Multilevel Modeling
eBook - ePub

Multilevel Modeling

Applications in STATA®, IBM® SPSS®, SAS®, R, & HLM™

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Multilevel Modeling

Applications in STATA®, IBM® SPSS®, SAS®, R, & HLM™

About this book

Multilevel Modeling: Applications in STATA®, IBM® SPSS®, SAS®, R & HLM™ provides a gentle, hands-on illustration of the most common types of multilevel modeling software, offering instructors multiple software resources for their students and an applications-based foundation for teaching multilevel modeling in the social sciences. Author G. David Garson's step-by-step instructions for software walk readers through each package. The instructions for the different platforms allow students to get a running start using the package with which they are most familiar while the instructor can start teaching the concepts of multilevel modeling right away. Instructors will find this text serves as both a comprehensive resource for their students and a foundation for their teaching alike.

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Yes, you can access Multilevel Modeling by G. David Garson in PDF and/or ePUB format, as well as other popular books in Education & Education Theory & Practice. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Cover
  2. Title Page
  3. Title Page
  4. Copyright Page
  5. Brief Contents
  6. Detailed Contents
  7. Preface
  8. Acknowledgments
  9. About the Author
  10. Publisher Note
  11. 1 Introduction to Multilevel Modeling
  12. 2 Assumptions of Multilevel Modeling
  13. 3 The Null Model
  14. 4 Estimating Multilevel Models
  15. 5 Goodness of Fit and Effect Size in Multilevel Models
  16. 6 The Two-Level Random Intercept Model
  17. 7 The Two-Level Random Coefficients Model
  18. 8 The Three-Level Unconditional Random Intercept Model With Longitudinal Data
  19. 9 Repeated Measures and Heterogeneous Variance Models
  20. 10 Residual and Influence Analysis for a Three-Level RC Model
  21. 11 Cross-Classified Linear Mixed Models
  22. 12 Generalized Linear Mixed Models
  23. Appendix 1 Data Used in Examples
  24. Appendix 2 How to Report Multilevel Results
  25. References
  26. Index