Longitudinal Data Analysis

Garrett Fitzmaurice, Marie Davidian, Geert Verbeke, Geert Molenberghs

August 11, 2008 by Chapman and Hall/CRC
Reference - 632 Pages - 106 B/W Illustrations
ISBN 9781584886587 - CAT# C6587
Series: Chapman & Hall/CRC Handbooks of Modern Statistical Methods

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Features

  • Provides a clear, comprehensive, and unified overview of recent developments in statistical methods for the analysis of longitudinal data
  • Addresses the challenges that arise in analyzing longitudinal data, such as complex random-error structures, stochastic time-varying covariates, missing data, and attrition
  • Presents contributions from some of the most prominent researchers in the field
  • Includes an introductory chapter in each section to set the stage for subsequent chapters
  • Highlights connections between various research threads in the statistical literature
  • Contains numerous examples and case studies drawn from a range of disciplines, including medical research, epidemiology, and the social sciences
  • Offers data sets, software programs, and other material on the editors’ website
  • Summary

    Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory and applications. It also focuses on the assorted challenges that arise in analyzing longitudinal data.

    After discussing historical aspects, leading researchers explore four broad themes: parametric modeling, nonparametric and semiparametric methods, joint models, and incomplete data. Each of these sections begins with an introductory chapter that provides useful background material and a broad outline to set the stage for subsequent chapters. Rather than focus on a narrowly defined topic, chapters integrate important research discussions from the statistical literature. They seamlessly blend theory with applications and include examples and case studies from various disciplines.

    Destined to become a landmark publication in the field, this carefully edited collection emphasizes statistical models and methods likely to endure in the future. Whether involved in the development of statistical methodology or the analysis of longitudinal data, readers will gain new perspectives on the field.