0509, 2025

One citation, one vote! A new approach for analysing check-all-that-apply (CATA) data using L1-norm methods

John Castura/ September 5, 2025/ Peer-reviewed Paper

A unified framework is provided for analysing check-all-that-apply (CATA) product data following the “one citation, one vote” principle. CATA data arise from studies where A assessors evaluate P products by describing samples by checking all of the T terms that apply. Giving every citation the same weight, regardless of the assessor, product, or term, leads to analyses based on the L1 norm where the median absolute

0309, 2025

Comparison of check-all-that-apply product evaluations in different conditions using an L1-norm framework

John Castura/ September 3, 2025/ Poster, Rapid-fire talk

In sensory evaluation, consumers often evaluate products by answering check-all-that-apply (CATA) questions. These questions instruct the consumer to check all terms in a list that describe the product, where checking a term is called a citation. When all products are evaluated by all consumers under two conditions, the CATA data can be organized into a four-dimensional array (assessors, products, terms,

1808, 2025

One citation, one vote! A new approach for analyzing check-all-that-apply (CATA) data using L1 norm methods

John Castura/ August 18, 2025/ Oral Presentation

2502, 2025

One citation, one vote! A new approach for analysing check-all-that-apply (CATA) data in sensometrics, using L1 norm methods

John Castura/ February 25, 2025/ Preprint

A unified framework is provided for analysing check-all-that-apply (CATA) product data following the “one citation, one vote” principle. CATA data arise from studies where A consumers evaluate P products by describing samples by checking all of the T terms that apply. Giving every citation the same weight, regardless of the assessor, product, or term, leads to analyses based on the

3107, 2024

Sugar replacement in chocolate-flavored milk: Differences in liking of sweetener system relates to temporal perception

John Castura/ July 31, 2024/ Peer-reviewed Paper

Chocolate-flavored milk contributes to excessive intake of added sugars among children and adolescents, which why it is a good candidate product for sucrose replacement. This study investigates how replacing sucrose partially or completely with different sweetener systems affects the sensory profile and consumer liking. Five chocolate-flavored milk treatments were formulated, varying in sucrose replacement level (partial: 58%; complete: 100%) and

2107, 2023

An approach for clustering consumers by their top-box and top-choice responses

John Castura/ July 21, 2023/ Peer-reviewed Paper

Cluster analysis is often used to group consumers based on their hedonic responses to products. We give a motivating example in which conventional cluster analyses converge on a solution where consumers do not agree on which products they like. We show why this occurs. We state a goal: to group together consumers who have a shared opinion of which products

0911, 2022

Clustering consumers based on their hedonic responses

John Castura/ November 9, 2022/ Oral Presentation/ 0 comments

Consumers are diverse in their product perceptions. But within the consumer population there are often consumer segments whose product perceptions are relatively homogeneous. To discover these consumer segments, consumers’ product-related responses are submitted to a cluster analysis. The particular cluster analysis is chosen by the researcher. But the choice of clustering algorithm can have profound consequences on the clustering solution

0403, 2022

Clustering consumers based on product discrimination in check-all-that-apply (CATA) data

John Castura/ March 4, 2022/ Peer-reviewed Paper/ 0 comments

Consumers can be clustered based on their product-related check-all-that-apply (CATA) responses. We identify two paradoxes that can occur if these clusters are derived from conventional similarity coefficients. The first paradox is that clustering similar consumers can nullify within-cluster sensory differentiation of products. The second paradox is that consumers who check many attributes yet disagree can be clustered together, whereas consumers

0608, 2019

Analysis of sensory check-all-that-apply (CATA) data which includes the evaluation of a single ideal product

John Castura/ August 6, 2019/ Poster/ 0 comments

When evaluating samples in sensory tests, consumers are sometimes asked not only about real samples but also about imagined ideal products. Check-all-that-apply (CATA) questions are one way to understand consumers’ perceptions of products and their ideal product. We propose the following statistical analyses of consumer CATA data: (i) confidence intervals for head-to-head comparisons based on CATA data; (ii) panel (dis)agreement

2807, 2014

The Role of Imputation in Clustering BIB Data

Sara King/ July 28, 2014/ Tutorial/ 0 comments

Clustering consumer data reveals important information to help refine products for specific market segments. There are compelling reasons to use incomplete block designs to collect consumer data; however, this presents the challenge of dealing with missing data. The purpose of this workshop is to investigate the effect of different imputation techniques on the results of cluster analysis of balanced-incomplete-block (BIB)