2022/23 Taught Postgraduate Module Catalogue
TRAN5282M Choice Modelling and Stated Preference Survey Design
15 creditsClass Size: 50
Module manager: Stephane Hess
Taught: Semester 2 (Jan to Jun) View Timetable
Year running 2022/23
Module replaces5281M Stated Preference Analysis Methods
This module is not approved as an Elective
Module summaryChoice modelling techniques are used widely to produce insights into choice behaviour, often with a view to providing guidance to policy makers, e.g. as an input to cost-benefit analyses. The models can be estimated either on data containing real observed choices, or data collected in hypothetical choice scenarios. The latter approach, known as stated preference data, is widespread and an appealing solution in cases where data on real choices are difficult to obtain, for example when looking at behaviour in the presence of a new transport mode. This course covers the essential principles involved in the specification, estimation and interpretation of choice models, covering topics from basic structures right through to state-of-the-art techniques. Similarly, the course covers different available techniques for generating designs for stated preference surveys, and also addresses the topics of data collection.The course involves a mix of lectures and practicals, providing extensive hands-on experience with model estimation as well as survey design.
ObjectivesTo provide a thorough grounding in choice modelling and stated preference survey design.
1. Understand the basics of experimental design
2. Understand the theory behind the development and application of choice models
3. Be able to create experimental designs using NGene
4. Be able to analyse choice modelling data using Apollo
5. Be able to justify the decisions made in survey design and model specification
6. Be able to interpret model outputs
Random utility theory; multinomial logit model; nested logit; cross-nested logit; mixed logit; model specification; model estimation; interpretation of results; joint RP-SP estimation; model application; forecasting
Orthogonal design; design testing; efficient design; dealing with respondent issues including strategic bias and non-trading
|Delivery type||Number||Length hours||Student hours|
|Private study hours||115.00|
|Total Contact hours||35.00|
|Total hours (100hr per 10 credits)||150.00|
Opportunities for Formative Feedback- The coursework for this module consists of two parts, designing a stated preference survey, and then analysing data that the module leader provides to the student
- Students are given an opportunity of feedback on a preliminary design one week after receiving the coursework instructions, in one-on-one sessions or via e-mail/phone.
- The actual design received by the module leader as the first deliverable presents another opportunity for monitoring, ahead of the student conducting the analysis and writing a report.
- Written feedback on the report is provided.
Methods of assessment
|Assessment type||Notes||% of formal assessment|
|Report||5,000 words due six weeks after the course ends||100.00|
|Total percentage (Assessment Coursework)||100.00|
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Reading listThe reading list is available from the Library website
Last updated: 29/04/2022 15:39:42
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