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Longitudinal Data Analysis

Handbooks of Modern Statistical Methods

Edited by: Garrett Fitzmaurice , Marie Davidian , Geert Verbeke , Geert Molenberghs

Print publication date:  August  2008
Online publication date:  August  2008

Print ISBN: 9781584886587
eBook ISBN: 9781420011579
Adobe ISBN:

10.1201/9781420011579
 Cite  Marc Record

Book description

With contributions from some of the most prominent researchers in the field, this carefully edited collection provides a clear, comprehensive, and unified overview of recent developments in statistical methods for the analysis of longitudinal data. Focusing on both theory and applications, it addresses challenges that arise in analyzing longitudinal data, emphasizes statistical models and methods likely to endure in the future, highlights connections between various research threads in the statistical literature, and contains numerous examples and case studies drawn from a range of disciplines. Data sets, software programs, and other material are available on the editors’ website.

Table of contents

Chapter  1:  Advances in longitudinal data analysis: An historical perspective Download PDF
Chapter  2:  Parametric modeling of longitudinal data: Introduction and overview Download PDF
Chapter  3:  Generalized estimating equations for longitudinal data analysis Download PDF
Chapter  4:  Generalized linear mixed-effects models Download PDF
Chapter  5:  Non-linear mixed-effects models Download PDF
Chapter  6:  Growth mixture modeling Download PDF
Chapter  7:  Targets of inference in hierarchical models for longitudinal data Download PDF
Chapter  8:  Non-parametric and semi-parametric regression methods: Download PDF
Chapter  9:  Non-parametric and semi-parametric regression methods for longitudinal data Download PDF
Chapter  10:  Functional modeling of longitudinal data Download PDF
Chapter  11:  Smoothing spline models for longitudinal data Download PDF
Chapter  12:  Penalized spline models for longitudinal data Download PDF
Chapter  13:  Joint models for longitudinal data Download PDF
Chapter  14:  Joint models for continuous and discrete longitudinal data Download PDF
Chapter  15:  Random-effects models for joint analysis of repeated-measurement and time-to-event outcomes Download PDF
Chapter  16:  Joint models for high-dimensional longitudinal data Download PDF
Chapter  17:  Incomplete data Download PDF
Chapter  18:  Selection and pattern-mixture models Download PDF
Chapter  19:  Shared-parameter models Download PDF
Chapter  20:  Inverse probability weighted methods Download PDF
Chapter  21:  Multiple imputation Download PDF
Chapter  22:  Sensitivity analysis for incomplete data Download PDF
Chapter  23:  Estimation of the causal effects of time-varying exposures Download PDF
prelims Download PDF
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