Book contents
- Frontmatter
- Contents
- List of Figures
- List of Tables
- Preface
- Acknowledgements
- Notes on Notation
- Part I Concepts, Theory, and Implementation
- Part II Model Evaluation and Interpretation
- Part III The Generalized Linear Model
- 7 The Generalized Linear Model
- 8 Ordered Categorical Variable Models
- 9 Models for Nominal Data
- 10 Strategies for Analyzing Count Data
- Part IV Advanced Topics
- Part V A Look Ahead
- Bibliography
- Index
9 - Models for Nominal Data
from Part III - The Generalized Linear Model
Published online by Cambridge University Press: 15 November 2018
Book contents
- Frontmatter
- Contents
- List of Figures
- List of Tables
- Preface
- Acknowledgements
- Notes on Notation
- Part I Concepts, Theory, and Implementation
- Part II Model Evaluation and Interpretation
- Part III The Generalized Linear Model
- 7 The Generalized Linear Model
- 8 Ordered Categorical Variable Models
- 9 Models for Nominal Data
- 10 Strategies for Analyzing Count Data
- Part IV Advanced Topics
- Part V A Look Ahead
- Bibliography
- Index
Summary
Applies the GLM framework to modeling unorded categorical responses. Discusses the IIA assumption for the mutinomial logit and the many tools developed for times when it fails.
- Type
- Chapter
- Information
- Maximum Likelihood for Social ScienceStrategies for Analysis, pp. 161 - 189Publisher: Cambridge University PressPrint publication year: 2018