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Modeling Survival Data Using Frailty Models
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Catalogue Information
Field name
Details
Dewey Class
519.5
Title
Modeling Survival Data Using Frailty Models ([EBook]) / by David D. Hanagal.
Author
Hanagal, David D.
Other name(s)
SpringerLink (Online service)
Edition statement
Second Edition
Publication
Singapore : Springer Singapore , 2019.
Physical Details
XXIV, 295 pages, 50 illus., 15 illus. in color. : online resource.
Series
Industrial and Applied Mathematics
ISBN
9789811511813
Summary Note
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.:
Contents note
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.
System details note
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users).
Internet Site
https://doi.org/10.1007/978-981-15-1181-3
Links to Related Works
Subject References:
Bayesian Inference
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Computer simulation
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Simulation and Modeling
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Statistics
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Statistics for Life Sciences, Medicine, Health Sciences
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Authors:
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Hanagal, David D.
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Corporate Authors:
SpringerLink (Online service)
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Series:
Industrial and Applied Mathematics
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Classification:
519.5
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