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Experimental measurement of preferences in health care using best-worst scaling (BWS): theoretical and statistical issues
For optimal solutions in health care, decision makers inevitably must evaluate trade-offs, which call for multi-attribute valuation methods. Researchers have proposed using best-worst scaling (BWS) methods which seek to extract information from respondents by asking them to identify the best and wor...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4731383/ https://www.ncbi.nlm.nih.gov/pubmed/26822869 http://dx.doi.org/10.1186/s13561-015-0077-z |
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author | Mühlbacher, Axel C. Zweifel, Peter Kaczynski, Anika Johnson, F. Reed |
author_facet | Mühlbacher, Axel C. Zweifel, Peter Kaczynski, Anika Johnson, F. Reed |
author_sort | Mühlbacher, Axel C. |
collection | PubMed |
description | For optimal solutions in health care, decision makers inevitably must evaluate trade-offs, which call for multi-attribute valuation methods. Researchers have proposed using best-worst scaling (BWS) methods which seek to extract information from respondents by asking them to identify the best and worst items in each choice set. While a companion paper describes the different types of BWS, application and their advantages and downsides, this contribution expounds their relationships with microeconomic theory, which also have implications for statistical inference. This article devotes to the microeconomic foundations of preference measurement, also addressing issues such as scale invariance and scale heterogeneity. Furthermore the paper discusses the basics of preference measurement using rating, ranking and stated choice data in the light of the findings of the preceding section. Moreover the paper gives an introduction to the use of stated choice data and juxtaposes BWS with the microeconomic foundations. |
format | Online Article Text |
id | pubmed-4731383 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-47313832016-02-04 Experimental measurement of preferences in health care using best-worst scaling (BWS): theoretical and statistical issues Mühlbacher, Axel C. Zweifel, Peter Kaczynski, Anika Johnson, F. Reed Health Econ Rev Research For optimal solutions in health care, decision makers inevitably must evaluate trade-offs, which call for multi-attribute valuation methods. Researchers have proposed using best-worst scaling (BWS) methods which seek to extract information from respondents by asking them to identify the best and worst items in each choice set. While a companion paper describes the different types of BWS, application and their advantages and downsides, this contribution expounds their relationships with microeconomic theory, which also have implications for statistical inference. This article devotes to the microeconomic foundations of preference measurement, also addressing issues such as scale invariance and scale heterogeneity. Furthermore the paper discusses the basics of preference measurement using rating, ranking and stated choice data in the light of the findings of the preceding section. Moreover the paper gives an introduction to the use of stated choice data and juxtaposes BWS with the microeconomic foundations. Springer Berlin Heidelberg 2016-01-29 /pmc/articles/PMC4731383/ /pubmed/26822869 http://dx.doi.org/10.1186/s13561-015-0077-z Text en © Mühlbacher et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Research Mühlbacher, Axel C. Zweifel, Peter Kaczynski, Anika Johnson, F. Reed Experimental measurement of preferences in health care using best-worst scaling (BWS): theoretical and statistical issues |
title | Experimental measurement of preferences in health care using best-worst scaling (BWS): theoretical and statistical issues |
title_full | Experimental measurement of preferences in health care using best-worst scaling (BWS): theoretical and statistical issues |
title_fullStr | Experimental measurement of preferences in health care using best-worst scaling (BWS): theoretical and statistical issues |
title_full_unstemmed | Experimental measurement of preferences in health care using best-worst scaling (BWS): theoretical and statistical issues |
title_short | Experimental measurement of preferences in health care using best-worst scaling (BWS): theoretical and statistical issues |
title_sort | experimental measurement of preferences in health care using best-worst scaling (bws): theoretical and statistical issues |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4731383/ https://www.ncbi.nlm.nih.gov/pubmed/26822869 http://dx.doi.org/10.1186/s13561-015-0077-z |
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