Book contents
- Frontmatter
- Contents
- Preface
- Acknowledgments
- 1 Introduction
- Part I Foundations
- Part II Model-Based Causal Inference
- 7 Process Tracing with Causal Models
- 8 Process-Tracing Applications
- 9 Integrated Inferences
- 10 Integrated Inferences Applications
- 11 Mixing Models
- Part III Design Choices
- Part IV Models in Question
- Part V Appendices
- Bibliography
- Index
9 - Integrated Inferences
from Part II - Model-Based Causal Inference
Published online by Cambridge University Press: 13 October 2023
- Frontmatter
- Contents
- Preface
- Acknowledgments
- 1 Introduction
- Part I Foundations
- Part II Model-Based Causal Inference
- 7 Process Tracing with Causal Models
- 8 Process-Tracing Applications
- 9 Integrated Inferences
- 10 Integrated Inferences Applications
- 11 Mixing Models
- Part III Design Choices
- Part IV Models in Question
- Part V Appendices
- Bibliography
- Index
Summary
This chapter extends the analysis from Chapter 7 to multi-case settings and demonstrate how we can use the approach to undertake mixed-method analysis. We show how, when analyzing multiple cases, we can update our theory from the evidence and then use our updated theory to draw both population- and case-level inferences. While single-case process tracing is entirely theory-informed, mixed-data inference is thus also “data”-informed. We show how the approach can integrate information across any arbitrary mix of data structures, such as “thin” data on causes and outcomes in many cases and “thicker” process evidence on a subset of those cases.
- Type
- Chapter
- Information
- Integrated InferencesCausal Models for Qualitative and Mixed-Method Research, pp. 217 - 258Publisher: Cambridge University PressPrint publication year: 2023