top of page
Taking notes at coffee time_edited_edited_edited.jpg

COURSE PROGRAM

Each week consists of a 3.5 hour live online session, plus a series of pre-recorded videos that explain key concepts/theories and demonstrate widely used software tools in choice modelling. Students are also given exercises to complete in their own time each week. It is strongly recommended to reserve half a day each week to watch these videos, practice with software, and work on exercises.

 

Delegates will receive installation instructions and temporary licences (where needed)

for the following software tools:

 

• Apollo for estimating choice models

• Ngene for generating choice experimental designs

• SurveyEngine for creating online questionnaires and choice experiments

WEEK 1: INTRODUCTION TO CHOICE MODELLING

  • Introduction to key concepts

  • A guide to: Planning a choice study

  • Case studies: study plan

  • Decision rules

  • The multinomial logit model

WEEK 2: CHOICE DATA COLLECTION

  • Stated and revealed preference data

  • A guide to: Data collection

  • Creating questionnaires

  • Case study: revealed preference data collection

  • Case study: stated preference data collection

WEEK 3: CHOICE MODEL SPECIFICATION AND ESTIMATION

  • A guide to: Model building

  • Formulating utility functions

  • Model estimation and outputs

  • Model comparison

  • Case study: model specification and estimation

WEEK 4: INTERPRETATION OF OUTPUTS AND MODEL APPLICATION

  • Attribute importance

  • Willingness-to-pay and other marginal rates of substitution

  • Predictions and elasticities

  • Determining precision of derived measures of interest

  • Case study: model interpretation and application

WEEK 5: DESIGNING CHOICE EXPERIMENTS

  • A guide to: Experimental design

  • Orthogonal designs

  • Efficient designs

  • Bayesian efficient designs

  • Case study: experimental design

WEEK 6: OTHER CHOICE MODELLING CONSIDERATIONS

  • Willingness-to-pay space models

  • Nested logit and other GEV models

  • Joint estimation

  • Heteroskedastic choice models

  • Case study

WEEK 7: ACCOUNTING FOR RANDOM PREFERENCE HETEROGENEITY

  • Heterogeneity: an overview

  • Latent class analysis

  • Mixed logit

  • Marginal rates of substitution with random heterogeneity

  • Case study: random preference heterogeneity

WEEK 8: ADVANCED CHOICE MODELLING AND EXPERIMENTAL DESIGN

  • Advanced experimental designs

  • Posterior analysis

  • Hybrid choice models

  • Discrete-continuous choice models

  • Q&A and feedback

bottom of page