Abstract
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.
| Translated title of the contribution | Best-Worst Scaling: What it can do for health care research and how to do it |
|---|---|
| Original language | English |
| Pages (from-to) | 171 - 189 |
| Number of pages | 19 |
| Journal | Journal of Health Economics |
| Volume | 26 (1) |
| DOIs | |
| Publication status | Published - Jan 2007 |
Bibliographical note
Publisher: ElsevierFingerprint
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