MANUAL Published: 01 January 2009
MNL11503M

Appendix V: Preference Mapping from JAR Data Using Tree-Based Regressions

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Penalty analysis offers a method to consider the individual effects of JAR ratings on Overall Liking (OAL), but does not provide a way to assess the impacts of simultaneous changes in JAR ratings on Overall Liking. Standard multiple regression is of limited use in this situation because of its strong assumptions of linearity. A form of non-parametric regression, which we will refer to as “tree-based” regression, removes that assumption and allows you to determine the combinations of the JAR ratings that have the strongest impact on Overall Liking. There are wide variety of “tree-based” regressions packages available, such as CART, MARS, KnowledgeSeeger, and SPSS AnswerTree, as well as free implementations such as part in R. This example will use MARS (multivariate adaptive regression splines) as its example [1]. This is commercial software, sold by Salford Systems (http://www.salfordsystems.com/) [2].

Author Information

Meullenet, Jean-Francois
University of Arkansas, Fayetteville, AR
Xiong, Rui
University of Arkansas, Fayetteville, AR
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Developed by Committee: E18
Pages: 90–93
DOI: 10.1520/MNL11503M
ISBN-EB: 978-0-8031-6739-1
ISBN-13: 978-0-8031-7010-0