Applied Longitudinal Analysis

Couverture
John Wiley & Sons, 2004 - 506 pages
A rigorous, systematic presentation of modern longitudinal analysis

Longitudinal studies, employing repeated measurement of subjects over time, play a prominent role in the health and medical sciences as well as in pharmaceutical studies. An important strategy in modern clinical research, they provide valuable insights into both the development and persistence of disease and those factors that can alter the course of disease development.

Written at a technical level suitable for researchers and graduate students, Applied Longitudinal Analysis provides a rigorous and comprehensive description of modern methods for analyzing longitudinal data. Focusing on General Linear and Mixed Effects Models for continuous responses, and extensions of Generalized Linear Models for discrete responses, the authors discuss in detail the relationships among these different models, including their underlying assumptions and relative merits. The book features:

  • A focus on practical applications, utilizing a wide range of examples drawn from real-world studies
  • Coverage of modern methods of regression analysis for correlated data
  • Analyses utilizing SAS®
  • Multiple exercises and "homework" problems for review

An accompanying Web site features twenty-five real data sets used throughout the text, in addition to programming statements and selected computer output for the examples.

 

Table des matières

Longitudinal and Clustered Data
1
Basic Concepts
19
Linear Models for Longitudinal Continuous Data
47
Estimation and Statistical Inference
87
Analyzing Response Profiles
103
Parametric Curves
141
Modelling the Covariance
163
Linear Mixed Effects Models
187
Generalized Linear Mixed Effects Models
325
Contrasting Marginal and Mixed Effects Models
359
Advanced Topics for Longitudinal and Clustered Data
373
Some Aspects of the Design of Longitudinal Studies
401
Repeated Measures and Related Designs
425
Multilevel Models
441
Appendix A Gentle Introduction to Vectors and Matrices
469
Appendix B Properties of Expectations and Variances
479

Residual Analyses and Diagnostics
237
Review of Generalized Linear Models
257
Generalized Estimating
291
References
485
Index
501
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