Postgraduate taught 

One Health & Infectious Disease MSc/PgDip/PgCert: Online distance learning

Choice experiments for health economics, HTA and one health MED5641

  • Academic Session: 2023-24
  • School: School of Health and Wellbeing
  • Credits: 10
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 2
  • Available to Visiting Students: Yes
  • Taught Wholly by Distance Learning: Yes

Short Description

This course introduces the fundamentals of choice experiment methods and how they can be implemented as a quantitative ex ante approach to investigate people's stated preferences among alternative health-care interventions, services or policies. Choice experiments can be used within economic evaluation to value impacts and outcomes which, due to prevailing market failure, means that typical economic valuation methods such as revealed values are not possible.


This course is made up of online lectures and tutorials.

Excluded Courses





This course will be assessed by two summative assessments: a 2,000 word report (80%) and a practical skills exercise using the statistical software (20%). 

Course Aims

This course aims to foster students' understanding of the concepts and mechanisms of the choice experiment, as well as its applications in health economics, HTA and new methods in 'One Health' economics. Moreover, this module is intended to impart the basic technical knowledge and statistical software skills required for the design, implementation and analysis of choice experiments.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

1. Demonstrate a critical overview of what choice experiments are, what purposes they serve within economic evaluation and understand how they are implemented. 

2. Describe applications of choice experiments at the forefront of health, environmental and One Health economics; 

3. Identify appropriate attributes for a choice experiment in a specialised context; 

4. Conceptualise different experimental designs and their importance for statistical and behavioural efficiency objectives; 

5. Construct and arrange a choice experiment dataset which could be implemented in a real world context;

6. Critically analyse choice experiment data using conditional logit models, latent class models, mixed (random parameters) logit models, for utility and welfare analysis;

7. Interpret and effectively communicate the outputs of a choice experiment to a diverse audience;

8. Offer original insights and informed judgements regarding the outcomes of an intervention, service or policy, by applying insights from choice experiment analysis;

9. Critically evaluate the strengths and weaknesses of choice experiments as a methodology.

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.