Book contents
- Frontmatter
- Contents
- Preface
- Acknowledgments
- 1 Introduction
- Part I Foundations
- 2 Causal Models
- 3 Illustrating Causal Models
- 4 Causal Queries
- 5 Bayesian Answers
- 6 Theories as Causal Models
- Part II Model-Based Causal Inference
- Part III Design Choices
- Part IV Models in Question
- Part V Appendices
- Bibliography
- Index
2 - Causal Models
from Part I - Foundations
Published online by Cambridge University Press: 13 October 2023
Book contents
- Frontmatter
- Contents
- Preface
- Acknowledgments
- 1 Introduction
- Part I Foundations
- 2 Causal Models
- 3 Illustrating Causal Models
- 4 Causal Queries
- 5 Bayesian Answers
- 6 Theories as Causal Models
- Part II Model-Based Causal Inference
- Part III Design Choices
- Part IV Models in Question
- Part V Appendices
- Bibliography
- Index
Summary
We provide a lay-language primer on the counterfactual model of causal inference and the logic of causal models. Topics include the representation of causal models with causal graphs and using causal graphs to read off relations of conditional independence among variables in a causal domain.
Keywords
- Type
- Chapter
- Information
- Integrated InferencesCausal Models for Qualitative and Mixed-Method Research, pp. 19 - 58Publisher: Cambridge University PressPrint publication year: 2023