{"title":"计算回归均值效应:一种比较分析","authors":"Nissan Levin , Jacob Zahavi","doi":"10.1002/(SICI)1522-7138(199623)10:4<29::AID-DIR3>3.0.CO;2-Z","DOIUrl":null,"url":null,"abstract":"<div><p>Various methods are compared to calculate the regression-to-the-mean (RTM) effect in segmentation analysis, based on the results of a test mailing, distinguishing between the case of no-prior, non-parametric, and parametric knowledge on the distribution of the response rates of segments across the list. The advantages and disadvantages of each method and its implication for decision making are discussed.</p></div>","PeriodicalId":100774,"journal":{"name":"Journal of Direct Marketing","volume":"10 4","pages":"Pages 29-40"},"PeriodicalIF":0.0000,"publicationDate":"1996-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/(SICI)1522-7138(199623)10:4<29::AID-DIR3>3.0.CO;2-Z","citationCount":"4","resultStr":"{\"title\":\"Calculating the regression-to-the-mean effect: A comparative analysis\",\"authors\":\"Nissan Levin , Jacob Zahavi\",\"doi\":\"10.1002/(SICI)1522-7138(199623)10:4<29::AID-DIR3>3.0.CO;2-Z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Various methods are compared to calculate the regression-to-the-mean (RTM) effect in segmentation analysis, based on the results of a test mailing, distinguishing between the case of no-prior, non-parametric, and parametric knowledge on the distribution of the response rates of segments across the list. The advantages and disadvantages of each method and its implication for decision making are discussed.</p></div>\",\"PeriodicalId\":100774,\"journal\":{\"name\":\"Journal of Direct Marketing\",\"volume\":\"10 4\",\"pages\":\"Pages 29-40\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1002/(SICI)1522-7138(199623)10:4<29::AID-DIR3>3.0.CO;2-Z\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Direct Marketing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0892059196703087\",\"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 Direct Marketing","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0892059196703087","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Calculating the regression-to-the-mean effect: A comparative analysis
Various methods are compared to calculate the regression-to-the-mean (RTM) effect in segmentation analysis, based on the results of a test mailing, distinguishing between the case of no-prior, non-parametric, and parametric knowledge on the distribution of the response rates of segments across the list. The advantages and disadvantages of each method and its implication for decision making are discussed.
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