Preference Paths and Their Kaizen Tasks for Small Samples.

Background: Stated preference research currently lacks a form of evidence that is well suited for small samples. A preference path is a sequence of two or more choices showing the evolution of an object following an adaptive process. Objectives: The aims were to introduce preference paths and their...

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Publicado en:Patient Vol. 15; no. 2; pp. 187 - 197
Autores principales: Craig, Benjamin Matthew, Rand, Kim, Hartman, John D.
Formato: equations & formulas pictorial research tables/charts Journal Article
Publicado: Springer Nature Mar2022
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Mar2022
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s40271-021-00541-z
        155396977
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        atl: Preference Paths and Their Kaizen Tasks for Small Samples.
      aug:
        au:
          Craig, Benjamin Matthew
          Rand, Kim
          Hartman, John D.
        affil: Department of Economics, University of South Florida, Tampa, Florida, USA
      sug:
        subj:
          Decision Making
          Task Performance and Analysis
          Behavioral Changes
          Patient Preference
          Human
          Quality-Adjusted Life Years
          Interviews
          Adaptation, Psychological
          Games
          Attitude to Death
          Convenience Sample
      ab: Background: Stated preference research currently lacks a form of evidence that is well suited for small samples. A preference path is a sequence of two or more choices showing the evolution of an object following an adaptive process. Objectives: The aims were to introduce preference paths and their kaizen tasks and to demonstrate how to analyze their evidence using a small sample. Methods: Twenty respondents were assigned the same 16 profiles generated from an orthogonal array based on the five attributes of the EQ-5D-5L descriptive system. Each kaizen task began with an opt-out paired comparison (i.e., choosing between the initial 10-year profile and the opt-out "dying immediately"), followed by choosing three changes, and ended with a second paired comparison (final profile versus opt-out) if the respondent chose opt-out initially. By maximum likelihood with respondent clusters, we estimated the 20 main effects using conditional logit and Zermelo–Bradley–Terry (ZBT) specifications. Results: Apart from demonstrating heterogeneity and profile effects, all main effect estimates were non-negative, and most were significant (15 for logit and all 20 for ZBT; p value < 0.05). Under the logit and ZBT specifications, the value of the worst EQ-5D-5L profile (55555) is − 0.920 quality-adjusted life years (QALYs) or − 1.478 QALYs, respectively. Furthermore, the findings illustrate a log-linear relationship between the logit and ZBT main effects. Conclusion: This paper demonstrates the feasibility of a stated-preference study that estimates 20 main effects using path evidence from 20 respondents (16 kaizen tasks, 15-min interviews). This approach shows promise for future application in stated-preference research, particularly in small samples.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        pictorial
        research
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      ougenre: Article
    language: English
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