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Supra-states and censoring in health utility modelling: an examination of their importance in the EQ-5D tariff


  • Richard Edlin

    () (Academic Unit of Health Economics, University of Leeds, Leeds)

  • Roberta Longo

    (Academic Unit of Health Economics, University of Leeds, Leed)

  • Christopher McCabe

    (Academic Unit of Health Economics, University of Leeds, Leed)


The methodology used when estimating utilities assumes that the best health state in a health-related quality of life (HrQoL) measure is equivalent to perfect health, with both valued at one. In this paper we explore the impact of relaxing this assumption by treating measured utilities as censored data. We compare Random Effects Tobit (Tobit RE), and Censored Least Absolute Deviation (CLAD) models of the UK EQ-5D TTO data with the recommended Generalised Least Squares Random Effects (GLS RE) model. Both the Tobit RE and CLAD models indicate that value of perfect health is greater than one (1.106, 1.036). The Tobit RE model values three of the mildest EQ-5D states (11112 , 11211, 21111) as greater than one; capturing the large scale non-trading in measured values for the states. The Tobit RE model utility estimates for poor health states are close to the GLE RE estimates. Possible health policy and research responses to the findings are discussed.

Suggested Citation

  • Richard Edlin & Roberta Longo & Christopher McCabe, 2010. "Supra-states and censoring in health utility modelling: an examination of their importance in the EQ-5D tariff," Working Papers 1002, Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds.
  • Handle: RePEc:lee:wpaper:1002

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    References listed on IDEAS

    1. Eddy van Doorslaer & Xander Koolman, 2004. "Explaining the differences in income-related health inequalities across European countries," Health Economics, John Wiley & Sons, Ltd., vol. 13(7), pages 609-628.
    2. Ann Lecluyse & Irina Cleemput, 2006. "Making health continuous: implications of different methods on the measurement of inequality," Health Economics, John Wiley & Sons, Ltd., vol. 15(1), pages 99-104.
    3. van Doorslaer, Eddy & Wagstaff, Adam & Bleichrodt, Han & Calonge, Samuel & Gerdtham, Ulf-G. & Gerfin, Michael & Geurts, Jose & Gross, Lorna & Hakkinen, Unto & Leu, Robert E., 1997. "Income-related inequalities in health: some international comparisons," Journal of Health Economics, Elsevier, vol. 16(1), pages 93-112, February.
    4. Van Ourti, Tom, 2003. "Socio-economic inequality in ill-health amongst the elderly: Should one use current or permanent income?," Journal of Health Economics, Elsevier, vol. 22(2), pages 219-241, March.
    5. Hendrik Jürges, 2007. "True health vs response styles: exploring cross-country differences in self-reported health," Health Economics, John Wiley & Sons, Ltd., vol. 16(2), pages 163-178.
    6. repec:adr:anecst:y:2006:i:83-84:p:04 is not listed on IDEAS
    7. Olsen, Karen M. & Dahl, Svenn-Åge, 2007. "Health differences between European countries," Social Science & Medicine, Elsevier, vol. 64(8), pages 1665-1678, April.
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    More about this item


    Measurement and valuation of health; EQ-5D; anchoring;

    JEL classification:

    • I1 - Health, Education, and Welfare - - Health


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