Applied Longitudinal Analysis
John Wiley & Sons Inc (Verlag)
978-0-471-21487-8 (ISBN)
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This book offers 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; and, analyses utilizing SAS[registered] 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.
GARRETT M. FITZMAURICE, ScD, is Associate Professor of Biostatistics at the Harvard School of Public Health. NAN M. LAIRD, PhD, is Professor of Biostatistics at the Harvard School of Public Health. JAMES H. WARE, PhD, is Frederick Mosteller Professor of Biostatistics and Dean for Academic Affairs at the Harvard School of Public Health. All three authors are Fellows of the American Statistical Association and members of the International Statistical Institute.
Preface.Acknowledgments.PART I: INTRODUCTION TO LONGITUDINAL AND CLUSTERED DATA.1. Longitudinal and Clustered Data.2. Longitudinal Data: Basic Concepts.PART II: LINEAR MODELS FOR LONGITUDINAL CONTINUOUS DATA.3. Overview of Linear Models for Longitudinal Data.4. Estimation and Statistical Inference.5. Modelling the Mean: Analyzing Response Profiles.6. Modelling the Mean: Parametric Curves.7. Modelling the Covariance.8. Linear Mixed Effects Models.9. Residual Analyses and Diagnostics.PART III: GENERALIZED LINEAR MODELS FOR LONGITUDINAL DATA.10. Review of Generalized Linear Models.11. Marginal Models: Generalized Estimating Equations (GEE).12. Generalized Linear Mixed Effects Models.13. Contrasting Marginal and Mixed Effects Models.PART IV: ADVANCED TOPICS FOR LONGITUDINAL AND CLUSTERED DATA.14. Missing Data and Dropout.15. Some Aspects of the Design of Longitudinal Studies.16. Repeated Measures and Related Designs.17. Multilevel Models.Appendix A: Gentle Introduction to Vectors and Matrices.Appendix B: Properties of Expectations and Variances.Appendix C: Critical Points for a 50:50 Mixture of Chi-Squared Distributions.References.Index.
| Erscheint lt. Verlag | 13.7.2004 |
|---|---|
| Reihe/Serie | Wiley Series in Probability and Statistics |
| Zusatzinfo | Illustrations |
| Verlagsort | New York |
| Sprache | englisch |
| Maße | 164 x 234 mm |
| Gewicht | 856 g |
| Einbandart | gebunden |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik |
| ISBN-10 | 0-471-21487-6 / 0471214876 |
| ISBN-13 | 978-0-471-21487-8 / 9780471214878 |
| Zustand | Neuware |
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