{"title":"回归标准化风险、风险比和风险差异的大样本置信区间","authors":"W.Dana Flanders, Philip H. Rhodes","doi":"10.1016/0021-9681(87)90106-8","DOIUrl":null,"url":null,"abstract":"<div><p>Several methods have been proposed for standardizing risks, risk ratios, and risk differences based on the results of logistic regression. These methods provide an alternative to direct standardization, a particularly useful approach when there are many covariates. In this paper, methods for calculating approximate confidence limits for these standardized measures are presented. A simple example, in which published data are used, illustrates the techniques and allows comparison with confidence limits calculated from the directly standardized risk ratio.</p></div>","PeriodicalId":15427,"journal":{"name":"Journal of chronic diseases","volume":"40 7","pages":"Pages 697-704"},"PeriodicalIF":0.0000,"publicationDate":"1987-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0021-9681(87)90106-8","citationCount":"100","resultStr":"{\"title\":\"Large sample confidence intervals for regression standardized risks, risk ratios, and risk differences\",\"authors\":\"W.Dana Flanders, Philip H. Rhodes\",\"doi\":\"10.1016/0021-9681(87)90106-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Several methods have been proposed for standardizing risks, risk ratios, and risk differences based on the results of logistic regression. These methods provide an alternative to direct standardization, a particularly useful approach when there are many covariates. In this paper, methods for calculating approximate confidence limits for these standardized measures are presented. A simple example, in which published data are used, illustrates the techniques and allows comparison with confidence limits calculated from the directly standardized risk ratio.</p></div>\",\"PeriodicalId\":15427,\"journal\":{\"name\":\"Journal of chronic diseases\",\"volume\":\"40 7\",\"pages\":\"Pages 697-704\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1987-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/0021-9681(87)90106-8\",\"citationCount\":\"100\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of chronic diseases\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/0021968187901068\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of chronic diseases","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/0021968187901068","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Large sample confidence intervals for regression standardized risks, risk ratios, and risk differences
Several methods have been proposed for standardizing risks, risk ratios, and risk differences based on the results of logistic regression. These methods provide an alternative to direct standardization, a particularly useful approach when there are many covariates. In this paper, methods for calculating approximate confidence limits for these standardized measures are presented. A simple example, in which published data are used, illustrates the techniques and allows comparison with confidence limits calculated from the directly standardized risk ratio.