Authors:
- The first-ever book tailored to the problem of correlated endpoints in survival analysis
- Offers a clearly structured textbook on survival analysis, suitable for graduate students, (bio)statisticians, mathematicians, and medical researchers alike
- Helps readers apply the statistical methods of this book to real data, by means of the R package
Part of the book series: SpringerBriefs in Statistics (BRIEFSSTATIST)
Part of the book sub series: JSS Research Series in Statistics (JSSRES)
Buy it now
Buying options
Tax calculation will be finalised at checkout
Other ways to access
This is a preview of subscription content, log in via an institution to check for access.
Table of contents (6 chapters)
-
Front Matter
-
Back Matter
About this book
This book introduces readers to advanced statistical methods for analyzing survival data involving correlated endpoints. In particular, it describes statistical methods for applying Cox regression to two correlated endpoints by accounting for dependence between the endpoints with the aid of copulas. The practical advantages of employing copula-based models in medical research are explained on the basis of case studies.
In addition, the book focuses on clustered survival data, especially data arising from meta-analysis and multicenter analysis. Consequently, the statistical approaches presented here employ a frailty term for heterogeneity modeling. This brings the joint frailty-copula model, which incorporates a frailty term and a copula, into a statistical model. The book also discusses advanced techniques for dealing with high-dimensional gene expressions and developing personalized dynamic prediction tools under the joint frailty-copula model.
To help readers apply the statistical methods to real-world data, the book provides case studies using the authors’ original R software package (freely available in CRAN). The emphasis is on clinical survival data, involving time-to-tumor progression and overall survival, collected on cancer patients. Hence, the book offers an essential reference guide for medical statisticians and provides researchers with advanced, innovative statistical tools. The book also provides a concise introduction to basic multivariate survival models.
Reviews
Authors and Affiliations
-
Graduate Institute of Statistics, National Central University, Taoyuan City, Taiwan
Takeshi Emura
-
Department of Biostatistics, Graduate School of Medicine, Nagoya University, Nagoya, Japan
Shigeyuki Matsui
-
INSERM CR1219 (Biostatistic), University of Bordeaux, Bordeaux Cedex, France
Virginie Rondeau
About the authors
Takeshi Emura, Chang Gung University
Shigeyuki Matsui, Department of Biostatistics, Nagoya University Graduate School of Medicine
Virginie Rondeau, INSERM U 1219
Bibliographic Information
Book Title: Survival Analysis with Correlated Endpoints
Book Subtitle: Joint Frailty-Copula Models
Authors: Takeshi Emura, Shigeyuki Matsui, Virginie Rondeau
Series Title: SpringerBriefs in Statistics
DOI: https://doi.org/10.1007/978-981-13-3516-7
Publisher: Springer Singapore
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2019
Softcover ISBN: 978-981-13-3515-0Published: 04 April 2019
eBook ISBN: 978-981-13-3516-7Published: 25 March 2019
Series ISSN: 2191-544X
Series E-ISSN: 2191-5458
Edition Number: 1
Number of Pages: XVII, 118
Number of Illustrations: 10 b/w illustrations, 19 illustrations in colour
Topics: Statistics for Life Sciences, Medicine, Health Sciences, Statistics for Social Sciences, Humanities, Law, Statistical Theory and Methods, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences