Course Level: Intermediate
Format Requirements: This workshop will use both lectures and hands-on exercises. It will start with an overview of the theory underpinning the conjoint analysis, which will be followed by a review of the methods necessary to successfully navigate a application relevant to medical decision making. Particular attention will be given to the basic aspects of setting up a conjoint analysis, from defining the research question, construction of choice tasks and data-analysis. Participants will be given various practical exercises to obtain hands-on experience with these basic issues. Participants are encouraged to bring personal computers, but are not required to do so. This workshop is intended for researchers who have a working knowledge of statistics and health outcomes research, and who are interested in developing patient-focused preference-based values of health outcomes that can be used to inform health policy. Some knowledge or experience of conjoint analysis/discrete choice experiments would be advantageous.
Background: The application of stated preference methods, including conjoint analysis and discrete choice experiments has rapidly increased in recent years as a theory driven approach to measure the preferences of patient and other stakeholders. Researchers have also used these methods to understand or facilitate medical decision making both at the individual doctor-patient dyad and at the national level (e.g. through quantitative benefit-risk analysis).
Description and Objectives: This workshop will provide participants with the basic conceptual and practical background necessary to understand, evaluate, and interpret a conjoint analysis applied to a variety of medical decision making problems. The course will be built around current best practices (Bridges et al, 2011), and as such will lead participants through the elements of i) defining the research question; ii) specifying the attributes and levels; iii) constructing the choice tasks; iv) experimental design to construct hypothetical stimuli; v) preference elicitation format; vi) instrument design; vii) data collection plan; viii) statistical analyses; ix) results and conclusions; and x) study presentation.
By the end of this course participants will:
- Gain practical experience in calculating welfare estimates that can be used in formal technology assessment, including the calculation of willingness to pay measures used in cost benefit analysis;
- Become familiar with the history of conjoint analysis and gain an understanding of the theory underpinning the approach;
- Gain a practical grounding in the necessary steps for conducting conjoint analysis, including more advanced topics associated with experimental design and statistical estimation.