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Joint Modeling of Longitudinal and Time-to-Event Data af Gang Li, Robert Elashoff, Ning Li

Joint Modeling of Longitudinal and Time-to-Event Data (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)

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

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

Produktdetaljer:

Sprog:
Engelsk
ISBN-13:
9781439807835
Sideantal:
261
Udgivet:
01-08-2016
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(E-bog, ePub), Engelsk
kr. 468,35
 
kr. 649,95
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Forlagets beskrivelse
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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