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Modelling the EuroQol data: a comparison of discrete choice conjoint and conditional preference modelling

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  • Zafar Hakim

    (Global Pharmacoeconomic Research, Roche Pharmaceuticals, Palo Alto, CA, USA)

  • Dev S. Pathak

    (College of Pharmacy and Centre for Health Outcomes, Policy, and Evaluation Studies, The Ohio State University, Columbus, OH, USA)

Abstract

This article compares two measurement strategies for measuring EuroQol health state preferences: (a) conditional preference modelling, implemented using rating scale and standard gamble scaling methods and (b) discrete choice conjoint modelling. The nature of the model form of the EuroQol health status preference function and the predictive ability of each measurement strategy formed the basis of the comparison. Data were collected via personal interviews with 140 US patients, 139 of whom provided usable responses. Both strategies supported a multiplicative model form as representative of the EuroQol health status preference function and were acceptable in terms of predictive ability. The agreement of the two measurement strategies on the nature of the model form provides evidence of the convergent validity of the multiplicative nature of the EuroQol health status preference function in this patient population. Since both strategies were found to be acceptable in terms of predictive ability, further research comparing preference scores and measuring respondent evaluations of the methodologies is necessary to illustrate the relative strengths and weaknesses of different health state preference measurement methodologies. Copyright © 1999 John Wiley & Sons, Ltd.

Suggested Citation

  • 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.
  • Handle: RePEc:wly:hlthec:v:8:y:1999:i:2:p:103-116
    DOI: 10.1002/(SICI)1099-1050(199903)8:2<103::AID-HEC393>3.0.CO;2-E
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    References listed on IDEAS

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    Cited by:

    1. Bansback, Nick & Brazier, John & Tsuchiya, Aki & Anis, Aslam, 2012. "Using a discrete choice experiment to estimate health state utility values," Journal of Health Economics, Elsevier, vol. 31(1), pages 306-318.
    2. Luciana Scalone & Peep Stalmeier & Silvano Milani & Paul Krabbe, 2015. "Values for health states with different life durations," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(9), pages 917-925, December.
    3. Brazier, J & Rowen, D & Yang, Y & Tsuchiya, A, 2009. "Using rank and discrete choice data to estimate health state utility values on the QALY scale," MPRA Paper 29891, University Library of Munich, Germany.
    4. repec:spr:eujhec:v:18:y:2017:i:8:d:10.1007_s10198-016-0841-y is not listed on IDEAS
    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. John Brazier & Donna Rowen & Yaling Yang & Aki Tsuchiya, 2012. "Comparison of health state utility values derived using time trade-off, rank and discrete choice data anchored on the full health-dead scale," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 13(5), pages 575-587, October.
    7. 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.
    8. Seiritsu Ogura & Wataru Suzuki & Makoto Kawamura & Tamotsu Kadoda, 2006. "Conjoint Analysis to Estimate the Demand for Nicotine Replacement Therapy in Japan," NBER Chapters,in: Health Care Issues in the United States and Japan, pages 229-246 National Bureau of Economic Research, Inc.
    9. 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.
    10. Kara Hanson & Barbara McPake & Pamela Nakamba & Luke Archard, 2005. "Preferences for hospital quality in Zambia: results from a discrete choice experiment," Health Economics, John Wiley & Sons, Ltd., vol. 14(7), pages 687-701.
    11. Ariane Kawata & Leah Kleinman & Gale Harding & Sulabha Ramachandran, 2014. "Evaluation of Patient Preference and Willingness to Pay for Attributes of Maintenance Medication for Chronic Obstructive Pulmonary Disease (COPD)," The Patient: Patient-Centered Outcomes Research, Springer;Johns Hopkins Bloomberg School of Public Health, vol. 7(4), pages 413-426, December.
    12. 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.
    13. McKenzie, Lynda & Cairns, John & Osman, Liesl, 2001. "Symptom-based outcome measures for asthma: the use of discrete choice methods to assess patient preferences," Health Policy, Elsevier, vol. 57(3), pages 193-204, September.

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