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)
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...
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