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Quantification of Health States with Rank-Based Nonmetric Multidimensional Scaling

Author

Listed:
  • Paul F. M. Krabbe

    (Department of Medical Technology Assessment (138), Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands, p.krabbe@mta.umcn.nl)

  • Joshua A. Salomon

    (Department of Population and International Health, Harvard School of Public Health, Boston, Harvard Initiative for Global Health, Harvard University, Cambridge, MA)

  • Christopher J. L. Murray

    (Department of Population and International Health, Harvard School of Public Health, Boston, Harvard Initiative for Global Health, Harvard University, Cambridge, MA)

Abstract

Objectives. An alternative methodology is introduced to generate cardinal valuations of health states. This methodology is based on the ranking of differences between health states combined with an associated scaling model that transforms the individual rank data into group values on the interval level. Methods. Data were collected in a Dutch EuroQol EQ-5D valuation study, in which a representative sample (n = 212) of the Dutch population valued a set of 18 EQ-5D health states and death. Three computational steps were undertaken: 1) differences in visual analog scale (VAS) values were computed for each pair of health states based on individual data; 2) the rank ordering of these pairwise differences was derived; 3) nonmetric multidimensional scaling was used to recover cardinal scale values for each state based on these rankings of differences. Results. Scaling of ranked differences between health states using multidimensional scaling produced cardinal values that were nearly identical to the mean VAS valuations. The rank-based values explained 98% of the variance in the VAS values. Conclusion. Ordinal data collection techniques, combined with scaling models, may offer an attractive alternative to direct cardinal elicitation methods for valuing health states.

Suggested Citation

  • Paul F. M. Krabbe & Joshua A. Salomon & Christopher J. L. Murray, 2007. "Quantification of Health States with Rank-Based Nonmetric Multidimensional Scaling," Medical Decision Making, , vol. 27(4), pages 395-405, July.
    • Handle: RePEc:sae:medema:v:27:y:2007:i:4:p:395-405
    DOI: 10.1177/0272989X07302131
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    References listed on IDEAS

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    1. Louviere,Jordan J. & Hensher,David A. & Swait,Joffre D. With contributions by-Name:Adamowicz,Wiktor, 2000. "Stated Choice Methods," Cambridge Books, Cambridge University Press, number 9780521788304, December.
    2. Schoemaker, Paul J H, 1982. "The Expected Utility Model: Its Variants, Purposes, Evidence and Limitations," Journal of Economic Literature, American Economic Association, vol. 20(2), pages 529-563, June.
    3. Warren Torgerson, 1952. "Multidimensional scaling: I. Theory and method," Psychometrika, Springer;The Psychometric Society, vol. 17(4), pages 401-419, December.
    4. Nord, Erik, 1992. "Methods for quality adjustment of life years," Social Science & Medicine, Elsevier, vol. 34(5), pages 559-569, March.
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    Cited by:

    1. Paul F. M. Krabbe & Elly A. Stolk & Nancy J. Devlin & Feng Xie & Elise H. Quik & A. Simon Pickard, 2017. "Head-to-head comparison of health-state values derived by a probabilistic choice model and scores on a visual analogue scale," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(8), pages 967-977, November.
    2. Paul F M Krabbe, 2013. "A Generalized Measurement Model to Quantify Health: The Multi-Attribute Preference Response Model," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-12, November.

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