Applied Longitudinal Analysis
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Applied Longitudinal Analysis: (998 Wiley Series in Probability and Statistics)

Applied Longitudinal Analysis: (998 Wiley Series in Probability and Statistics)


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About the Book

Table of Contents:
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

About the Author :
Garrett M. Fitzmaurice, ScD, is Professor in the Department of Biostatistics at the Harvard School of Public Health and Director of the Laboratory for Psychiatric Biostatistics at McLean Hospital. A Fellow of the American Statistical Association and advisor for the Wiley Series in Probability and Statistics, Dr. Fitzmaurice's areas of research interest include statistical methods for analyzing discrete longitudinal data and methods for handling missing data. Nan M. Laird, PhD, is Professor of Biostatistics at the Harvard School of Public Health. A Fellow of the American Statistical Association and Institute of Mathematical Sciences, she has published extensively in the areas of statistical genetics, longitudinal studies, missing or incomplete data, and analysis of multiple informant data. James H. Ware, PhD, is Frederick Mosteller Professor of Biostatistics at the Harvard School of Public Health. A Fellow of the American Statistical Association and statistical consultant to the New England Journal of Medicine, he has made significant contributions to the development of statistical methods for the design and analysis of longitudinal studies.

Review :
“The text is well-organized and clearly written. It is accessible to researchers with varying levels of statistical expertise, with plenty of data examples that make reading and learning enjoyable. I recommend it to biostatisticians as well as to clinicians and other health researchers who may not have much statistical training . . . Applied Longitudinal Analysisis generally my first recommendation when asked for a valuable resource in the field due to the breadth of topics covered and its practical utility.”  (Journal of Biopharmaceutical Statistics, 1 January 2013) “The book also serves as a valuable reference for researchers and professionals in the medical, public health, and pharmaceutical fields, as well as those in social and behavioral sciences who would like to learn more about analysing longitudinal data.” (Zentralblatt MATH, 2012) "This book provides very broad coverage of modern methods for longitudinal data analysis from an applied perspective ... I highly recommend this book to statisticians and quantitative researchers who encounter longitudinal and/or clustered data. In addition, I think the book would be an excellent choice as the primary textbook in an applied longitudinal data course." (Journal of Biopharmaceutical Statistics, 2013)  


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Product Details
  • ISBN-13: 9781118551790
  • Publisher: John Wiley & Sons Inc
  • Publisher Imprint: John Wiley & Sons Inc
  • Edition: Revised edition
  • No of Pages: 752
  • ISBN-10: 1118551796
  • Publisher Date: 23 Oct 2012
  • Binding: Digital (delivered electronically)
  • Language: English
  • Series Title: 998 Wiley Series in Probability and Statistics


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