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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 Melbourne, Parkville, Vic., Australia)
Anthony Scott (Melbourne Institute of Applied Economic and Social Research, The University of Melbourne, Parkville, Vic., Australia)
Richard H. Osborne (Centre for Rheumatic Diseases, Department of Medicine, Royal Melbourne Hospital, The University of Melbourne, Parkville, Vic., Australia)

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Abstract

The aim of this paper is to undertake a discrete choice experiment using a 'blocked attribute' design. To date in the health economics literature, most 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. We examine this issue in the context of attaching weights to a disease-specific quality-of-life instrument used to prioritise patients on orthopaedic waiting lists in Victorian hospitals. Eleven attributes are allocated across three separate experimental designs and the data pooled for analysis. Pooling is justified given the specific context of the study, including attempts to minimise the effect of unobserved heterogeneity across the three models when designing the study and collecting data. Blocked attribute designs may offer flexibility to researchers when it is not possible or desirable to reduce the number of attributes. Copyright © 2008 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/hec.1396
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Publisher Info
Article provided by John Wiley & Sons, Ltd. in its journal Health Economics.

Volume (Year): 18 (2009)
Issue (Month): 6 ()
Pages: 681-696
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Handle: RePEc:wly:hlthec:v:18:y:2009:i:6:p:681-696

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/5749

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References listed on IDEAS
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. 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)
  3. 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)
  4. 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)
  5. 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!]
  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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