CPD

We run two annual courses for fee-paying delegates, a winter course on choice modelling and stated choice design and a summer course on advanced choice modelling. Both courses use the Apollo package in R for model coding and estimation. Full details of this are given below. In addition, we offer tailor-made courses on choice modelling and/or stated preference design. We are flexible in terms of timing and deliver these courses worldwide. Recent examples include a course on stated preference design run at the National Cheng Kung University, Taiwan and a course on choice modelling run in Singapore. For more details, please contact us.

You can now book onto our 2022 course.

The courses will be held in Leeds this year.  Lectures allow ample time to ask questions. Tutorials consist of exercises in Apollo and Ngene.

Please see below for details.

1. Advanced choice modelling course (Summer)

Advanced choice modelling course

Leeds course, 4-6 July 2022

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.

This course will be held as an in-person course at the University of Leeds. We will also allow online participation via livestreaming, but for the best experience, we recommend in person attendance. Taught by experts from the University of Leeds, the course will consist of a mixture of lectures, computer practicals (using the Apollo package in 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.

Course instructors

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 the author of Apollo (with David Palma) and is also the editor-in-chief of the Journal of Choice Modelling.

 

Dr Thijs Dekker is an Associate Professor at the Institute for Transport Studies at the University of Leeds. He is an expert in analysing advanced discrete choice models with a particular interest in alternative estimation techniques. He has many methodological contributions and experience in both the fields of transport and environmental economics.

 

Fee structure

Before 30 April 2022 After 30 April 2022
Full registration fee: £1,050 £1,200
Full time academics: £775 £905
Research students: £650 £800

To register please go to 0722ACMC3 Advanced Choice Modelling Course | University of Leeds

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

A 10% discount is applied to these rates for delegates who attended our introductory winter course. 

Host organisation

The Choice Modelling Centre (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.

Venue

Institute for Transport Studies, University of Leeds

Outline programme for the course

Day 1 (July 4th): 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 (July 5th): 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 (July 6th): Bayesian Estimation – Bayesian estimation in R – Moving beyond discrete choice – MDCEV in R

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

 

2. Choice Modelling and Survey Design (Winter)

Course in choice modelling and
stated choice survey design

Leeds course, 28 Nov- 2 Dec 2022

This five day course, run by the Choice Modelling Centre (CMC) at the University of Leeds, will provide delegates with an in-depth introduction to basic and advanced choice modelling and stated choice survey design.

Taught by experts from the University of Leeds and the University of Sydney Business School, the course will consist of a mixture of lectures, computer practicals (using Ngene and the Apollo package in 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 choice modelling analyses, from inception via survey design and data collection to modelling, analysis, interpretation and implementation.

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.

Course instructors

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, and a joint developer of Apollo.

 

Professor Michiel Bliemer  is an external affiliate of the Choice Modelling Centre. He works at the Institute of Transport and Logistics Studies at the University of Sydney and is also active as a consultant and joint Director of ChoiceMetrics, the company that develops the Ngene software for generating efficient experimental designs. Michiel is an expert in the design of stated choice experiments and has made many methodological contributions in this area. Further, he is an associate editor of the Journal of Choice Modelling.

 

Fee structure

Before 15 October 2022 After 15 October 2022
Full registration fee: £1,800 £2,050
Full time academics: £1,300 £1,550
Research students: £1,100 £1,350

To register please go to 1122CMC5 Choice Modelling & Stated Choice Survey | University of Leeds

To be announced shortly. Registrations details also to follow.

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

Host organisation

The Choice Modelling Centre (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.

Venue

Institute for Transport Studies, University of Leeds

Outline programme for the course

Day 1: Introduction to choice modelling and data requirement; The Multinomial Logit model and estimation; Introduction to estimation of choice models in R; Specification testing and further examples in R.

Day 2: Introduction to stated choice surveys; Nested Logit and other GEV models; Estimation on multiple data sources

Day 3: Survey examples, fractional factorial and orthogonal designs; Computer exercises with experimental design software (Ngene), generating orthogonal designs; Mixed Logit.

Day 4: From design to survey; Drawbacks of orthogonal designs; Efficient designs; Generating efficient designs; Discrete mixtures and latent class models.

Day 5: Bayesian efficient designs; Advanced designs; Alternatives to Random Utility models; Hybrid model structures.