| 書目名稱 | Regression Methods in Biostatistics |
| 副標題 | Linear, Logistic, Su |
| 編輯 | Eric Vittinghoff,Stephen C. Shiboski,Charles E. Mc |
| 視頻video | http://file.papertrans.cn/826/825514/825514.mp4 |
| 概述 | Short and to the point so that the important issues and similarities between the methods, rather than the differences, shine through.Includes supplementary material: .Request lecturer material: |
| 叢書名稱 | Statistics for Biology and Health |
| 圖書封面 |  |
| 描述 | Theprimarybiostatisticaltoolsinmodernmedicalresearcharesingle-outcome, multiple-predictor methods: multiple linear regression for continuous o- comes, logistic regression for binary outcomes, and the Cox proportional h- ardsmodelfortime-to-eventoutcomes. Morerecently,generalizedlinearm- els and regression methods for repeated outcomes have come into widespread use in the medical research literature. Applying these methods and interpr- ing the results requires some introduction. However, introductory statistics courses have no time to spend on such topics and hence they are often r- egated to a third or fourth course in a sequence. Books tend to have either very brief coverage or to be treatments of a single topic and more theoretical than the typical researcher wants or needs. Our goal in writing this book was to provide an accessible introduction to multipredictor methods, emphasizing their proper use and interpretation. We feel strongly that this can only be accomplished by illustrating the te- niques using a variety of real datasets. We have incorporated as little theory as feasible. Further, we have tried to keep the book relatively short and to the point. Our hope in doing so |
| 出版日期 | Book 20051st edition |
| 關鍵詞 | Generalized linear model; Logistic Regression; Regression analysis; Stata; Survival analysis; Variance; ap |
| 版次 | 1 |
| doi | https://doi.org/10.1007/b138825 |
| isbn_ebook | 978-0-387-27255-9Series ISSN 1431-8776 Series E-ISSN 2197-5671 |
| issn_series | 1431-8776 |
| copyright | Springer-Verlag New York 2005 |
|Archiver|手機版|小黑屋|
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