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Books > Medicine > General issues > Public health & preventive medicine > Epidemiology & medical statistics
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Advanced Survival Models (Hardcover)
Loot Price: R3,685
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Advanced Survival Models (Hardcover)
Series: Chapman & Hall/CRC Biostatistics Series
Expected to ship within 12 - 17 working days
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Survival data analysis is a very broad field of statistics,
encompassing a large variety of methods used in a wide range of
applications, and in particular in medical research. During the
last twenty years, several extensions of "classical" survival
models have been developed to address particular situations often
encountered in practice. This book aims to gather in a single
reference the most commonly used extensions, such as frailty models
(in case of unobserved heterogeneity or clustered data), cure
models (when a fraction of the population will not experience the
event of interest), competing risk models (in case of different
types of event), and joint survival models for a time-to-event
endpoint and a longitudinal outcome. Features Presents state-of-the
art approaches for different advanced survival models including
frailty models, cure models, competing risk models and joint models
for a longitudinal and a survival outcome Uses consistent notation
throughout the book for the different techniques presented Explains
in which situation each of these models should be used, and how
they are linked to specific research questions Focuses on the
understanding of the models, their implementation, and their
interpretation, with an appropriate level of methodological
development for masters students and applied statisticians Provides
references to existing R packages and SAS procedure or macros, and
illustrates the use of the main ones on real datasets This book is
primarily aimed at applied statisticians and graduate students of
statistics and biostatistics. It can also serve as an introductory
reference for methodological researchers interested in the main
extensions of classical survival analysis.
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