Cluster Analysis of Personal Questionnaires Compared with Principal Component Analysis
British Journal of Social and Clinical PsychologyPublished 1 September 1974
E. E. Rump
Citations7
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
Abstract
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.
Keywords
Computer Science