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Best worst discrete choice experiments in health: Methods and an application

  • Lancsar, Emily
  • Louviere, Jordan
  • Donaldson, Cam
  • Currie, Gillian
  • Burgess, Leonie

A key objective of discrete choice experiments is to obtain sufficient quantity of high quality choice data to estimate choice models to be used to explore various policy/clinically relevant issues. This paper focuses on a relatively new form of choice experiment, ‘Best Worst Discrete Choice Experiments’ (BWDCEs) and their relevance to health research as a new way to meet such an objective. We explain what BWDCEs are, how and when to apply them and we present several analytical approaches to model the resulting data. We demonstrate this preference elicitation approach in an empirical application exploring preferences of 898 members of the general public in Edmonton and Calgary, Canada for treatment of cardiac arrest occurring in a public place and show the gains achieved compared to traditional analysis of first best data. We suggest that BWDCEs are a valuable way to investigate preferences in the health sector and discuss implications for task design, analysis and areas for future research.

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Article provided by Elsevier in its journal Social Science & Medicine.

Volume (Year): 76 (2013)
Issue (Month): C ()
Pages: 74-82

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Handle: RePEc:eee:socmed:v:76:y:2013:i:c:p:74-82
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  1. Kenneth Train, 2003. "Discrete Choice Methods with Simulation," Online economics textbooks, SUNY-Oswego, Department of Economics, number emetr2, December.
  2. Kjaer, Trine & Gyrd-Hansen, Dorte, 2008. "Preference heterogeneity and choice of cardiac rehabilitation program: Results from a discrete choice experiment," Health Policy, Elsevier, vol. 85(1), pages 124-132, January.
  3. Wiktor Adamowicz & David Bunch & Trudy Cameron & Benedict Dellaert & Michael Hanneman & Michael Keane & Jordan Louviere & Robert Meyer & Thomas Steenburgh & Joffre Swait, 2008. "Behavioral frontiers in choice modeling," Marketing Letters, Springer, vol. 19(3), pages 215-228, December.
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  6. Flynn, Terry N. & Louviere, Jordan J. & Peters, Tim J. & Coast, Joanna, 2007. "Best-worst scaling: What it can do for health care research and how to do it," Journal of Health Economics, Elsevier, vol. 26(1), pages 171-189, January.
  7. Julie Ratcliffe & Leah Couzner & Terry Flynn & Michael Sawyer & Katherine Stevens & John Brazier & Leonie Burgess, 2011. "Valuing child health utility 9D health states with a young adolescent sample," Applied Health Economics and Health Policy, Springer, vol. 9(1), pages 15-27, January.
  8. Pat Auger & Timothy Devinney & Jordan Louviere, 2007. "Using Best–Worst Scaling Methodology to Investigate Consumer Ethical Beliefs Across Countries," Journal of Business Ethics, Springer, vol. 70(3), pages 299-326, February.
  9. Vermeulen, Bart & Goos, Peter & Vandebroek, Martina, 2010. "Obtaining more information from conjoint experiments by best-worst choices," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1426-1433, June.
  10. Flynn, Terry Nicholas & Louviere, Jordan J. & Peters, Tim J. & Coast, Joanna, 2010. "Using discrete choice experiments to understand preferences for quality of life. Variance-scale heterogeneity matters," Social Science & Medicine, Elsevier, vol. 70(12), pages 1957-1965, June.
  11. Potoglou, Dimitris & Burge, Peter & Flynn, Terry & Netten, Ann & Malley, Juliette & Forder, Julien & Brazier, John E., 2011. "Best-worst scaling vs. discrete choice experiments: An empirical comparison using social care data," Social Science & Medicine, Elsevier, vol. 72(10), pages 1717-1727, May.
  12. Arne Risa Hole, 2006. "Small-sample properties of tests for heteroscedasticity in the conditional logit model," Economics Bulletin, AccessEcon, vol. 3(18), pages 1-14.
  13. Mandy Ryan & Karen Gerard & Gillian Currie, 2012. "Using Discrete Choice Experiments in Health Economics," Chapters, in: The Elgar Companion to Health Economics, Second Edition, chapter 41 Edward Elgar Publishing.
  14. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
  15. Swait, Joffre & Adamowicz, Wiktor L., 1999. "Choice Environment, Market Complexity and Consumer Behavior: A Theoretical and Empirical Approach for Incorporating Decision Complexity into Models of Consumer Choice," Staff Paper Series 24093, University of Alberta, Department of Resource Economics and Environmental Sociology.
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  17. Denzil G. Fiebig & Stephanie Knox & Rosalie Viney & Marion Haas & Deborah J. Street, 2011. "Preferences for new and existing contraceptive products," Health Economics, John Wiley & Sons, Ltd., vol. 20(S1), pages 35-52, 09.
  18. Arne Risa Hole, 2007. "Fitting mixed logit models by using maximum simulated likelihood," Stata Journal, StataCorp LP, vol. 7(3), pages 388-401, September.
  19. Arne Risa Hole, 2007. "Modelling Heterogeneity in Patients' Preferences for the Attributes of a General Practitioner Appointment," Working Papers 022cherp, Centre for Health Economics, University of York.
  20. Emily Lancsar & Jordan Louviere, 2008. "Conducting Discrete Choice Experiments to Inform Healthcare Decision Making," PharmacoEconomics, Springer, vol. 26(8), pages 661-677, August.
  21. Jordan Louviere & Terry Flynn, 2010. "Using Best-Worst Scaling Choice Experiments to Measure Public Perceptions and Preferences for Healthcare Reform in Australia," The Patient: Patient-Centered Outcomes Research, Springer;Johns Hopkins Bloomberg School of Public Health, vol. 3(4), pages 275-283, December.
  22. Coast, Joanna & Flynn, Terry N. & Natarajan, Lucy & Sproston, Kerry & Lewis, Jane & Louviere, Jordan J. & Peters, Tim J., 2008. "Valuing the ICECAP capability index for older people," Social Science & Medicine, Elsevier, vol. 67(5), pages 874-882, September.
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