All Tutorials can be viewed or downloaded. Select the name of the desired software package to view the tutorials that are available for that package.
Tutorial 1: Using Latent GOLD® to Estimate LC Cluster Models
Tutorial 2: Using Latent GOLD® to Estimate DFactor Models
Tutorial 3: LC Regression with Repeated Measures
Tutorial 3A: Using Latent GOLD® 5.0 with Holdout Records
Tutorial 4: Profiling LC Segments using the CHAID Option
Tutorial 7A: Latent Class Growth Model
Tutorial 7B: Latent Class Growth Model Using an Active Covariate
Tutorial 8: LC Regression with High-dimensional Data
Step-3 Tutorial #1: Step-3 models with covariates, distal outcomes, and multiple latent variables
Step-3 Tutorial #2: Obtaining equations for scoring new cases in a basic example with main affects
Tutorial 1: Using LG Choice 4.5 to Estimate Discrete Choice Models
Tutorial 1A: Using CHAID to Profile Latent Class Segments
Tutorial 2: Using LG Choice to Predict Future Choices
Tutorial 3: Estimating Brand and Price Effects
Tutorial 3A: Using Random Regret Models to Analyze Brand and Price Effects
Tutorial 4: Using the 1-file Format
Tutorial 5: Analyzing Ranking Data
Tutorial 7: LC Segmentation with Ratings-based Conjoint Data
Tutorial 7A: LC Segmentation with Ratings-based Conjoint Data
Tutorial 8A: Analyzing MaxDiff Data with Scale Factors (3-file)
Tutorial 8B: Analyzing MaxDiff Data with Scale Factors (1-file)
Tutorial 8C: Analyzing MaxDiff Data with Latent Class Trees (3-file)
Tutorial 10A: Estimate Scale-Adjusted Latent Class (SALC) Models (3-file)
Tutorial 10B: Estimate Scale-Adjusted Latent Class (SALC) Models (1-file)
Tutorial 11A: Estimate sCFactor Scale Adjusted Latent Class (SALC) Model (3-file)
Advanced Tutorial: Latent GOLD 4.5 and IRT Modeling
Tutorial 1: Getting Started with LG-Syntax
Tutorial 2: Scoring with LG-Syntax
Markov Tutorial #1: Latent GOLD Longitudinal Analysis of Brand Loyalty
Markov Tutorial #2: Latent GOLD Longitudinal Analysis of Life Satisfaction
Markov Tutorial #3: Latent GOLD Longitudinal Analysis of Sparse Data
Tutorial 1: Getting Started with Correlated Component Regression (CCR) in CORExpress
Tutorial 2: CCR for a Continuous Dependent Variable with Many Predictors
Tutorial 3: Correlated Component Regression for a Dichotomous Dependent Variable
Tutorial 4: Obtaining Predictions from a 2-class Regression
Tutorial 5: Prediction with Near Infrared (NIR) Data
Tutorial 6: Estimation of Naive Bayes and Extended Naive Bayes Models (forthcoming)
Tutorial 1: Beginning a CHAID Analysis
Tutorial 2: Using SI-CHAID to identify profitable segments
Tutorial 3: Using SI-CHAID with a Hold-out Sample
Tutorial 4: Using CHAID with Multiple Correlated Dependent Variables