10. Frequency Counts and Check-All-That-Apply (CATA)

  1. Harry T. Lawless Ph.D. Professor Emeritus

Published Online: 19 JUL 2013

DOI: 10.1002/9781118684818.ch10

Quantitative Sensory Analysis: Psychophysics, Models and Intelligent Design

Quantitative Sensory Analysis: Psychophysics, Models and Intelligent Design

How to Cite

Lawless, H. T. (2013) Frequency Counts and Check-All-That-Apply (CATA), in Quantitative Sensory Analysis: Psychophysics, Models and Intelligent Design, John Wiley & Sons, Chichester, UK. doi: 10.1002/9781118684818.ch10

Author Information

  1. Cornell University

Publication History

  1. Published Online: 19 JUL 2013
  2. Published Print: 30 AUG 2013

ISBN Information

Print ISBN: 9780470673461

Online ISBN: 9781118684818

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Keywords:

  • advertising claim;
  • check-all-that-apply (CATA);
  • frequency counts;
  • multivariate techniques;
  • penalty analysis;
  • principal components analysis (PCA)

Summary

Frequency counts of responses in consumer research can be found in a number of situations. Two of the most common are counts of the responses to open-ended questions and checklist data such as check-all-that-apply (CATA). The simplest, easiest, and maybe quickest analysis is a simple comparison of two proportions or frequencies using a binomial test on proportions. Many consumer tests involve a monadic sequential design, in which two or more products are viewed by all participants. A number of multivariate techniques are available for analyzing CATA data. These methods can produce product and attribute maps analogous to using principal components analysis (PCA) or generalized Procrustes analysis (GPA) for rating scale data. This chapter discusses the difference from ideal and penalty analysis. It finally talks about the testing against a fixed benchmark or single proportion, as one might do for substantiating an advertising claim based on a fixed percentage or ratio.