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200 10$aAnalysis of Survival Data with Dependent Censoring $eCopula-Based Approaches /$fby Takeshi Emura, Yi-Hau Chen
205   $a1st ed. 2018.
210  1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2018.
215   $a1 online resource (94 pages)
225 1 $aJSS Research Series in Statistics,$x2364-0065
311 08$a981-10-7163-2 
327   $aChapter 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.
330   $aThis 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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606   $aSocial sciences$xStatistical methods
606   $aBiostatistics
606   $aStatistical Theory and Methods
606   $aStatistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy
615  0$aBiometry.
615  0$aStatistics.
615  0$aSocial sciences$xStatistical methods.
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615 24$aStatistical Theory and Methods.
615 24$aStatistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy.
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