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

Published on Jun 3, 2019in Journal of Medical Economics
· DOI :10.1080/13696998.2018.1553781
Kei Long Cheung6
Estimated H-index: 6
,
Susanne Mayer6
Estimated H-index: 6
(Medical University of Vienna)
+ 4 AuthorsMickaël Hiligsmann28
Estimated H-index: 28
(PHRI: Public Health Research Institute)
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 (28)
  • Citations (1)
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References28
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#2Stefan Evers (PHRI: Public Health Research Institute)H-Index: 57
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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...
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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 ...
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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. ...
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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.
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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 ...
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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
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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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