Fitzmaurice / Laird / Ware Applied Longitudinal Analysis

2. Auflage 2012
ISBN: 978-1-118-55179-0
Verlag: John Wiley & Sons
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 752 Seiten, E-Book

Reihe: Wiley Series in Probability and Statistics

Praise for the First Edition
". . . [this book] should be on the shelf of everyone interestedin . . . longitudinal data analysis."
--Journal of the American Statistical Association
Features newly developed topics and applications of theanalysis of longitudinal data
Applied Longitudinal Analysis, Second Edition presentsmodern methods for analyzing data from longitudinal studies and nowfeatures the latest state-of-the-art techniques. The bookemphasizes practical, rather than theoretical, aspects of methodsfor the analysis of diverse types of longitudinal data that can beapplied across various fields of study, from the health and medicalsciences to the social and behavioral sciences.
The authors incorporate their extensive academic and researchexperience along with various updates that have been made inresponse to reader feedback. The Second Edition features six newlyadded chapters that explore topics currently evolving in the field,including:
* Fixed effects and mixed effects models
* Marginal models and generalized estimating equations
* Approximate methods for generalized linear mixed effectsmodels
* Multiple imputation and inverse probability weightedmethods
* Smoothing methods for longitudinal data
* Sample size and power
Each chapter presents methods in the setting of applications todata sets drawn from the health sciences. New problem sets havebeen added to many chapters, and a related website features sampleprograms and computer output using SAS, Stata, and R, as well asdata sets and supplemental slides to facilitate a completeunderstanding of the material.
With its strong emphasis on multidisciplinary applications andthe interpretation of results, Applied LongitudinalAnalysis, Second Edition is an excellent book for courses onstatistics in the health and medical sciences at theupper-undergraduate and graduate levels. The book also serves as avaluable reference for researchers and professionals in themedical, public health, and pharmaceutical fields as well as thosein social and behavioral sciences who would like to learn moreabout analyzing longitudinal data.

Autoren/Hrsg.

Fitzmaurice, Garrett M.

Laird, Nan M.

Ware, James H.

Inhaltsverzeichnis

Preface xvii
Preface to First Edition xxi
Acknowledgments xxv
Part I. Introduction to Longitudinal and Clustered Data
1. Longitudinal and Clustered Data 1
2. Longitudinal Data. Basic Concepts 19
Part II. Linear Models for Longitudinal Continuous Data
3. Overview of Linear Models for Longitudinal Data 49
4. Estimation and Statistical Inference 89
5. Modelling the Mean: Analyzing Response Profiles 105
6. Modelling the Mean: Parametric Curves 143
7. Modelling the Covariance 165
8. Linear Mixed Effect Models 189
9. Fixed Effects versus Random Effects Models 241
10. Residual Analyses and Diagnostics 265
Part III. Generalized Linear Models for Longitudinal Data
11. Review of Generalized Linear Models 291
12. Marginal Models: Introduction and Overview 341
13. Marginal Models: Generalized Estimating Equations (GEE) 353
14. Generalized Linear Mixed Effects Models 395
15. Generalized Linear Mixed Effects Models: Approximate Methods of Estimation 441
16. Contrasting Marginal and Mixed Effects Models 473
Part IV. Missing Data and Dropout
17. Missing Data and Dropout: Overview of Concepts and Methods 489
18. Missing Data and Dropout: Multiple Imputation and Weighting Methods 515
Part V. Advanced Topics for Longitudinal and Clustered Data
19. Smoothing Longitudinal Data: Semiparametric Regression Models 553
20. Sample Size and Power 581
21. Repeated Measures and Related Designs 611
22. Multilevel Models 627
Appendix A. Gentle Introduction to Vectors and Matrices 655
Appendix B. Properties of Expectations and Variance 665
Appendix C. Critical Points for a 50:50 Mixture of Chi-Squared Distributions 669
References 671
Index 695

Über Autor(innen)

Garrett M. Fitzmaurice, ScD, is Professor in the Departmentof Biostatistics at the Harvard School of Public Health andDirector of the Laboratory for Psychiatric Biostatistics at McLeanHospital. A Fellow of the American Statistical Association andadvisor for the Wiley Series in Probability and Statistics, Dr.Fitzmaurice's areas of research interest include statisticalmethods for analyzing discrete longitudinal data and methods forhandling missing data.
Nan M. Laird, PhD, is Professor of Biostatistics at theHarvard School of Public Health. A Fellow of the AmericanStatistical Association and Institute of Mathematical Sciences, shehas published extensively in the areas of statistical genetics,longitudinal studies, missing or incomplete data, and analysis ofmultiple informant data.
James H. Ware, PhD, is Frederick Mosteller Professor ofBiostatistics at the Harvard School of Public Health. A Fellow ofthe American Statistical Association and statistical consultant tothe New England Journal of Medicine, he has made significantcontributions to the development of statistical methods for thedesign and analysis of longitudinal studies.