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Subject:

Advanced choice modelling course, London 25-27 June 2018

From:

Stephane Hess <[log in to unmask]>

Reply-To:

Stephane Hess <[log in to unmask]>

Date:

Tue, 6 Feb 2018 07:50:50 +0000

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Advanced choice modelling course 

London, United Kingdom, 25-27 June 2018

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. The course will take place in central London (De Vere West One, 9-10 Portland Pl, Marylebone, London W1B 1PR).

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.

Please book early to avoid disappointment as spaces are limited and the 2017 course sold out quickly.

For further details, please go to http://www.cmc.leeds.ac.uk/courses-phds/cpd/

Book your place at: http://store.leeds.ac.uk/conferences-and-events/environment/institute-of-transport-studies/advanced-choice-modelling-course-june-2018

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.		

Dr Thijs Dekker is Lecturer in Transport Economics 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 1 May 2018	After 1 May 2018
Full registration fee:	£1150			£1,300
Full time academics:	£825			       £975
Research students:	£675			      £825

Fees include three lunches, one evening dinner and 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 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. 

Outline programme for the course

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

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