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Cluster Analysis of Personal Questionnaires Compared with Principal Component Analysis
Author(s) -
RUMP E. E.
Publication year - 1974
Publication title -
british journal of social and clinical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.479
H-Index - 92
eISSN - 2044-8260
pISSN - 0007-1293
DOI - 10.1111/j.2044-8260.1974.tb00121.x
Subject(s) - principal component analysis , cluster (spacecraft) , psychology , set (abstract data type) , relation (database) , interpretation (philosophy) , clinical psychology , statistics , computer science , data mining , mathematics , programming language
When intensity levels for several symptoms are obtained by use of a personal questionnaire on a series of occasions, it is convenient to reduce the scores to a smaller set of variables by grouping symptoms. Elementary cluster analysis is suitable for this purpose, in that cluster scores are easily calculated, and their interpretation is directly meaningful in relation to the patient's progress. The advantages of cluster analysis are illustrated in comparison with the principal component analysis recommended by Slater.