Analysis of Survival Data with Dependent Censoring
Copula-Based Approaches
Seiten
2018
|
2018 ed.
Springer Verlag, Singapore
978-981-10-7163-8 (ISBN)
Springer Verlag, Singapore
978-981-10-7163-8 (ISBN)
This book introduces readers to copula-based statistical methods for analyzing survival data involving dependent censoring. Primarily focusing on likelihood-based methods performed under copula models, it is the first book solely devoted to the problem of dependent censoring.
The book demonstrates the advantages of the copula-based methods in the context of medical research, especially with regard to cancer patients’ survival data. Needless to say, the statistical methods presented here can also be applied to many other branches of science, especially in reliability, where survival analysis plays an important role.
The book can be used as a textbook for graduate coursework or a short course aimed at (bio-) statisticians. To deepen readers’ understanding of copula-based approaches, the book provides an accessible introduction to basic survival analysis and explains the mathematical foundations of copula-based survival models.
The book demonstrates the advantages of the copula-based methods in the context of medical research, especially with regard to cancer patients’ survival data. Needless to say, the statistical methods presented here can also be applied to many other branches of science, especially in reliability, where survival analysis plays an important role.
The book can be used as a textbook for graduate coursework or a short course aimed at (bio-) statisticians. To deepen readers’ understanding of copula-based approaches, the book provides an accessible introduction to basic survival analysis and explains the mathematical foundations of copula-based survival models.
Takeshi Emura, Chang Gung University Yi-Hau Chen, Institute of Statistical Science, Academia Sinica
Chapter 1: Setting the scene.- Chapter 2: Introduction to survival analysis.- Chapter 3: Copula models for dependent censoring.- Chapter 4: Gene selection under dependent censoring.- Chapter 5: The joint frailty-copula model for meta-analysis.- Chapter 6:High-dimensional covariates in the joint frailty-copula model.- Chapter 7:Dynamic prediction of time-to-death. Chapter 8: Future developments.- Appendix.
| Erscheinungsdatum | 21.04.2018 |
|---|---|
| Reihe/Serie | JSS Research Series in Statistics | SpringerBriefs in Statistics |
| Zusatzinfo | 10 Illustrations, black and white; XIII, 84 p. 10 illus. |
| Verlagsort | Singapore |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik |
| Medizin / Pharmazie | |
| Naturwissenschaften ► Biologie | |
| Sozialwissenschaften ► Soziologie ► Empirische Sozialforschung | |
| Schlagworte | Competing Risk • Compound Covariate • Cox Regression • Kendall’s Tau • Meta-analysis • Semi-Competing Risk • Surrogate Endpoint |
| ISBN-10 | 981-10-7163-2 / 9811071632 |
| ISBN-13 | 978-981-10-7163-8 / 9789811071638 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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