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An experiment on simplifying conjoint analysis designs for measuring preferences

Author

Listed:
  • Tara Maddala

    (Clinimetrics Research Inc., San Jose, California, USA)

  • Kathryn A. Phillips

    (University of California, San Francisco, USA)

  • F. Reed Johnson

    (Health Economics, Research Triangle Institute, North Carolina, USA)

Abstract

In conjoint analysis (CA) studies, choosing between scenarios with multiple health attributes may be demanding for respondents. This study examined whether simplifying the choice task in CA designs, by using a design with more overlap of attribute levels, provides advantages over standard minimal-overlap methods. Two experimental conditions, minimal and increased-overlap discrete choice CA designs, were administered to 353 respondents as part of a larger HIV testing preference survey. In the minimal-overlap survey, all six attribute levels were allowed to vary. In the increased-overlap survey, an average of two attribute levels were the same between each set of scenarios. We hypothesized that the increased-overlap design would reduce cognitive burden, while minimally impacting statistical efficiency. We did not find any significant improvement in consistency, willingness to trade, perceived difficulty, fatigue, or efficiency, although several results were in the expected direction. However, evidence suggested that there were differences in stated preferences. The results increase our understanding of how respondents answer CA questions and how to improve future surveys. Copyright © 2003 John Wiley & Sons, Ltd.

Suggested Citation

  • 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.
  • Handle: RePEc:wly:hlthec:v:12:y:2003:i:12:p:1035-1047
    DOI: 10.1002/hec.798
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    References listed on IDEAS

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    1. 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.
    2. Mandy Ryan & Emma McIntosh & Phil Shackley, 1998. "Methodological issues in the application of conjoint analysis in health care," Health Economics, John Wiley & Sons, Ltd., vol. 7(4), pages 373-378.
    3. Stirling Bryan & Lisa Gold & Rob Sheldon & Martin Buxton, 2000. "Preference measurement using conjoint methods: an empirical investigation of reliability," Health Economics, John Wiley & Sons, Ltd., vol. 9(5), pages 385-395.
    4. 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.
    5. 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.
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    Cited by:

    1. 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.
    2. Yasushi Ohkusa & Tamie Sugawara, 2006. "Cost-effectiveness analysis and its application for policy evaluation for medicine or public health," Public Policy Review, Policy Research Institute, Ministry of Finance Japan, vol. 2(1), pages 45-76, January.
    3. Yasushi Ohkusa & Tamie Sugawara, 2006. "Cost-effectiveness analysis and its application for policy evaluation for medicine or public health," Development Economics Working Papers 22354, East Asian Bureau of Economic Research.
    4. Mandy Ryan & Mabelle Amaya-Amaya, 2005. "' Threats ' to and hopes for estimating benefits," Health Economics, John Wiley & Sons, Ltd., vol. 14(6), pages 609-619.
    5. 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.
    6. Mickael Bech & Dorte Gyrd-Hansen, 2005. "Effects coding in discrete choice experiments," Health Economics, John Wiley & Sons, Ltd., vol. 14(10), pages 1079-1083.
    7. Semra Özdemir & Ateesha F. Mohamed & F. Reed Johnson & A. Brett Hauber, 2010. "Who pays attention in stated-choice surveys?," Health Economics, John Wiley & Sons, Ltd., vol. 19(1), pages 111-118.
    8. Fernando San Miguel & Mandy Ryan & Mabelle Amaya-Amaya, 2005. "'Irrational' stated preferences: a quantitative and qualitative investigation," Health Economics, John Wiley & Sons, Ltd., vol. 14(3), pages 307-322.
    9. Deborah A. Marshall & F. Reed Johnson & Nathalie A. Kulin & Semra Özdemir & Judith M. E. Walsh & John K. Marshall & Stephanie Van Bebber & Kathryn A. Phillips, 2009. "How do physician assessments of patient preferences for colorectal cancer screening tests differ from actual preferences? A comparison in Canada and the United States using a stated-choice survey," Health Economics, John Wiley & Sons, Ltd., vol. 18(12), pages 1420-1439.
    10. Bart Neuts & Peter Nijkamp & Eveline van Leeuwen, 2013. "Crowding Externalities from Tourist Use of Urban Space," Tinbergen Institute Discussion Papers 13-146/VIII, Tinbergen Institute.
    11. Esther Bekker-Grob & John Rose & Michiel Bliemer, 2013. "A Closer Look at Decision and Analyst Error by Including Nonlinearities in Discrete Choice Models: Implications on Willingness-to-Pay Estimates Derived from Discrete Choice Data in Healthcare," PharmacoEconomics, Springer, vol. 31(12), pages 1169-1183, December.
    12. F. Johnson, 2006. "Comment on “Revealing Differences in Willingness to Pay Due to the Dimensionality of Stated Choice Designs: An Initial Assessment”," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 34(1), pages 45-50, May.
    13. 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.
    14. Christine Poulos & Elizabeth Kinter & Jui-Chen Yang & John F. P. Bridges & Joshua Posner & Anthony T. Reder, 2016. "Patient Preferences for Injectable Treatments for Multiple Sclerosis in the United States: A Discrete-Choice Experiment," The Patient: Patient-Centered Outcomes Research, Springer;Johns Hopkins Bloomberg School of Public Health, vol. 9(2), pages 171-180, April.
    15. Poulos, Christine & Yang, Jui-Chen & Patil, Sumeet R. & Pattanayak, Subhrendu & Wood, Siri & Goodyear, Lorelei & Gonzalez, Juan Marcos, 2012. "Consumer preferences for household water treatment products in Andhra Pradesh, India," Social Science & Medicine, Elsevier, vol. 75(4), pages 738-746.
    16. 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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