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Best-worst scaling: What it can do for health care research and how to do it
被引:526
作者:
Flynn, Terry N.
Louviere, Jordan J.
Peters, Tim J.
Coast, Joanna
机构:
[1] Univ Bristol, MRC, Hlth Serv Res Collaborat, Dept Social Med, Bristol BS8 1TH, Avon, England
[2] Univ Technol Sydney, Ctr Study Choice, Sydney, NSW 2007, Australia
[3] Univ Bristol, Dept Community Based Med, Bristol BS8 1TH, Avon, England
[4] Univ Birmingham, Hlth Econ Facil, Birmingham B15 2TT, W Midlands, England
基金:
英国医学研究理事会;
关键词:
discrete choice experiments;
utility;
attribute importance;
D O I:
10.1016/j.jhealeco.2006.04.002
中图分类号:
F [经济];
学科分类号:
02 ;
摘要:
Statements like "quality of care is more highly valued than waiting time" can neither be supported nor refuted by comparisons of utility parameters from a traditional discrete choice experiment (DCE). Best-worst scaling can overcome this problem because it asks respondents to perform a different choice task. However, whilst the nature of the best-worst task is generally understood, there are a number of issues relating to the design and analysis of a best-worst choice experiment that require further exposition. This paper illustrates how to aggregate and analyse such data and using a quality of life pilot study demonstrates how richer insights can be drawn by the use of best-worst tasks. (c) 2006 Elsevier B.V. All rights reserved.
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页码:171 / 189
页数:19
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