Advanced Choice Modelling

This three day course, run by the Choice Modelling Centre (CMC) at the University of Leeds, will provide delegates with in-depth insights into the estimation of advanced choice models. The course is a continuation of our annual winter course on ‘Choice modelling and stated choice survey design’ and assumes participants have the ability to estimate basic choice models, including the mixed logit model.

Taught by experts from the University of Leeds, the course will consist of a mixture of lectures, computer practicals (using R), and detailed case studies. Bringing together expertise from fields as diverse as transport, health, marketing and environmental economics, the course will cover all the steps required for successful estimation of flexible Mixed Logit and hybrid choice models, the implementation and interpretation of the Expectations Maximisation algorithm and Bayesian estimation procedures, and an introduction to models of multiple and continuous choice.

After taking this course, participants will be able to estimate and contrast state-of-the-art models, understand the properties and recognise limitations of maximum likelihood estimation and use alternative estimation techniques best suited for their particular research question and dataset. By conducting hands-on exercises with open source software, participants will become familiar with the theories and models, which adds greatly to the learning experience.

Delegates are expected to bring their own laptops. We will have a limited number of laptops available for rental for the duration of the course. Delegates need to book these when registering for the course.

Designed for people in the industry, these courses will develop up-to-date skills and knowledge for all transport professionals. Short courses are taught by active research staff and teachers, with external experts contributing, and are normally held at the Institute for Transport Studies. Alternate arrangements can be made to bring a course closer to you. All courses can be tailor-made to your company’s particular needs. Please get in touch to discuss bespoke course options.

Day 1: Introduction to estimation in R: MNL and basic Mixed Logit – Advanced Mixed Logit topics: distributions, correlations, estimation, WTP, posterior analysis            – Advanced Mixed Logit topics in R – Alternative decision rules – Hybrid Choice Models (theory & application issues)

Day 2: Estimation of Hybrid Choice Models in R – Local optima, alternative estimation routines, advanced diagnostics, error calculations – Advanced estimation routines and diagnostics in R

Day 3: Bayesian Estimation – Bayesian estimation in R – Moving beyond discrete choice – MDCEV in R

Please follow this link to find out about costs and to book on to this course https://cmc.leeds.ac.uk/courses-phds/cpd/

De Vere West One, 9-10 Portland Pl, London W1B 1PR

Institute for Transport Studies
Leeds LS2 9JT
Email: cpd@its.leeds.ac.uk