization - Mutually Exclusive Categories - Reuse by Sharing
- Text Analysis - Word Cloud
- Text Analysis - Semi-Automatic Categorization - Mutually Exclusive Categories - New
- Text Analysis - Semi-Automatic Categorization - Mutually Exclusive Categories - New
- Text Analysis - Semi-Automatic Categorization - Multiple Overlapping Categories - Reuse by Copying
- Text Analysis - Semi-Automatic Categorization - Multiple Overlapping Categories - New
Machine Learning
- Machine Learning - Diagnostic - Model Simulator extension (Typing Tool)
- Mixed-Mode Tree Analysis
- Machine Learning - Save Variable(s) - Probabilities of Each Response
- Machine Learning - Save Variables - Predicted Values
- Machine Learning - Save Variable(s) - Discriminant Variables
- Machine Learning - Ensemble of Models