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.

• Format: Paperback
• Language: English
• ISBN: 0367570572
• ISBN13: 9780367570576
• Release Date: June 2020
• Publisher: CRC Press
• Length: 241 Pages
• Weight: 0.92 lbs.
• Dimensions: 0.9" x 6.1" x 9.1"