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Designing Choice Experiments with Many Attributes: An Application to Setting Priorities for Orthopaedic Waiting Lists

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Author Info
Julia Witt () (Melbourne Institute of Applied Economic and Social Research, The University of MelbourneTitle: Fiscal and Current Account Balances in a Model with Sticky Prices and Distortionary Taxes)
Anthony Scott () (Melbourne Institute of Applied Economic and Social Research, The University of Melbourne)
Richard H. Osborne (Centre for Rheumatic Diseases, Department of Medicine, Royal Melbourne Hospital, The University of Melbourne)

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Abstract

Stated preference discrete choice experiments are being increasingly used to value the quality of health care services. To date in the health economics literature, discrete choice experiments have used only a relatively small number of attributes due to concerns about task complexity, non-compensatory decision rules, simplicity of experimental designs, and the costs of surveys. This may lead to omitted variable bias and reduced explanatory power when attributes have been pre-selected from a longer list. There may be situations where it is desirable to include a longer list of attributes, such as attaching weights to quality of life instruments to obtain single index scores. The aim of this paper is to examine the feasibility of using a ‘blocked attribute’ design in a DCE with 11 attributes. This method allocates the 11 attributes across three separate experimental designs and pools the data for analysis. We examine this issue in the context of attaching weights to a disease specific quality of life instrument used to prioritise orthopaedic waiting lists in Victorian hospitals. We produce a single index measure of utility for health states of patients, bounded between zero and one. The use of such a design seems feasible, although issues remain to be resolved about how the ranking should be used in practice to set priorities for waiting lists.

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Paper provided by Melbourne Institute of Applied Economic and Social Research, The University of Melbourne in its series Melbourne Institute Working Paper Series with number wp2006n24.

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Length: 25 pages
Date of creation: Oct 2006
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Handle: RePEc:iae:iaewps:wp2006n24

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Joel Huber & Kenneth Train, 2001. "On the Similarity of Classical and Bayesian Estimates of Individual Mean Partworths," Econometrics 0012003, EconWPA. [Downloadable!]
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  2. Brownstone, David & Bunch, David S. & Train, Kenneth, 2000. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 315-338, June. [Downloadable!] (restricted)
  3. Scott, Anthony, 2002. "Identifying and analysing dominant preferences in discrete choice experiments: An application in health care," Journal of Economic Psychology, Elsevier, vol. 23(3), pages 383-398, June. [Downloadable!] (restricted)
  4. 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. [Downloadable!]
  5. 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. [Downloadable!] (restricted)
  6. Kenneth Train, 2003. "Discrete Choice Methods with Simulation," Online economics textbooks, SUNY-Oswego, Department of Economics, number emetr2, March. [Downloadable!]
  7. 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. [Downloadable!] (restricted)
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