Multilevel Statistical Models
eBook - ePub

Multilevel Statistical Models

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eBook - ePub

Multilevel Statistical Models

Book details
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About This Book

Throughout the social, medical and other sciences the importance of understanding complex hierarchical data structures is well understood. Multilevel modelling is now the accepted statistical technique for handling such data and is widely available in computer software packages. A thorough understanding of these techniques is therefore important for all those working in these areas. This new edition of Multilevel Statistical Models brings these techniques together, starting from basic ideas and illustrating how more complex models are derived. Bayesian methodology using MCMC has been extended along with new material on smoothing models, multivariate responses, missing data, latent normal transformations for discrete responses, structural equation modeling and survival models.

Key Features:

  • Provides a clear introduction and a comprehensive account of multilevel models.
  • New methodological developments and applications are explored.
  • Written by a leading expert in the field of multilevel methodology.
  • Illustrated throughout with real-life examples, explaining theoretical concepts.

This book is suitable as a comprehensive text for postgraduate courses, as well as a general reference guide. Applied statisticians in the social sciences, economics, biological and medical disciplines will find this book beneficial.

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Yes, you can access Multilevel Statistical Models by Harvey Goldstein in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Wiley
Year
2011
ISBN
9781119956822
Edition
4
Topic
Mathematics
Subtopic
Probability & Statistics
Index
Mathematics

Table of contents

  1. Cover
  2. Title
  3. Copyright
  4. Preface
  5. Acknowledgements
  6. Notation
  7. Glossary
  8. Chapter 1: An introduction to multilevel models
  9. Chapter 2: The 2-level model
  10. Chapter 3: 3-level models and more complex hierarchical structures
  11. Chapter 4: Multilevel models for discrete response data
  12. Chapter 5: Models for repeated measures data
  13. Chapter 6: Multivariate multilevel data
  14. Chapter 7: Latent normal models for multivariate data
  15. Chapter 8: Multilevel factor analysis, structural equation and mixture models
  16. Chapter 9: Nonlinear multilevel models
  17. Chapter 10: Multilevel modelling in sample surveys
  18. Chapter 11: Multilevel event history and survival models
  19. Chapter 12: Cross-classified data structures
  20. Chapter 13: Multiple membership models
  21. Chapter 14: Measurement errors in multilevel models
  22. Chapter 15: Smoothing models for multilevel data
  23. Chapter 16: Missing data, partially observed data and multiple imputation
  24. Chapter 17: Multilevel models with correlated random effects
  25. Chapter 18: Software for multilevel modelling
  26. References
  27. Author index
  28. Subject index