Joint Modeling of Longitudinal and Time-to-Event Data (Hardcover)

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.

General

Imprint:	Chapman & Hall/CRC
Country of origin:	United States
Series:	Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Release date:	August 2016
First published:	2017
Authors:	Robert Elashoff • Gang Li • Ning Li
Dimensions:	234 x 156 x 19mm (L x W x T)
Format:	Hardcover - Cloth over boards
Pages:	262
ISBN-13:	978-1-4398-0782-8
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Promotions
LSN:	1-4398-0782-5
Barcode:	9781439807828

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