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Empirical investigation of experimental design properties of discrete choice experiments in health care

  • Rosalie Viney

    (Centre for Health Economics Research and Evaluation, Faculty of Business, University of Technology, Sydney, Australia)

  • Elizabeth Savage

    (Centre for Health Economics Research and Evaluation, Faculty of Business, University of Technology, Sydney, Australia)

  • Jordan Louviere

    (Centre for Study of Choice and Centre for Health Economics Research and Evaluation, School of Marketing, Faculty of Business, University of Technology, Sydney, Australia)

Experimental design is critical to valid inference from the results of discrete choice experiments (DCEs). In health economics, DCEs have placed limited emphasis on experimental design, typically employing relatively small fractional factorial designs, which allow only strictly linear additive utility functions to be estimated. The extensive literature on optimal experimental design outside health economics has proposed potentially desirable design properties, such as orthogonality, utility balance and level balance. However, there are trade-offs between these properties and emphasis on some properties may increase the random variability in responses, potentially biasing parameter estimates. This study investigates empirically the design properties of DCEs, in particular, the optimal method of combining alternatives in the choice set. The study involves a forced choice between two alternatives (treatment and non-treatment for a hypothetical health care condition), each with three, four-level, alternative-specific attributes. Three experimental design approaches are investigated: a standard six-attribute, orthogonal main effects design; a design that combines alternatives to achieve utility balance, ensuring no alternatives are dominated; and a design that combines alternatives randomly. The different experimental designs did not impact on the underlying parameter estimates, but imposing utility balance increases the random variability of responses. Copyright © 2005 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/hec.981
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Article provided by John Wiley & Sons, Ltd. in its journal Health Economics.

Volume (Year): 14 (2005)
Issue (Month): 4 ()
Pages: 349-362

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Handle: RePEc:wly:hlthec:v:14:y:2005:i:4:p:349-362
Contact details of provider: Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/5749

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  1. Stirling Bryan & Martin Buxton & Robert Sheldon & Alison Grant, 1998. "Magnetic resonance imaging for the investigation of knee injuries: an investigation of preferences," Health Economics, John Wiley & Sons, Ltd., vol. 7(7), pages 595-603.
  2. repec:cup:cbooks:9780521788304 is not listed on IDEAS
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  7. Zafar Hakim & Dev S. Pathak, 1999. "Modelling the EuroQol data: a comparison of discrete choice conjoint and conditional preference modelling," Health Economics, John Wiley & Sons, Ltd., vol. 8(2), pages 103-116.
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  9. 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.
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