Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/266328 
Authors: 
Year of Publication: 
2022
Citation: 
[Journal:] Statistics in Transition new series (SiTns) [ISSN:] 2450-0291 [Volume:] 23 [Issue:] 3 [Publisher:] Sciendo [Place:] Warsaw [Year:] 2022 [Pages:] 185-198
Publisher: 
Sciendo, Warsaw
Abstract: 
The measurement of preferences can be based on historical observations of consumer behaviour or on data describing consumer intentions. In the latter case, the measure-ment of preferences is performed using methods which express consumer attitudes at the time of research. However, most of these methods are very laborious, especially when a large number of objects is tested. In such cases incomplete analyses may prove useful. An incomplete analysis involves the division of objects into subgroups, so that each pair of objects appears at exactly the same frequency and all objects are in each subgroup. The purpose of the work is to compare two incomplete methods for measuring the similarity of preferences, i.e. the triad method and the tetrad method. These methods can be used whenever similarities are measured on an ordinal scale. They have been com-pared in terms of their labour intensity and ability to map the known structure of ob-jects, even when all pairs of objects in subgroups cannot be presented equally frequent-ly.
Subjects: 
measurement of preferences
triads
tetrads
multidimensional scaling
Persistent Identifier of the first edition: 
Creative Commons License: 
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Document Type: 
Article

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