Open AccessMultidimensional unfolding analyses of ranking data for groups
Author(s) -
Hojo Hiroshi
Publication year - 1998
Publication title -
japanese psychological research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.392
H-Index - 30
eISSN - 1468-5884
pISSN - 0021-5368
DOI - 10.1111/1468-5884.00088
Subject(s) - ranking (information retrieval) , space (punctuation) , point (geometry) , ideal point , feature (linguistics) , computer science , ideal (ethics) , group (periodic table) , probabilistic logic , statistical model , mathematics , data mining , artificial intelligence , epistemology , linguistics , philosophy , chemistry , geometry , organic chemistry , operating system
One probabilistic version of Coombs' unfolding model called the MMUR (Marginalization model for the Multidimensional Unfolding analysis of Ranking data) is extended to treat ranking data for groups. One favorable feature of the model is that it can both take into consideration individual differences without estimating the subject parameters and capture the differences between the groups in a systematic manner. Another advantage lies in the fact that one can see the group differences in the geometrical point configuration, since the model shows how the ideal points of the groups differ from each other in space. Four applications are provided which demonstrate that the model is useful for clarifying systematic differences in this type of data.