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A statistical paradigm to evaluate homogeneity within subjects and within tasks
Author(s) -
Gliner Gail S.
Publication year - 1982
Publication title -
british journal of mathematical and statistical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.157
H-Index - 51
eISSN - 2044-8317
pISSN - 0007-1102
DOI - 10.1111/j.2044-8317.1982.tb00646.x
Subject(s) - homogeneity (statistics) , computer science , task (project management) , statistical analysis , cognitive psychology , artificial intelligence , statistics , psychology , machine learning , mathematics , management , economics
A statistical paradigm proposed by Hubert et al. (1981) for evaluating the pattern of cross‐classified proximity data can be used to assess homogeneity between responses for the same subjects on two different tasks, and conversely, for the same tasks over different subjects. The paradigm involves ‘blocking’ on one variable while evaluating the effects of the second. As an example using a similarity rating task and a sorting task on the same animal names, the increase of within subject and within task correlations was confirmed.