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

by Robert Elashoff, Gang Li, and Ning Li

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Book cover for Joint Modeling of Longitudinal and Time-to-Event Data

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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 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.

  • ISBN10 1439807825
  • ISBN13 9781439807828
  • Publish Date 24 August 2016
  • Publish Status Active
  • Publish Country US
  • Publisher Taylor & Francis Ltd
  • Imprint Chapman & Hall/CRC
  • Format Hardcover
  • Pages 262
  • Language English