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Dynamic prediction in clinical survival analysis [electronic resource] / Hans C. van Houwelingen, Hein Putter.

By: Houwelingen, J. C. van.
Contributor(s): Putter, Hein | ProQuest (Firm).
Material type: materialTypeLabelBookSeries: Monographs on statistics and applied probability: 123.Publisher: Boca Raton, Fla. : CRC Press, 2012Description: xvi, 231 p. : ill.Subject(s): Proportional hazards models | Survival analysis (Biometry)Genre/Form: Electronic books.DDC classification: 615.580724 Online resources: Click to View
Contents:
The special nature of survival data -- Cox regression model -- Measuring the predictive value of a Cox model -- Calibration and revision of Cox models -- Mechanisms explaining violation of the Cox model -- Non-proportional hazards models -- Dealing with non-proportional hazards -- Dynamic predictions using biomarkers -- Dynamic prediction in multi-state models -- Dynamic prediction in chronic disease -- Penalized Cox models -- Dynamic prediction based on genomic data.
Summary: "In the last twenty years, dynamic prediction models have been extensively used to monitor patient prognosis in survival analysis. Written by one of the pioneers in the area, this book synthesizes these developments in a unified framework. It covers a range of models, including prognostic and dynamic prediction of survival using genomic data and time-dependent information. The text includes numerous examples using real data that is taken from the authors collaborative research. R programs are provided for implementing the methods"--Provided by publisher.
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Item type Current location Collection Call number URL Copy number Status Date due Item holds
E-book E-book IUKL Library
Subscripti https://ebookcentral.proquest.com/lib/kliuc-ebooks/detail.action?docID=830223 1 Available
Total holds: 0

"A Chapman & Hall book."

Includes bibliographical references.

The special nature of survival data -- Cox regression model -- Measuring the predictive value of a Cox model -- Calibration and revision of Cox models -- Mechanisms explaining violation of the Cox model -- Non-proportional hazards models -- Dealing with non-proportional hazards -- Dynamic predictions using biomarkers -- Dynamic prediction in multi-state models -- Dynamic prediction in chronic disease -- Penalized Cox models -- Dynamic prediction based on genomic data.

"In the last twenty years, dynamic prediction models have been extensively used to monitor patient prognosis in survival analysis. Written by one of the pioneers in the area, this book synthesizes these developments in a unified framework. It covers a range of models, including prognostic and dynamic prediction of survival using genomic data and time-dependent information. The text includes numerous examples using real data that is taken from the authors collaborative research. R programs are provided for implementing the methods"--Provided by publisher.

Electronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.

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