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A bayesian hierarchical modeling approach for the estimation of demand curves from hypothetical purchase tasks administered in an experimental setting.

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Title: A bayesian hierarchical modeling approach for the estimation of demand curves from hypothetical purchase tasks administered in an experimental setting.
Authors: McBride, Zoe Gibbs1 (AUTHOR) zmcbride@stat.byu.edu, Wang, Xiaojing2 (AUTHOR), Moore, Timothy E.2 (AUTHOR), Mead-Morse, Erin3 (AUTHOR)
Source: Journal of Applied Statistics. Jul2026, p1-30. 30p. 7 Illustrations.
Database: Business Source Ultimate
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Header DbId: bsu
DbLabel: Business Source Ultimate
An: 195116127
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1080/02664763.2026.2697912
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 30
        StartPage: 1
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      – TitleFull: A bayesian hierarchical modeling approach for the estimation of demand curves from hypothetical purchase tasks administered in an experimental setting.
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            NameFull: McBride, Zoe Gibbs
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            NameFull: Wang, Xiaojing
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            NameFull: Moore, Timothy E.
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            NameFull: Mead-Morse, Erin
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            – D: 04
              M: 07
              Text: Jul2026
              Type: published
              Y: 2026
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            – Type: issn-print
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            – TitleFull: Journal of Applied Statistics
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