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Joint Modeling of Longitudinal and Time-to-Event Data

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by Robert Elashoff & Gang li & Ning Li
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Joint Modeling of Longitudinal and Time-to-Event Data by Robert Elashoff & Gang li & Ning Li

Longitudinal studies often incur several problems that challenge standard statistical methods for data analysis. These problems include non-ignorable missing data in longitudinal measurements of one or more response variables, informative observation times of longitudinal data, and survival analysis with intermittently measured time-dependent covariates that are subject to measurement error and/or substantial biological variation. Joint modeling of longitudinal and time-to-event data has emerged as a novel approach to handle these issues.

Joint Modeling of Longitudinal and Time-to-Event Data provides a systematic introduction and review of state-of-the-art statistical methodology in this active research field. The methods are illustrated by real data examples from a wide range of clinical research topics. A collection of data sets and software for practical implementation of the joint modeling methodologies are available through the book website.

This book serves as a reference book for scientific investigators who need to analyze longitudinal and/or survival data, as well as researchers developing methodology in this field. It may also be used as a textbook for a graduate level course in biostatistics or statistics.

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Ebook Details
Pages: 261
Size: 8.4 MB
Publisher: Chapman and Hall/CRC
Date published:   2016
ISBN: 9781315357188 (DRM-EPUB)
9781439807835 (DRM-PDF)

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This product is listed in the following categories:

Nonfiction > Mathematics > Probability & Statistics
Nonfiction > Medical > Biostatistics
Nonfiction > Mathematics > Finite Mathematics

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01/24/2017
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