Joint modeling of longitudinal and time-to-event data

Joint modeling of longitudinal and time-to-event data

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LF/405283/R
English
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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 Dataprovides 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.
LF/405283/R

Data sheet

Name of the Author
Elashoff
Gang
Li
Ning
Robert M.
Language
English
Series
Monographs on statistics and applied probability (Series) 151
ISBN
9781439807828
Release date
2017

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Joint modeling of longitudinal and time-to-event data

Longitudinal studies often incur several problems that challenge standard statistical methods for data analysis. These problems include non-ignorable missing...

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