{"title":"个人问卷聚类分析与主成分分析的比较","authors":"E. E. Rump","doi":"10.1111/J.2044-8260.1974.TB00121.X","DOIUrl":null,"url":null,"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.","PeriodicalId":76614,"journal":{"name":"The British journal of social and clinical psychology","volume":"45 1","pages":"283-292"},"PeriodicalIF":0.0000,"publicationDate":"1974-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Cluster Analysis of Personal Questionnaires Compared with Principal Component Analysis\",\"authors\":\"E. E. Rump\",\"doi\":\"10.1111/J.2044-8260.1974.TB00121.X\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":76614,\"journal\":{\"name\":\"The British journal of social and clinical psychology\",\"volume\":\"45 1\",\"pages\":\"283-292\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1974-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The British journal of social and clinical psychology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1111/J.2044-8260.1974.TB00121.X\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The British journal of social and clinical psychology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1111/J.2044-8260.1974.TB00121.X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cluster Analysis of Personal Questionnaires Compared with Principal Component Analysis
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.
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