Let us consider that you have surveyed N assessors for P products (one of the products can be a virtual, often ideal, product) on K attributes. The CATA data analysis tool of XLSTAT has been developed to automate the analysis of CATA data.
Ares et al. (2014), recommend that the order of the CATA questions is randomized for each assessor to improve the reproducibility CATA analysis in XLSTAT If participants are asked to give an overall rating to each product of the study, then further analyses and preference modelling is possible. Other questions on different scales may be added to relate the attributes to preferences and liking scores. If it does, he/she simply needs to check the attribute, otherwise he does not need to do anything.
The principle is that each assessor receives a questionnaire with attributes or descriptors that the respondent may feel, or not, that they apply to one or more products. They are easy to set up and easy for participants to answer. CATA surveys allow to focus on consumers, more representative of the market, instead of trained assessors. What is CATA (check-all-that-apply) analysis?ĬATA ( check-all-that-apply) surveys have become more and more popular for sensory product characterization since 2007, when it was presented by Adams et al.
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