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MaxDiff Analysis in Displayr
MaxDiff Analysis in Displayr
MaxDiff Analysis in Displayr

About the Course

Course Progress
Not started
Enroll
Course Outline
  1. Introduction
    1. Course overview
    2. Course outline
    3. What you need
  2. Setting Up Your MaxDiff Project
    1. Preparing your workspace
    2. Preparing the data
    3. Creating the experimental design
    4. Types of MaxDiff analyses
  3. Counts Analysis
    1. Counts analysis overview
    2. When to use counting analysis
    3. Benefits and limitations of counts analysis
    4. Counts analysis in Displayr (Exercise)
    5. Interpreting the output
  4. Ranking Experiments
    1. Ranking experiments overview
    2. When to use ranking experiments
    3. Benefits and limitations
    4. Ranking experiment data format
    5. Exploring the data
    6. Setting up the ranking experiment
    7. Interpreting the output
  5. Hierarchical Bayes Analysis
    1. Hierarchical bayes overview
    2. When to use hierarchical bayes
    3. Benefits and limitations of HBA
    4. Exploring the data
    5. The experimental design
    6. Setting up the HBA analysis
    7. Checking convergence
    8. Interpreting the output
    9. HBA preference shares
  6. Latent Class Analysis
    1. Latent class analysis overview
    2. When to use LCA
    3. Benefits and limitations of LCA
    4. LCA inputs and options
    5. Evaluating the model
    6. Interpreting the output
    7. LCA outputs
    8. Preference simulation
  7. Choosing the Right Model
    1. LCA vs. HBA
    2. Trade-offs in model selection
    3. Prediction accuracies
    4. When to use each approach
  8. Test Your Knowledge
    1. Module Quiz
course
MaxDiff Analysis in Displayr
MaxDiff Analysis in Displayr
Course Progress
Not started
Enroll

About the Course

Course Outline
  1. Introduction
    1. Course overview
    2. Course outline
    3. What you need
  2. Setting Up Your MaxDiff Project
    1. Preparing your workspace
    2. Preparing the data
    3. Creating the experimental design
    4. Types of MaxDiff analyses
  3. Counts Analysis
    1. Counts analysis overview
    2. When to use counting analysis
    3. Benefits and limitations of counts analysis
    4. Counts analysis in Displayr (Exercise)
    5. Interpreting the output
  4. Ranking Experiments
    1. Ranking experiments overview
    2. When to use ranking experiments
    3. Benefits and limitations
    4. Ranking experiment data format
    5. Exploring the data
    6. Setting up the ranking experiment
    7. Interpreting the output
  5. Hierarchical Bayes Analysis
    1. Hierarchical bayes overview
    2. When to use hierarchical bayes
    3. Benefits and limitations of HBA
    4. Exploring the data
    5. The experimental design
    6. Setting up the HBA analysis
    7. Checking convergence
    8. Interpreting the output
    9. HBA preference shares
  6. Latent Class Analysis
    1. Latent class analysis overview
    2. When to use LCA
    3. Benefits and limitations of LCA
    4. LCA inputs and options
    5. Evaluating the model
    6. Interpreting the output
    7. LCA outputs
    8. Preference simulation
  7. Choosing the Right Model
    1. LCA vs. HBA
    2. Trade-offs in model selection
    3. Prediction accuracies
    4. When to use each approach
  8. Test Your Knowledge
    1. Module Quiz