Longitudinal Data Analysis [Hardcover]

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 Analysisprovides 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.Introduction and Historical Overview
Advances in Longitudinal Data Analysis: A Historical Perspective
Garrett Fitzmaurice and Geert Molenberghs
Parametric Modeling of Longitudinal Data
Parametric Modeling of Longitudinal Data: Introduction and Overview
Garrett Fitzmaurice and Geert Verbeke
Generalized Estimating Equations for Longitudinal Data Analysis
Stuart Lipsitz and Garrett Fitzmaurice
Generalized Linear Mixed-Effects Models
Sophia Rabe-Hesketh and Anders Skrondal
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