Online Course: Understanding and Predicting Choice Behaviour in Health: Preference Elicitation and Analysis
Next Course Dates: 04, 05, 06, 12 & 13 October - 8am-11am UK BST each morning
WHAT THE COURSE IS ABOUT
Methods for understanding how choices are applied in health care to assess preferences, analyse policies, help to develop randomised controlled trials, conduct non-market valuation, and forecast behaviour. This course teaches introductory methods for devising experiments and modelling choice data in health care.
Increasingly, health researchers need to understand decision-making in a wide range of health settings. For example, what drives smokers to choose cigarettes or e-cigarettes? What is a realistic non-inferiority margin to use in my clinical trial? How does society value different aspects of quality of life? What drives individuals to take, or refuse, vaccines? What kind of people prefer drug A over drug B?
Whether data are generated in experiments, such as discrete choice experiments, or are taken from recording individuals’ real-world behaviour, choice models are needed to understand these behaviours. The course provides the tools for understanding health-based choice behaviour, an introduction to choice experiments, and an introduction to choice modelling.
Lectures and worked examples that form part of the course enable participants to learn and apply these techniques.
WHO THE COURSE IS FOR
The course is designed for those who need to perform discrete choice analysis in healthcare and those who need to understand the issues that health researchers face when performing these analyses. This could include researchers and decision makers from public, commercial, and academic organisations concerned with understanding health preferences. We welcome participants from a wide variety of organisations and from all over the world. If you are unsure as to whether the course is suitable for you, please email firstname.lastname@example.org who will be happy to advise.
There are no formal prerequisites for attendance, but participants should have some understanding of basic statistics and regression techniques, including multinomial logistic regression. Choice modelling will be conducted using R (using the Apollo package for choice models), and some familiarity with R software is advised. Ngene software will be used for experimental design, though no prior experience is required.
We also strongly recommend that you have access to two screens for the duration of the course: one to watch the presentations and the other to view the materials.
AIMS OF THE COURSE
• To provide detailed study of the methods of discrete choice analysis for health care
• To provide introduction to the theory and application of discrete choice experiments in health care
• To provide introduction to the theory and application of discrete choice models in health care
• To give participants experience of computer-based application with worked-through exercises and feedback sessions
The course will consist of five LIVE tutorial sessions and will not be recorded. Therefore, to gain the maximum benefit, please ensure you are able to attend the live sessions. Live sessions will last for 4 hours each. Live sessions include lectures for course materials, and live coding of models and experimental designs.
The five taught sessions will cover the following topics:
- Introduction to choice models, data types, and analysing preferences in health
- Model specification, estimation, post-estimation analyses, and interpretation
- Experimental design and case studies in health
- Heterogeneity part (i): deterministic and random tastes
- Heterogeneity part (ii): attitudes
Each tutorial session is followed by a question and answer session.
This course is taught in English and a certificate of participation will be issued post course.
Note: Some of the exercises require the use of Ngene software.
Note: Places on the course are limited. Book early to avoid disappointment.
For booking enquiries, please contact the HERC Administration team at email@example.com
This course usually consists of five half-day live taught sessions and was last held in January 2023. To be placed on a waiting list for a future course, please visit https://oxford.onlinesurveys.ac.uk/waiting-list-for-herc-short-courses-2023
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 John Buckell is a senior researcher in health economics at the Health Economics Research Centre at the University of Oxford. He has worked on choice models in health markets including tobacco, obesity, and genomics. He has made methodological and policy making contributions in health
Thomas Hancock is a Research Fellow at CMC, University of Leeds. His main research interests are understanding the decision-making process, the integration of (econometric) choice modelling and mathematical psychology, model specification and interpretation, and moral choice behaviour. His work thus far has focussed on the implementation of decision field theory and ideas from quantum cognition within choice modelling.