Modeling Survival Data Using Frailty Models Second Edition /

• Κύριος συγγραφέας: Hanagal, David D. (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Σειρά: Industrial and Applied Mathematics,
• Θέματα: Statistics .; Computer simulation.; Statistics for Life Sciences, Medicine, Health Sciences.; Bayesian Inference.; Simulation and Modeling.

 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. 

 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.