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Titlebook: Regression Methods in Biostatistics; Linear, Logistic, Su Eric Vittinghoff,Stephen C. Shiboski,Charles E. Mc Book 20051st edition Springer-

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書目名稱Regression Methods in Biostatistics
副標(biāo)題Linear, Logistic, Su
編輯Eric Vittinghoff,Stephen C. Shiboski,Charles E. Mc
視頻videohttp://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Titlebook: Regression Methods in Biostatistics; Linear, Logistic, Su Eric Vittinghoff,Stephen C. Shiboski,Charles E. Mc Book 20051st edition Springer-
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(guān)鍵詞Generalized linear model; Logistic Regression; Regression analysis; Stata; Survival analysis; Variance; ap
版次1
doihttps://doi.org/10.1007/b138825
isbn_ebook978-0-387-27255-9Series ISSN 1431-8776 Series E-ISSN 2197-5671
issn_series 1431-8776
copyrightSpringer-Verlag New York 2005
The information of publication is updating

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pinning centers. First, the statistical theory of Labusch is discussed. This theory predicts that the pinning force density has non-zero values for the elementary pinning force above the threshold value. This condition is identical to the condition of the hysteresis loss shown in Sect.?., and this t
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Logistic Regression,t example, it would be clearly important to control for age in addition to behaviors potentially linked to infection risk. In the second example, a number of demographic and clinical variables may be related to both the mortality outcome and treatment regime. Both of these examples are characterized
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Book 20051st editionheir 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
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