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Design techniques for stated preference methods in health economics

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  • Fredrik Carlsson

    (Department of Economics, Göteborg University, Gothenburg, Sweden)

  • Peter Martinsson

    (Department of Economics, Lund University, Lund, Sweden)

Abstract

This paper discusses different design techniques for stated preference surveys in health economic applications. In particular, we focus on different design techniques, i.e. how to combine the attribute levels into alternatives and choice sets, for choice experiments. Design is a vital issue in choice experiments since the combination of alternatives in the choice sets will determine the degree of precision obtainable from the estimates and welfare measures. In this paper we compare orthogonal, cyclical and D-optimal designs, where the latter allows expectations about the true parameters to be included when creating the design. Moreover, we discuss how to obtain prior information on the parameters and how to conduct a sequential design procedure during the actual experiment in order to improve the precision in the estimates. The designs are evaluated according to their ability to predict the true marginal willingness to pay under different specifications of the utility function in Monte Carlo simulations. Our results suggest that the designs produce unbiased estimations, but orthogonal designs result in larger mean square error in comparison to D-optimal designs. This result is expected when using correct priors on the parameters in D-optimal designs. However, the simulations show that welfare measures are not very sensitive if the choice sets are generated from a D-optimal design with biased priors. Copyright © 2002 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/hec.729
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Bibliographic Info

Article provided by John Wiley & Sons, Ltd. in its journal Health Economics.

Volume (Year): 12 (2003)
Issue (Month): 4 ()
Pages: 281-294

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Handle: RePEc:wly:hlthec:v:12:y:2003:i:4:p:281-294

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/5749

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  1. Verhoef, C. G. & Maas, A. & Stalpers, L. J. A. & Verbeek, A. L. M. & Wobbes, Th. & van Daal, W. A. J., 1991. "The feasibility of additive conjoint measurement in measuring utilities in breast cancer patients," Health Policy, Elsevier, vol. 17(1), pages 39-50, February.
  2. Barbara J. Kanninen, 1993. "Optimal Experimental Design for Double-Bounded Dichotomous Choice Contingent Valuation," Land Economics, University of Wisconsin Press, vol. 69(2), pages 138-146.
  3. Vick, Sandra & Scott, Anthony, 1998. "Agency in health care. Examining patients' preferences for attributes of the doctor-patient relationship," Journal of Health Economics, Elsevier, vol. 17(5), pages 587-605, October.
  4. Alberini Anna, 1995. "Optimal Designs for Discrete Choice Contingent Valuation Surveys: Single-Bound, Double-Bound, and Bivariate Models," Journal of Environmental Economics and Management, Elsevier, vol. 28(3), pages 287-306, May.
  5. F. Reed Johnson & Melissa Ruby Banzhaf & William H. Desvousges, 2000. "Willingness to pay for improved respiratory and cardiovascular health: a multiple-format, stated-preference approach," Health Economics, John Wiley & Sons, Ltd., vol. 9(4), pages 295-317.
  6. Kanninen Barbara J., 1993. "Design of Sequential Experiments for Contingent Valuation Studies," Journal of Environmental Economics and Management, Elsevier, vol. 25(1), pages S1-S11, July.
  7. Mandy Ryan & Jenny Hughes, 1997. "Using Conjoint Analysis to Assess Women's Preferences for Miscarriage Management," Health Economics, John Wiley & Sons, Ltd., vol. 6(3), pages 261-273.
  8. Carol Propper, 1995. "The Disutility of Time Spent on the United Kingdom's National Health Service Waiting Lists," Journal of Human Resources, University of Wisconsin Press, vol. 30(4), pages 677-700.
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