On the analysis of Rate-All-That-Apply (RATA) data

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Comparison of Rate-All-That-Apply and Descriptive Analysis for the Sensory Profiling of Wine (2018, methodology): “Meyners et al. (2016), investigating the analysis of RATA-derived data, concluded that transforming the absence of a check for an attribute to a score of 0 (and subsequent parametric inference based on F-tests) provides valid statistical inference for RATA data, even though not all assumptions for…”
Consumers’ perception of bakery products with insect fat as partial butter replacement (2020, methodology): “Furthermore, Principal Component Analysis (PCA) was performed using Dravniek’s scores (Dravnieks, 1982) for the emotional/sensory attributes separately to graphical visualize the emotional/sensory space of each bakery product (Meyners et al., 2016).”
Comparison of Rate-All-That-Apply (RATA) and Descriptive sensory Analysis (DA) of model double emulsions with subtle perceptual differences (2017, result): “In order to fully investigate the data and compare results to similar studies (Ares et al., 2014; Meyners et al., 2016), RATA data were explored by the frequency of term selection only (treated as CATA data and not taking into account the intensity ratings of selected terms) as well as their…”