Analysis of Survival Data with Dependent Censoring
Copula-Based Approaches
Authors: Emura, Takeshi, Chen, Yi-Hau
Free Preview- The first book devoted to the problem of dependent censoring
- An essential textbook on survival analysis accessible to students, (bio-)statisticians, mathematicians, and medical researchers alike
- Written by leading statisticians in the field of survival analysis
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- About this book
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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.
- About the authors
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Takeshi Emura, Chang Gung University
Yi-Hau Chen, Institute of Statistical Science, Academia Sinica
- Table of contents (6 chapters)
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Setting the Scene
Pages 1-8
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Introduction to Survival Analysis
Pages 9-26
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Copula Models for Dependent Censoring
Pages 27-40
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Analysis of Survival Data Under an Assumed Copula
Pages 41-55
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Gene Selection and Survival Prediction Under Dependent Censoring
Pages 57-70
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Table of contents (6 chapters)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Analysis of Survival Data with Dependent Censoring
- Book Subtitle
- Copula-Based Approaches
- Authors
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- Takeshi Emura
- Yi-Hau Chen
- Series Title
- JSS Research Series in Statistics
- Copyright
- 2018
- Publisher
- Springer Singapore
- Copyright Holder
- The Author(s)
- eBook ISBN
- 978-981-10-7164-5
- DOI
- 10.1007/978-981-10-7164-5
- Softcover ISBN
- 978-981-10-7163-8
- Series ISSN
- 2364-0057
- Edition Number
- 1
- Number of Pages
- XIII, 84
- Number of Illustrations
- 10 b/w illustrations
- Topics
