Statistical and Thurstonian models for the A-not A protocol with and without sureness

Publication: Research - peer-reviewJournal article – Annual report year: 2011

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The A-not A protocol with sureness produce multinomial observations that are traditionally analyzed with statistical methods for contingency tables or by calculation of an R-index. In this paper it is shown that the Thurstonian model for the A-not A protocol can be written as a cumulative link model including the binormal unequal variances model. The model is extended to allow for explanatory variables and we illustrate how consumer differences can be modeled within the Thurstonian framework on a consumer study of packet soup conducted by Unilever. The extension also allows several test-product variations to be analyzed in the same model providing additional insight and reduced experimental costs. The effects of explanatory variables on the Thurstonian delta, the sensitivity (AUC), the ROC curve and the response category thresholds are discussed in detail. All statistical methods are implemented in the free R-package ordinal (http://www.cran.r-project.org/package=ordinal/).
Original languageEnglish
JournalFood Quality and Preference
Publication date2011
Volume22
Issue6
Pages542-549
ISSN0950-3293
DOIs
StatePublished
CitationsWeb of Science® Times Cited: 9

Keywords

  • ROC curves, R-program, Signal detection theory, Cumulative link models, Thurstonian models, Ordinal regression models
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