Modeling Survival Data Using Frailty Models.

By:

David D. Hanagal

Material type: Text

TextLanguage: English Series: Industrial and Applied MathematicsPublication details: Symbiosis International University Pune, Maharashtra, India | Springer Nature Singapore Pte Ltd | 2019.Edition: 2nd. EditionDescription: 307 Pages; Includes References and IndexISBN:

978-981-15-1180-6
978-981-15-1181-3 (eBook)

ISSN:

2364-6837
2364-6845 (electronic)

Uniform titles:

Modeling Survival Data Using Frailty Models.

Subject(s):

-- Biometry, Computer simulation, Computers / Computer Simulation, Mathematics / Probability & Statistics / Bayesian Analysis, Mathematics / Probability & Statistics / General, Medical / Biostatistics, Medical / General, Statistics, Bayesian Inference, Failure time data analysis -- Mathematical models, Simulation and Modeling, Statistics for Life Sciences, Medicine, Health Sciences, Survival analysis (Biometry) -- Mathematical models

Online resources:

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Summary: This book presents the basic concepts of survival analysis and frailty models, covering both fundamental and advanced topics. It focuses on applications of statistical tools in biology and medicine, highlighting the latest frailty-model methodologies and applications in these areas. After explaining the basic concepts of survival analysis, the book goes on to discuss shared, bivariate, and correlated frailty models and their applications. It also features nine datasets that have been analyzed using the R statistical package. Covering recent topics, not addressed elsewhere in the literature, this book is of immense use to scientists, researchers, students and teachers.

Item type: E-BOOKS

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Holdings
Item type	Current library	URL	Copy number	Status	Barcode
E-BOOKS	MWALIMU NYERERE LEARNING RESOURCES CENTRE-CUHAS BUGANDO	Link to resource	20241107130743.0	Not for loan	20241107130743.0

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This book presents the basic concepts of survival analysis and frailty models, covering both fundamental and advanced topics. It focuses on applications of statistical tools in biology and medicine, highlighting the latest frailty-model methodologies and applications in these areas. After explaining the basic concepts of survival analysis, the book goes on to discuss shared, bivariate, and correlated frailty models and their applications. It also features nine datasets that have been analyzed using the R statistical package. Covering recent topics, not addressed elsewhere in the literature, this book is of immense use to scientists, researchers, students and teachers.

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