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2. Categorical Data and Generalized Linear Models

  • John P. Hoffmann
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Regression Models for Categorical, Count, and Related Variables
This chapter is in the book Regression Models for Categorical, Count, and Related Variables
© 2019 University of California Press, Berkeley

© 2019 University of California Press, Berkeley

Chapters in this book

  1. Frontmatter i
  2. Contents vii
  3. Preface xi
  4. Acknowledgments xv
  5. 1. Review of Linear Regression Models 1
  6. 2. Categorical Data and Generalized Linear Models 39
  7. 3. Logistic and Probit Regression Models 63
  8. 4. Ordered Logistic and Probit Regression Models 87
  9. 5. Multinomial Logistic and Probit Regression Models 111
  10. 6. Poisson and Negative Binomial Regression Models 131
  11. 7. Event History Models 159
  12. 8. Regression Models for Longitudinal Data 189
  13. 9. Multilevel Regression Models 207
  14. 10. Principal Components and Factor Analysis 243
  15. Appendix A: SAS, SPSS, and R Code for Examples in Chapters 269
  16. Appendix B: Using Simulations to Examine Assumptions of OLS Regression 383
  17. Appendix C: Working with Missing Data 389
  18. References 397
  19. Index 403
https://doi.org/10.1525/9780520965492-004

Chapters in this book

  1. Frontmatter i
  2. Contents vii
  3. Preface xi
  4. Acknowledgments xv
  5. 1. Review of Linear Regression Models 1
  6. 2. Categorical Data and Generalized Linear Models 39
  7. 3. Logistic and Probit Regression Models 63
  8. 4. Ordered Logistic and Probit Regression Models 87
  9. 5. Multinomial Logistic and Probit Regression Models 111
  10. 6. Poisson and Negative Binomial Regression Models 131
  11. 7. Event History Models 159
  12. 8. Regression Models for Longitudinal Data 189
  13. 9. Multilevel Regression Models 207
  14. 10. Principal Components and Factor Analysis 243
  15. Appendix A: SAS, SPSS, and R Code for Examples in Chapters 269
  16. Appendix B: Using Simulations to Examine Assumptions of OLS Regression 383
  17. Appendix C: Working with Missing Data 389
  18. References 397
  19. Index 403
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