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
- 5 Model Evaluation and Selection
- 6 Inference and Interpretation
- Part III The Generalized Linear Model
- Part IV Advanced Topics
- Part V A Look Ahead
- Bibliography
- Index
6 - Inference and Interpretation
from Part II - Model Evaluation and Interpretation
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
- 5 Model Evaluation and Selection
- 6 Inference and Interpretation
- Part III The Generalized Linear Model
- Part IV Advanced Topics
- Part V A Look Ahead
- Bibliography
- Index
Summary
Discusses the mechanics and computation for effectively interpreting theoutput of likelihood-based models in ways that are easy to understand and communicate.
- Type
- Chapter
- Information
- Maximum Likelihood for Social ScienceStrategies for Analysis, pp. 119 - 132Publisher: Cambridge University PressPrint publication year: 2018