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Best-worst scaling vs. discrete choice experiments: An empirical comparison using social care data

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Listed:
  • Potoglou, Dimitris
  • Burge, Peter
  • Flynn, Terry
  • Netten, Ann
  • Malley, Juliette
  • Forder, Julien
  • Brazier, John E.

Abstract

This paper presents empirical findings from the comparison between two principal preference elicitation techniques: discrete choice experiments and profile-based best-worst scaling. Best-worst scaling involves less cognitive burden for respondents and provides more information than traditional "pick-one" tasks asked in discrete choice experiments. However, there is lack of empirical evidence on how best-worst scaling compares to discrete choice experiments. This empirical comparison between discrete choice experiments and best-worst scaling was undertaken as part of the Outcomes of Social Care for Adults project, England, which aims to develop a weighted measure of social care outcomes. The findings show that preference weights from best-worst scaling and discrete choice experiments do reveal similar patterns in preferences and in the majority of cases preference weights - when normalised/rescaled - are not significantly different.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:socmed:v:72:y:2011:i:10:p:1717-1727
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    References listed on IDEAS

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    1. Brazier, John & Ratcliffe, Julie & Salomon, Joshua & Tsuchiya, Aki, 2016. "Measuring and Valuing Health Benefits for Economic Evaluation," OUP Catalogue, Oxford University Press, edition 2, number 9780198725923.
    2. 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.
    3. 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.
    4. Burge, Peter & Netten, Ann & Gallo, Federico, 2010. "Estimating the value of social care," Journal of Health Economics, Elsevier, vol. 29(6), pages 883-894, December.
    5. Office of Health Economics, 2007. "The Economics of Health Care," For School 001490, Office of Health Economics.
    6. Jordan Louviere, 2006. "What You Don’t Know Might Hurt You: Some Unresolved Issues in the Design and Analysis of Discrete Choice Experiments," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 34(1), pages 173-188, May.
    7. Terry Flynn, 2010. "Using Conjoint Analysis and Choice Experiments to Estimate QALY Values," PharmacoEconomics, Springer, vol. 28(9), pages 711-722, September.
    8. Denzil G. Fiebig & Michael P. Keane & Jordan Louviere & Nada Wasi, 2010. "The Generalized Multinomial Logit Model: Accounting for Scale and Coefficient Heterogeneity," Marketing Science, INFORMS, vol. 29(3), pages 393-421, 05-06.
    9. Grewal, Ini & Lewis, Jane & Flynn, Terry & Brown, Jackie & Bond, John & Coast, Joanna, 2006. "Developing attributes for a generic quality of life measure for older people: Preferences or capabilities?," Social Science & Medicine, Elsevier, vol. 62(8), pages 1891-1901, April.
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