Overview
- 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
Part of the book series: SpringerBriefs in Statistics (BRIEFSSTATIST)
Part of the book sub series: JSS Research Series in Statistics (JSSRES)
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About this book
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.
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Keywords
Table of contents (6 chapters)
Authors and Affiliations
About the authors
Takeshi Emura, Chang Gung University
Yi-Hau Chen, Institute of Statistical Science, Academia Sinica
Bibliographic Information
Book Title: Analysis of Survival Data with Dependent Censoring
Book Subtitle: Copula-Based Approaches
Authors: Takeshi Emura, Yi-Hau Chen
Series Title: SpringerBriefs in Statistics
DOI: https://doi.org/10.1007/978-981-10-7164-5
Publisher: Springer Singapore
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Author(s) 2018
Softcover ISBN: 978-981-10-7163-8Published: 13 April 2018
eBook ISBN: 978-981-10-7164-5Published: 05 April 2018
Series ISSN: 2191-544X
Series E-ISSN: 2191-5458
Edition Number: 1
Number of Pages: XIII, 84
Number of Illustrations: 10 b/w illustrations
Topics: Statistics for Life Sciences, Medicine, Health Sciences, Statistical Theory and Methods, Biostatistics, Statistics for Social Sciences, Humanities, Law