A new approach to measuring Overall Liking with the Many-Facet Rasch Model

Fuzzy Nonbalanced Hedonic Scale (F-NBHS): A New Method for Treatments of Food Preference Data Collected with Hedonic Scales of Points

“…Among the various forms of fuzzy numbers, the triangular form (Figure 1) is the most used [22,27]. Triangular fuzzy numbers can be defined as a triplet (a, b, c) according to equation (1). In this case, a and c are the lower and upper extreme values, respectively, and b represents the central value of each triangular fuzzy number:…”

“…In studies of this nature, the semantic labels of linguistic variables do not express psychologically uniform spacing. erefore, the distances between underlying categories must also be different [1,9,10]. Studies indicate that the behavior of responses in central and extreme categories is different from the behavior of responses in fine categories (intermediate).…”

“…In this way, each existing category in the scale will be determined by a triangular fuzzy number or, to rephrase it, by a triplet (a, b, c) as shown in equation (1). To construct the triangular numbers associated with each of the existing categories in the scale, two factors are necessary and indispensable:…”

“…One of the most common ways of collecting food preference data is through 9-point hedonic scales. Due to its flexibility and ease of use, this type of scale is widely used [1][2][3][4][5][6]. Although hedonic scales are generally treated in a balanced way, that is, with symmetrically distributed linguistic labels, studies show that the psychometric distances between categories are different, and this may alter the results of the research [7][8][9][10].…”

“…Although hedonic scales are generally treated in a balanced way, that is, with symmetrically distributed linguistic labels, studies show that the psychometric distances between categories are different, and this may alter the results of the research [7][8][9][10]. Other features of the hedonic scales may also interfere with the results of the studies, such as the following: (i) extreme-scale effect: the intermediate points are used less frequently than the extreme points of the scale [5,[10][11][12]; (ii) central tendency effect: the center category is judged by the participants as safe for setting responses [8,10,12]; (iii) imprecision in the judgment of the answers: it implies the tendency to repeat answers [13,14]; (iv) the lack of definition of the scale is scalar or ordinal: it affects the way data analysis is performed [5,11,15,16]; (v) assignment of symmetrically spaced discrete values for each point of the scale: it reduces the mathematical level in the analysis of the data [1,10,14,[17][18][19][20].…”