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

Author

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  • 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)

Abstract

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.

Suggested Citation

  • Rosalie Viney & Elizabeth Savage & Jordan Louviere, 2005. "Empirical investigation of experimental design properties of discrete choice experiments in health care," Health Economics, John Wiley & Sons, Ltd., vol. 14(4), pages 349-362.
  • Handle: RePEc:wly:hlthec:v:14:y:2005:i:4:p:349-362 DOI: 10.1002/hec.981
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    References listed on IDEAS

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    1. Propper, Carol, 1990. "Contingent Valuation of Time Spent on NHS Waiting Lists," Economic Journal, Royal Economic Society, vol. 100(400), pages 193-199, Supplemen.
    2. 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.
    3. 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, March.
    4. 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.
    5. Shelley Farrar & Mandy Ryan, 1999. "Response-ordering effects: a methodological issue in conjoint analysis," Health Economics, John Wiley & Sons, Ltd., vol. 8(1), pages 75-79.
    6. Farrar, Shelley & Ryan, Mandy & Ross, Donald & Ludbrook, Anne, 2000. "Using discrete choice modelling in priority setting: an application to clinical service developments," Social Science & Medicine, Elsevier, vol. 50(1), pages 63-75, January.
    7. Tara Maddala & Kathryn A. Phillips & F. Reed Johnson, 2003. "An experiment on simplifying conjoint analysis designs for measuring preferences," Health Economics, John Wiley & Sons, Ltd., vol. 12(12), pages 1035-1047.
    8. 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.
    9. Fredrik Carlsson & Peter Martinsson, 2003. "Design techniques for stated preference methods in health economics," Health Economics, John Wiley & Sons, Ltd., vol. 12(4), pages 281-294.
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    Citations

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    Cited by:

    1. Rosalie Viney & Elizabeth Savage, 2006. "Health care policy evaluation: empirical analysis of the restrictions implied by Quality Adjusted Life Years, CHERE Working Paper 2006/10," Working Papers 2006/10, CHERE, University of Technology, Sydney.
    2. Kerr, Geoffrey N. & Sharp, Basil M.H., 2010. "Choice experiment adaptive design benefits: a case study," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 54(4), December.
    3. Johnson, F. Reed & Ozdemir, Semra & Phillips, Kathryn A., 2010. "Effects of simplifying choice tasks on estimates of taste heterogeneity in stated-choice surveys," Social Science & Medicine, Elsevier, vol. 70(2), pages 183-190, January.
    4. repec:spr:pharme:v:35:y:2017:i:4:d:10.1007_s40273-016-0475-z is not listed on IDEAS
    5. Bouscasse, H. & Joly, I. & Peyhardi, J., 2016. "Estimating travel mode choice, including rail in regional area, based on a new family of regression models," Working Papers 2016-04, Grenoble Applied Economics Laboratory (GAEL).
    6. repec:spr:patien:v:11:y:2018:i:1:d:10.1007_s40271-017-0263-7 is not listed on IDEAS
    7. Chiara Seghieri & Alessandro Mengoni & Sabina Nuti, 2014. "Applying discrete choice modelling in a priority setting: an investigation of public preferences for primary care models," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 15(7), pages 773-785, September.
    8. Hall, Jane & Fiebig, Denzil G. & King, Madeleine T. & Hossain, Ishrat & Louviere, Jordan J., 2006. "What influences participation in genetic carrier testing?: Results from a discrete choice experiment," Journal of Health Economics, Elsevier, vol. 25(3), pages 520-537, May.
    9. Ferrini, Silvia & Scarpa, Riccardo, 2007. "Designs with a priori information for nonmarket valuation with choice experiments: A Monte Carlo study," Journal of Environmental Economics and Management, Elsevier, vol. 53(3), pages 342-363, May.
    10. Regier, Dean A. & Watson, Verity & Burnett, Heather & Ungar, Wendy J., 2014. "Task complexity and response certainty in discrete choice experiments: An application to drug treatments for juvenile idiopathic arthritis," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 50(C), pages 40-49.
    11. Bliemer, Michiel C.J. & Rose, John M., 2011. "Experimental design influences on stated choice outputs: An empirical study in air travel choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(1), pages 63-79, January.
    12. Emily Lancsar & Jordan Louviere, 2008. "Conducting Discrete Choice Experiments to Inform Healthcare Decision Making," PharmacoEconomics, Springer, vol. 26(8), pages 661-677, August.
    13. Emily Lancsar & Joffre Swait, 2014. "Reconceptualising the External Validity of Discrete Choice Experiments," PharmacoEconomics, Springer, vol. 32(10), pages 951-965, October.
    14. Elizabeth Kinter & Thomas Prior & Christopher Carswell & John Bridges, 2012. "A Comparison of Two Experimental Design Approaches in Applying Conjoint Analysis in Patient-Centered Outcomes Research," The Patient: Patient-Centered Outcomes Research, Springer;Johns Hopkins Bloomberg School of Public Health, vol. 5(4), pages 279-294, December.
    15. T.N. Flynn & A.A.J. Marley, 2014. "Best-worst scaling: theory and methods," Chapters,in: Handbook of Choice Modelling, chapter 8, pages 178-201 Edward Elgar Publishing.
    16. Julie Ratcliffe & John Brazier & Aki Tsuchiya & Tara Symonds & Martin Brown, 2009. "Using DCE and ranking data to estimate cardinal values for health states for deriving a preference-based single index from the sexual quality of life questionnaire," Health Economics, John Wiley & Sons, Ltd., vol. 18(11), pages 1261-1276.
    17. Emily Lancsar & Cam Donaldson, 2005. "Discrete choice experiments in health economics," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 6(4), pages 314-316, December.
    18. Alessandro Mengoni & Chiara Seghieri & Sabina Nuti, 2013. "The application of discrete choice experiments in health economics: a systematic review of the literature," Working Papers 201301, Scuola Superiore Sant'Anna of Pisa, Istituto di Management.
    19. Anderson, C. Leigh & Cullen, Alison & Stamoulis, Kostas, 2008. "Preference variability along the policy chain in Vietnam," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 37(5), pages 1729-1745, October.
    20. Richard Yao & Riccardo Scarpa & John Rose & James Turner, 2015. "Experimental Design Criteria and Their Behavioural Efficiency: An Evaluation in the Field," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(3), pages 433-455, November.
    21. Ryan, Mandy & Netten, Ann & Skatun, Diane & Smith, Paul, 2006. "Using discrete choice experiments to estimate a preference-based measure of outcome--An application to social care for older people," Journal of Health Economics, Elsevier, vol. 25(5), pages 927-944, September.
    22. Kerr, Geoffrey N. & Sharp, Basil M.H., 2009. "Efficiency benefits of choice model experimental design updating: a case study," 2009 Conference (53rd), February 11-13, 2009, Cairns, Australia 47623, Australian Agricultural and Resource Economics Society.
    23. Emily Lancsar & Peter Burge, 2014. "Choice modelling research in health economics," Chapters,in: Handbook of Choice Modelling, chapter 28, pages 675-687 Edward Elgar Publishing.
    24. Araña, Jorge E. & León, Carmelo J. & Hanemann, Michael W., 2008. "Emotions and decision rules in discrete choice experiments for valuing health care programmes for the elderly," Journal of Health Economics, Elsevier, vol. 27(3), pages 753-769, May.

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