Choice Modeling and Categorical Data Analysis

Course Objective
To provide a strong foundation in categorical data analysis and choice modeling. It covers a thorough discussion of the widely used qualitative data models and their demonstration using industry analogous data sets.

Learning Outcomes

Upon completion of this course, students will be able to

Extract useful information from qualitative/categorical data sets

Use appropriate modeling tools for qualitative/categorical data.

Detailed Syllabus

  1. Introduction: Increasing importance of choice modelling and categorical data analysis
  2. Distributions and Inference for Qualitative Data
  3. Describing Contingency Tables, Inference for Contingency Tables
  4. Introduction to Generalized Linear Models, Logistic Regression, Building and Applying Logistic Regression Models, Logit Models for Multinomial Responses, Loglinear Models for Contingency Tables
  5. Building and Extending Log linear Logit Models
  6. Models for Matched Pairs, Analyzing Repeated Categorical Response Data
  7. Random Effects: Generalized Linear Mixed Models for Categorical Responses
  8. Other Mixture Models for Categorical Data