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Using discrete choice experiments to understand preferences for quality of life. Variance-scale heterogeneity matters

Listed author(s):
  • Flynn, Terry Nicholas
  • Louviere, Jordan J.
  • Peters, Tim J.
  • Coast, Joanna
Registered author(s):

    Health services researchers are increasingly using discrete choice experiments (DCEs) to model a latent variable, be it health, health-related quality of life or utility. Unfortunately it is not widely recognised that failure to model variance heterogeneity correctly leads to bias in the point estimates. This paper compares variance heterogeneity latent class models with traditional multinomial logistic (MNL) regression models. Using the ICECAP-O quality of life instrument which was designed to provide a set of preference-based general quality of life tariffs for the UK population aged 65+, it demonstrates that there is both mean and variance heterogeneity in preferences for quality of life, which covariate-adjusted MNL is incapable of separating. Two policy-relevant mean groups were found: one group that particularly disliked impairments to independence was dominated by females living alone (typically widows). Males who live alone (often widowers) did not display a preference for independence, but instead showed a strong aversion to social isolation, as did older people (of either sex) who lived with a spouse. Approximately 6-10% of respondents can be classified into a third group that often misunderstood the task. Having a qualification of any type and higher quality of life was associated with smaller random component variances. This illustrates how better understanding of random utility theory enables richer inferences to be drawn from discrete choice experiments. The methods have relevance for all health studies using discrete choice tasks to make inferences about a latent scale, particular QALY valuation exercises that use DCEs, best-worst scaling and ranking tasks.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0277-9536(10)00235-2
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    Article provided by Elsevier in its journal Social Science & Medicine.

    Volume (Year): 70 (2010)
    Issue (Month): 12 (June)
    Pages: 1957-1965

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    Handle: RePEc:eee:socmed:v:70:y:2010:i:12:p:1957-1965
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    1. 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, 05.
    2. 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.
    3. Yatchew, Adonis & Griliches, Zvi, 1985. "Specification Error in Probit Models," The Review of Economics and Statistics, MIT Press, vol. 67(1), pages 134-139, February.
    4. 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.
    5. 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.
    6. Emily Lancsar & Jordan Louviere, 2008. "Conducting Discrete Choice Experiments to Inform Healthcare Decision Making," PharmacoEconomics, Springer, vol. 26(8), pages 661-677, August.
    7. 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.
    8. Hole, Arne Risa, 2008. "Modelling heterogeneity in patients' preferences for the attributes of a general practitioner appointment," Journal of Health Economics, Elsevier, vol. 27(4), pages 1078-1094, July.
    9. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    10. Dolan, Paul, 2008. "Developing methods that really do value the ‘Q’ in the QALY," Health Economics, Policy and Law, Cambridge University Press, vol. 3(01), pages 69-77, January.
    11. van der Pol, Marjon & Cairns, John, 2008. "Comparison of two methods of eliciting time preference for future health states," Social Science & Medicine, Elsevier, vol. 67(5), pages 883-889, September.
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