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Dynamic Prediction in Clinical Survival Analysis (Hardcover)
Loot Price: R4,450
Discovery Miles 44 500
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Dynamic Prediction in Clinical Survival Analysis (Hardcover)
Series: Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Expected to ship within 12 - 17 working days
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There is a huge amount of literature on statistical models for the
prediction of survival after diagnosis of a wide range of diseases
like cancer, cardiovascular disease, and chronic kidney disease.
Current practice is to use prediction models based on the Cox
proportional hazards model and to present those as static models
for remaining lifetime after diagnosis or treatment. In contrast,
Dynamic Prediction in Clinical Survival Analysis focuses on dynamic
models for the remaining lifetime at later points in time, for
instance using landmark models. Designed to be useful to applied
statisticians and clinical epidemiologists, each chapter in the
book has a practical focus on the issues of working with real life
data. Chapters conclude with additional material either on the
interpretation of the models, alternative models, or theoretical
background. The book consists of four parts: * Part I deals with
prognostic models for survival data using (clinical) information
available at baseline, based on the Cox model * Part II is about
prognostic models for survival data using (clinical) information
available at baseline, when the proportional hazards assumption of
the Cox model is violated * Part III is dedicated to the use of
time-dependent information in dynamic prediction * Part IV explores
dynamic prediction models for survival data using genomic data
Dynamic Prediction in Clinical Survival Analysis summarizes
cutting-edge research on the dynamic use of predictive models with
traditional and new approaches. Aimed at applied statisticians who
actively analyze clinical data in collaboration with clinicians,
the analyses of the different data sets throughout the book
demonstrate how predictive models can be obtained from proper data
sets.
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