| 書目名稱 | Regression with Linear Predictors | | 編輯 | Per Kragh Andersen,Lene Theil Skovgaard | | 視頻video | http://file.papertrans.cn/826/825522/825522.mp4 | | 概述 | Highlights similarities between regression models for quantitative, binary and survival time outcomes through construction of a linear predictor and emphasizes interpretation of effects and reparametr | | 叢書名稱 | Statistics for Biology and Health | | 圖書封面 |  | | 描述 | This is a book about regression analysis, that is, the situation in statistics where the distribution of a response (or outcome) variable is related to - planatory variables (or covariates). This is an extremely common situation in the application of statistical methods in many ?elds, andlinear regression,- gistic regression, and Cox proportional hazards regression are frequently used for quantitative, binary, and survival time outcome variables, respectively. Several books on these topics have appeared and for that reason one may well ask why we embark on writing still another book on regression. We have two main reasons for doing this: 1. First, we want to highlightsimilaritiesamonglinear,logistic,proportional hazards,andotherregressionmodelsthatincludealinearpredictor. These modelsareoftentreatedentirelyseparatelyintextsinspiteofthefactthat alloperationsonthemodelsdealingwiththelinearpredictorareprecisely the same, including handling of categorical and quantitative covariates, testing for linearity and studying interactions. 2. Second, we want to emphasize that, for any type of outcome variable, multiple regression models are composed of simple building blocks that areaddedtoget | | 出版日期 | Textbook 2010 | | 關鍵詞 | Cox; Logistic Regression; Radiologieinformationssystem; SAS; linear regression | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4419-7170-8 | | isbn_softcover | 978-1-4614-2627-1 | | isbn_ebook | 978-1-4419-7170-8Series ISSN 1431-8776 Series E-ISSN 2197-5671 | | issn_series | 1431-8776 | | copyright | Springer Science+Business Media LLC 2010 |
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