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|a Hanagal, David D.
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|a Modeling Survival Data Using Frailty Models
|h [electronic resource] :
|b Second Edition /
|c by David D. Hanagal.
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| 250 |
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|a 1st ed. 2019.
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| 264 |
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|a Singapore :
|b Springer Singapore :
|b Imprint: Springer,
|c 2019.
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| 300 |
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|a XXIV, 295 p. 50 illus., 15 illus. in color.
|b online resource.
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|a Industrial and Applied Mathematics,
|x 2364-6837
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|a Springer eBook Collection
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|a 1 Introduction to Survival Analysis -- 2 Some Parametric Models -- 3 Nonparametric and Semiparametric Models -- 4 The Frailty Concept -- 5 Various Frailty Models -- 6 Estimation Methods for Shared Frailty Models -- 7 Analysis of Survival Data in Shared Frailty Models -- 8 Tests of Hypotheses in Frailty Models -- 9 Shared Gamma Frailty Models -- 10 Shared Gamma Frailty Models Based on Reversed Hazard -- 11 Bivariate Frailty Models and Estimation Methods -- 12 Correlated Frailty Models -- 13 Correlated Gamma and Inverse Gaussian Frailty Models -- 14 Correlated Gamma Frailty Models Based on Reversed Hazard.
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| 520 |
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|a This book presents the basic concepts of survival analysis and frailty models, covering both fundamental and advanced topics. It focuses on applications of statistical tools in biology and medicine, highlighting the latest frailty-model methodologies and applications in these areas. After explaining the basic concepts of survival analysis, the book goes on to discuss shared, bivariate, and correlated frailty models and their applications. It also features nine datasets that have been analyzed using the R statistical package. Covering recent topics, not addressed elsewhere in the literature, this book is of immense use to scientists, researchers, students and teachers.
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