1124CMC5 Choice Modelling & Stated Choice Survey

Event Location

Contact

Stephane Hess

[email protected]

More Information

After taking this course, the participant will be able to design a stated choice survey, analyse stated or revealed choice data by estimating widely used discrete choice models, and interpret behavioural results. By letting participants do hands-on exercises with popular software, they will become familiar with the theories and models, which adds greatly to the learning experience. This makes the course suitable for practitioners who would like to get a good introduction and are interested in applications, as well as experienced academics who are interested in learning more advanced methods in design and analysis.

For further details and to register, please follow this link 

Professor Stephane Hess is the director of CMC and Professor of Choice Modelling at the University of Leeds. He is an expert in developing advanced choice models and analysing choice behaviour, with theoretical and empirical contributions across different fields. He is also the editor-in-chief of the Journal of Choice Modelling.

Professor Michiel Bliemer is Professor of Transport and Logistics Network Modelling at the University of Sydney Business School. He is an expert in the design of stated choice surveys and has made many methodological contributions in this area. Further he is joint developer of the widely used Ngene software for generating efficient experimental designs.

Host organisations
The Centre for Choice Modelling (CMC) at the University of Leeds is a large multi-disciplinary centre bringing together expertise in choice modelling and the study of human decision making from across different fields. The course is co-hosted by the Institute for Transport Studies in the Faculty of Environment at the University of Leeds and the Institute of Transport and Logistics Studies in the University of Sydney Business School. Both have global reputations for state-of-the-art research in choice modelling, discrete choice analysis and experimental design.

Outline programme for the course
Day 1: Introduction to choice modelling and data requirement; Multinomial Logit estimation; Specification testing; Analysis and interpretation of results; Computer exercises with estimation software (R)
Day 2: Models with flexible error structures: Nested Logit; Mixed Logit; Latent Class; Computer exercises with estimation software (R)
Day 3: Alternatives to Random Utility models including Random Regret; Hybrid choice models; Emerging data sources for choice modelling; Computer exercises with estimation software (R)
Day 4: Introduction to stated choice surveys and experimental design; Full and fractional factorial designs; Orthogonal designs and their drawbacks; Survey formatting; Computer exercises with experimental design software (Ngene)
Day 5: Efficient experimental designs; Bayesian efficient designs; Advanced designs; Computer exercises with experimental design software (Ngene)

All fees include access to software and data for the course.

Cancellation options:
• More than 2 months in advance: 50% refund
• More than 1 month in advance: 25% refund
• Less than 1 month in advance: no refund