Generalizing the Regression Model
eBook - ePub

Generalizing the Regression Model

Techniques for Longitudinal and Contextual Analysis

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

Generalizing the Regression Model

Techniques for Longitudinal and Contextual Analysis

About this book

This comprehensive text introduces regression, the general linear model, structural equation modeling, the hierarchical linear model, growth curve models, panel data, and event history models, and includes discussion of published implementations of each technique showing how it was used to address substantive and interesting research questions. It takes a step-by-step approach in the presentation of each topic, using mathematical derivations where necessary, but primarily emphasizing how the methods involved can be implemented, are used in addressing representative substantive problems than span a number of disciplines, and can be interpreted in words. The book demonstrates the analyses in STATA and SAS. Generalizing the Regression Model provides students with a bridge from the classroom to actual research practice and application.

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Yes, you can access Generalizing the Regression Model by Blair Wheaton,Marisa Young in PDF and/or ePUB format, as well as other popular books in Social Sciences & Social Science Research & Methodology. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Publisher Note
  4. Title Page
  5. Copyright Page
  6. Brief Table of Contents
  7. Detailed Table of Contents
  8. Reviewer Acknowledgments
  9. Preface
  10. About the Authors
  11. 1 A Review of Correlation and Regression
  12. 2 Generalizations of regression 1: Testing and Interpreting Interactions
  13. 3 Generalizations of Regression 2: Nonlinear Regression
  14. 4 Generalizations of Regression 3: Logistic Regression
  15. 5 Generalizations of Regression 4: The Generalized Linear Model
  16. 6 From Equations to Models: The Process of Explanation
  17. 7 An Introduction to Structural Equation Models
  18. 8 Identification and Testing of Models
  19. 9 Variations and Extensions of SEM
  20. 10 An Introduction to Hierarchical Linear Models
  21. 11 The Generalized Hierarchical Linear Model
  22. 12 Growth Curvec Models
  23. 13 Introduction to Regression for Panel Data
  24. 14 Variations and Extensions of Panel Regression
  25. 15 Event History Analysis in discrete time
  26. 16 The Continuous Time Event History Model
  27. References
  28. Index