<p> Workshop proposal (satellite to 13 th Sensometrics, Brighton, 2016)</p><p>Title: Data analysis of Check-All-That-Apply (CATA) and allied methods Teachers: Michael Meyners, John Castura Software: Data collection using Compusense at-hand software Duration: 0.5 day Audience: Sensometricians / statisticians and sensory scientists who want to learn about the (design and) analysis of CATA questions Background: basic understanding of statistics is advantageous </p><p>Aims and Scope</p><p>Check-All-That-Apply (CATA) questionnaires have seen a widespread use recently. The task for the participant is to select those attributes from a list of attributes that he/she consider as being applicable for the sample under investigation. A variant of this is the so-called applicability testing; in that approach, participants need to check for each attribute whether it applies or not.</p><p>In this workshop, some relevant aspects of designing CATA studies are discussed in order to minimize undesired effects from, for instance, satisficing and order effects. Hands-on data collection will be conducted by workshop participants to illustrate these effects.</p><p>Subsequently, some of the existing approaches to analyze data obtained from such a study will be reviewed, including correspondence analysis. Depending on the availability of liking scores and CATA evaluations on a hypothetical ideal product, complementary ways to analyze the data may provide additional insight. Some of these extensions have been recently proposed by the workshop leaders. Emphasis will be given to methods published recently for detecting product differences, characterizing products, revealing attribute correlations, identifying (positive and negative) hedonic drivers, and focusing reformulation efforts. </p><p>Analysis methods for Rate-All-That-Apply (RATA) data and Temporal Check-All- That-Apply (TCATA) will each be discussed briefly, with emphasis on approaches for detecting product differences and for characterizing products.</p><p>Selected References:</p><p>Meyners, M. (2016). Testing for differences between impact of attributes in penalty- lift analysis. 29–33. Food Quality and Preference, 47A, http://dx.doi.org/10.1016/j.foodqual.2014.11.001 </p><p>Meyners, M., Castura, J. C., Carr, B. T. (2013). Existing and new approaches for the analysis of CATA data. Food Quality and Preference, 30, 309-319. http://dx.doi.org/10.1016/j.foodqual.2013.06.010</p><p>Castura, J. C., Antúnez, L., Giménez, A., Ares, G. (2016). Temporal Check-All-That- Apply (TCATA): A Novel Temporal Sensory Method for Characterizing Products. Food Quality and Preference, 47A, 79-90. http://dx.doi.org/10.1016/j.foodqual.2015.06.017</p>