Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/18986
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dc.contributor.authorCheung, KL-
dc.contributor.authorMayer, S-
dc.contributor.authorSimon, J-
dc.contributor.authorde Vries, H-
dc.contributor.authorEvers, SMAA-
dc.contributor.authorKremer, IEH-
dc.contributor.authorHiligsmann, M-
dc.date.accessioned2019-08-23T08:45:59Z-
dc.date.available2018-12-17-
dc.date.available2019-08-23T08:45:59Z-
dc.date.issued2018-12-17-
dc.identifier.citationJournal of Medical Economics, 2019, 22 (6), pp. 509 - 515en_US
dc.identifier.issn1369-6998-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/18986-
dc.description.sponsorshipKLC received financial support for his research stay at the Department of Health Economics, Center for Public Health, Medical University of Vienna through the ‘Erasmus+ staff mobility grant’.en_US
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.rightsThis is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Medical Economics on 17 December 2018, available online: https://www.tandfonline.com/doi/abs/10.1080/13696998.2018.1553781.-
dc.subjectanalysisen_US
dc.subjectbest–worst scalingen_US
dc.subjectcomparisonen_US
dc.subjectmethodsen_US
dc.subjectobject caseen_US
dc.titleComparison of statistical analysis methods for object case best–worst scalingen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1080/13696998.2018.1553781-
dc.relation.isPartOfJournal of Medical Economics-
pubs.publication-statusPublished-
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