{"title":"[抑郁状态评价的研究策略]。","authors":"M de Bonis, M O Lebeaux","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>The present paper discusses the respective benefits of a latent trait model and of factorial correspondence analysis in the research strategies of depression inventory construction. Results on the processing of the same list of depressive symptoms by both analyses are presented. The fact that, in questionnaires based on latent models, each answer brings an information closely dependent on its place in the hierarchical order is underlined. The latent trait strategy construction offers an accurate way to assess how patients recover from depression.</p>","PeriodicalId":75415,"journal":{"name":"Acta psychiatrica Belgica","volume":"94 1","pages":"8-22"},"PeriodicalIF":0.0000,"publicationDate":"1994-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"[Research strategies in the evaluation of depressive states].\",\"authors\":\"M de Bonis, M O Lebeaux\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The present paper discusses the respective benefits of a latent trait model and of factorial correspondence analysis in the research strategies of depression inventory construction. Results on the processing of the same list of depressive symptoms by both analyses are presented. The fact that, in questionnaires based on latent models, each answer brings an information closely dependent on its place in the hierarchical order is underlined. The latent trait strategy construction offers an accurate way to assess how patients recover from depression.</p>\",\"PeriodicalId\":75415,\"journal\":{\"name\":\"Acta psychiatrica Belgica\",\"volume\":\"94 1\",\"pages\":\"8-22\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Acta psychiatrica Belgica\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta psychiatrica Belgica","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
[Research strategies in the evaluation of depressive states].
The present paper discusses the respective benefits of a latent trait model and of factorial correspondence analysis in the research strategies of depression inventory construction. Results on the processing of the same list of depressive symptoms by both analyses are presented. The fact that, in questionnaires based on latent models, each answer brings an information closely dependent on its place in the hierarchical order is underlined. The latent trait strategy construction offers an accurate way to assess how patients recover from depression.