| 書(shū)目名稱 | Regression Methods in Biostatistics | | 副標(biāo)題 | Linear, Logistic, Su | | 編輯 | Eric Vittinghoff,David V. Glidden,Charles E. McCul | | 視頻video | http://file.papertrans.cn/826/825513/825513.mp4 | | 概述 | Short and to the point so that the important issues and similarities between the methods, rather than the differences, shine through.Provides a unified introduction to the regression methods listed in | | 叢書(shū)名稱 | Statistics for Biology and Health | | 圖書(shū)封面 |  | | 描述 | .This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, repeated-measures models for longitudinal and hierarchical outcomes, and generalized linear models for counts and other outcomes. ..Treating these topics together takes advantage of all they have in common. The authors point out the many-shared elements in the methods they present for selecting, estimating, checking, and interpreting each of these models. They also show that these regression methods deal with confounding, mediation, and interaction of causal effects in essentially the same way. ..The examples, analyzed using Stata, are drawn from the biomedical context but generalize to other areas of application. While a first course in statistics is assumed, a chapter reviewing basic statistical methods is included. Some advanced topics are covered but the presentation remains intuitive. A brief introduction to regression analysis of complex surveys and notes for further reading are provided.. | | 出版日期 | Book 2012Latest edition | | 關(guān)鍵詞 | adopted-textbook; applied regression methods for biomedical research; confounding, mediation, and inte | | 版次 | 2 | | doi | https://doi.org/10.1007/978-1-4614-1353-0 | | isbn_softcover | 978-1-4899-9854-5 | | isbn_ebook | 978-1-4614-1353-0Series ISSN 1431-8776 Series E-ISSN 2197-5671 | | issn_series | 1431-8776 | | copyright | Springer Science+Business Media, LLC 2012 |
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