Andere Kunden interessierten sich auch für
![Survival Analysis with Correlated Endpoints]( "Survival Analysis with Correlated Endpoints")
Survival Analysis with Correlated Endpoints44,99 €![Meta-Analysis]( "Meta-Analysis")
Meta-Analysis37,99 €![Meta-Analysis]( "Meta-Analysis")
Meta-Analysis55,99 €![Modeling Longitudinal Data]( "Modeling Longitudinal Data")
Modeling Longitudinal Data63,99 €![The Statistical Analysis of Interval-censored Failure Time Data]( "The Statistical Analysis of Interval-censored Failure Time Data")
The Statistical Analysis of Interval-censored Failure Time Data132,99 €![The Statistical Analysis of Interval-Censored Failure Time Data]( "The Statistical Analysis of Interval-Censored Failure Time Data")
The Statistical Analysis of Interval-Censored Failure Time Data211,99 €![Design and Analysis of Subgroups with Biopharmaceutical Applications]( "Design and Analysis of Subgroups with Biopharmaceutical Applications")
Design and Analysis of Subgroups with Biopharmaceutical Applications66,99 €
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.