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Comparison of statistical analysis methods for object case best–worst scaling

Published on Nov 27, 2018in Journal of Medical Economics
· DOI :10.1080/13696998.2018.1553781
Kei Long Cheung5
Estimated H-index: 5
(Medical University of Vienna),
Susanne Mayer6
Estimated H-index: 6
(Medical University of Vienna)
+ 4 AuthorsMickaël Hiligsmann27
Estimated H-index: 27
(PHRI: Public Health Research Institute)
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Abstract
AbstractAims: Different methods have been used to analyze “object case” best–worst scaling (BWS). This study aims to compare the most common statistical analysis methods for object case BWS (i.e. the count analysis, multinomial logit, mixed logit, latent class analysis, and hierarchical Bayes estimation) and to analyze their potential advantages and limitations based on an applied example.Methods: Data were analyzed using the five analysis methods. Ranking results were compared among the methods, and methods that take respondent heterogeneity into account were presented specifically. A BWS object case survey with 22 factors was used as a case study, tested among 136 policy-makers and HTA experts from the Netherlands, Germany, France, and the UK to assess the most important barriers to HTA usage.Results: Overall, the five statistical methods yielded similar rankings, particularly in the extreme ends. Latent class analysis identified five clusters and the mixed logit model revealed significant preference he...
  • References (27)
  • Citations (1)
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References27
Newest
Kei Long Cheung5
Estimated H-index: 5
(Medical University of Vienna),
Stefan Evers50
Estimated H-index: 50
(PHRI: Public Health Research Institute)
+ 8 AuthorsSusanne Mayer6
Estimated H-index: 6
(Medical University of Vienna)
ABSTRACTBackground: To enhance usage of health technology assessment (HTA) in decision-making, it is important to prioritise important barriers and facilitators to the uptake of HTA. This study aims to quantify and compare the relative importance of barriers and facilitators regarding the use of HTA in several European countries.Methods: A survey containing two best-worst scaling (BWS) object case studies (i.e. barriers and facilitators) were conducted among 136 policy makers and HTA researchers...
Published on Nov 1, 2017in Research in Social & Administrative Pharmacy2.72
James B. Schreiber12
Estimated H-index: 12
(Duquesne University)
Abstract Objective The purpose of this paper is to provide a brief non-mathematical introduction to Latent Class Analysis (LCA) and a demonstration for researchers new to the analysis technique in pharmacy and pharmacy administration. LCA is a mathematical technique for examining relationships among observed variables when there may be collections of unobserved categorical variables. Traditionally, LCA focused on polytomous observed variables, but recent work has extended the types of data that ...
Published on Jul 1, 2017in PharmacoEconomics3.71
Emily Lancsar21
Estimated H-index: 21
(Monash University),
Denzil G. Fiebig25
Estimated H-index: 25
(UNSW: University of New South Wales),
Arne Risa Hole19
Estimated H-index: 19
(University of Sheffield)
We provide a user guide on the analysis of data (including best–worst and best–best data) generated from discrete-choice experiments (DCEs), comprising a theoretical review of the main choice models followed by practical advice on estimation and post-estimation. We also provide a review of standard software. In providing this guide, we endeavour to not only provide guidance on choice modelling but to do so in a way that provides a ‘way in’ for researchers to the practicalities of data analysis. ...
Kei Long Cheung5
Estimated H-index: 5
(UM: Maastricht University),
Stefan Evers50
Estimated H-index: 50
(UM: Maastricht University)
+ 1 AuthorsMickaël Hiligsmann27
Estimated H-index: 27
(UM: Maastricht University)
Published on Dec 1, 2016in Health Economics Review
T Schmid3
Estimated H-index: 3
(Amgen),
Weiwei Xu1
Estimated H-index: 1
+ 1 AuthorsGalin V. Michailov1
Estimated H-index: 1
(Amgen)
Unfortunately, the original version of this article [1] contained an error. The full author list and affiliations was not included. The correct author list and affiliations can be found below. Tamara Schmida, Weiwei Xub, Shravanthi R Gandrac, Galin V Michailova a Amgen GmbH, Munich, Germany b Pharmerit International, Rotterdam, The Netherlands c Amgen Inc., Thousand Oaks, CA, USA
Published on Dec 1, 2016in Health Economics Review
Axel C. Mühlbacher16
Estimated H-index: 16
,
Anika Kaczynski5
Estimated H-index: 5
+ 1 AuthorsF. Reed Johnson35
Estimated H-index: 35
(Duke University)
Best-worst scaling (BWS), also known as maximum-difference scaling, is a multiattribute approach to measuring preferences. BWS aims at the analysis of preferences regarding a set of attributes, their levels or alternatives. It is a stated-preference method based on the assumption that respondents are capable of making judgments regarding the best and the worst (or the most and least important, respectively) out of three or more elements of a choice-set. As is true of discrete choice experiments ...
Published on Dec 1, 2016in PharmacoEconomics3.71
Kei Long Cheung5
Estimated H-index: 5
(UM: Maastricht University),
Ben F. M. Wijnen6
Estimated H-index: 6
(UM: Maastricht University)
+ 4 AuthorsMickaël Hiligsmann27
Estimated H-index: 27
(UM: Maastricht University)
Introduction Best–worst scaling (BWS) is becoming increasingly popular to elicit preferences in health care. However, little is known about current practice and trends in the use of BWS in health care. This study aimed to identify, review and critically appraise BWS in health care, and to identify trends over time in key aspects of BWS.
Published on Jun 1, 2016in Value in Health5.04
A. Brett Hauber20
Estimated H-index: 20
(RTP: Research Triangle Park),
Juan Marcos Gonzalez13
Estimated H-index: 13
(RTP: Research Triangle Park)
+ 5 AuthorsJohn F. P. Bridges27
Estimated H-index: 27
(Johns Hopkins University)
Conjoint analysis is a stated-preference survey method that can be used to elicit responses that reveal preferences, priorities, and the relative importance of individual features associated with health care interventions or services. Conjoint analysis methods, particularly discrete choice experiments (DCEs), have been increasingly used to quantify preferences of patients, caregivers, physicians, and other stakeholders. Recent consensus-based guidance on good research practices, including two re...
Published on Jan 1, 2015
Jordan J. Louviere78
Estimated H-index: 78
,
Terry N. Flynn31
Estimated H-index: 31
,
A. A. J. Marley23
Estimated H-index: 23
Preface Acknowledgments Theory and Methods: 1. Introduction and overview of the book 2. The BWS object case 3. The BWS profile case 4. The BWS multi-profile case 5. Basic models 6. Looking forward Applications - Case 1: 7. BWS object case application: attitudes towards end-of-life care Terry N. Flynn, Elisabeth Huynh and Charles Corke 8. How consumers choose wine: using best-worst scaling across countries Larry Lockshin and Eli Cohen 9. Best-worst scaling: an alternative to ratings data Geoffrey...
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