Preference Paths and Their Kaizen Tasks for Small Samples

Benjamin Matthew Craig (), Kim Rand and John D. Hartman
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Benjamin Matthew Craig: University of South Florida
Kim Rand: Akershus University Hospital
John D. Hartman: University of West Florida

The Patient: Patient-Centered Outcomes Research, 2022, vol. 15, issue 2, No 5, 187-196

Abstract: Abstract 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

Date: 2022
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DOI: 10.1007/s40271-021-00541-z

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