Multivariate analyses are commonly used to study differences among items in a multidimensional space and to relate these findings to hedonic assessments of the same items. But there are numerous methods in use and the purpose of this article is to review these methods from a process standpoint. Specifically, this article considers the process assumptions behind several of the popular methods for multivariate mapping of hedonic data and argues that experimenters should consider how their data arise so that they can correctly interpret their findings. Among the methods considered in this article are models based on the hedonic continuum, internal and external preference mapping, and deterministic and probabilistic unfolding of preference and liking.
This article appears as:
Ennis, D. M. and Ennis, J. M. Mapping hedonic data: A process perspective. Journal of Sensory Studies, 28, 324-334.
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Mapping hedonic data: A process perspective
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