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| Research article summary (published 30 Mar 2003): |
Design techniques for stated preference methods in health economics.
Full Abstract
This paper discusses different design techniques for stated preference surveys in health economic applications. In particular, we focus on different design techniques, i.e. how to combine the attribute levels into alternatives and choice sets, for choice experiments. Design is a vital issue in choice experiments since the combination of alternatives in the choice sets will determine the degree of precision obtainable from the estimates and welfare measures. In this paper we compare orthogonal, cyclical and D-optimal designs, where the latter allows expectations about the true parameters to be included when creating the design. Moreover, we discuss how to obtain prior information on the parameters and how to conduct a sequential design procedure during the actual experiment in order to improve the precision in the estimates. The designs are evaluated according to their ability to predict the true marginal willingness to pay under different specifications of the utility function in Monte Carlo simulations. Our results suggest that the designs produce unbiased estimations, but orthogonal designs result in larger mean square error in comparison to D-optimal designs. This result is expected when using correct priors on the parameters in D-optimal designs. However, the simulations show that welfare measures are not very sensitive if the choice sets are generated from a D-optimal design with biased priors.Copyright 2002 John Wiley & Sons, Ltd.
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Author information
Author/s: Carlsson, Fredrik (F); Martinsson, Peter (P);
Affiliation: Department of Economics, Göteborg University, Gothenburg, Sweden. frederik.carlsson(-atsign-)economics.gu.se
Journal and publication information
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal: Health economics (Health Econ), published in England. (Language: eng)
Reference: 2003-Apr; vol 12 (issue 4) : pp 281-94
Dates: Created 2003/03/24; Completed 2003/05/13; Revised 2006/11/15;
PMID: 12652515, status: MEDLINE (last retrieval date: 11/6/2008)
Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.
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