Full Description
A comprehensive and accessible guide to learning and successfully applying QCA
Social phenomena can rarely be attributed to single causes—instead, they typically stem from a myriad of interwoven factors that are often difficult to untangle. Drawing on set theory and the language of necessary and sufficient conditions, qualitative comparative analysis (QCA) is ideally suited to capturing this causal complexity. A case-based research method, QCA regards cases as combinations of conditions and compares the conditions of each case in a structured way to identify the necessary and sufficient conditions for an outcome.
Qualitative Comparative Analysis: An Introduction to Research Design and Application is a comprehensive guide to QCA. As QCA becomes increasingly popular across the social sciences, this textbook teaches students, scholars, and self-learners the fundamentals of the method, research design, interpretation of results, and how to communicate findings.
Following an ideal typical research cycle, the book's ten chapters cover the methodological basis and analytical routine of QCA, as well as matters of research design, causation and causal complexity, QCA variants, and the method's reception in the social sciences. A comprehensive glossary helps to clarify the meaning of frequently used terms. The book is complemented by an accessible online R manual to help new users to practice QCA's analytical steps on sample data and then implement with their own findings. This hands-on textbook is an essential resource for students and researchers looking for a complete and up-to-date introduction to QCA.
Contents
List of Boxes, Figures, and Tables
Preface
Acknowledgments
1. Introduction
What Is Qualitative Comparative Analysis?
How To Use This Book
The QCA Research Cycle
A Brief History of QCA
Trends in QCA Applications
Book Outline
Notes
2. Research Design
Research Questions
Uses of QCA
Case Selection
Condition Selection
Multi-Method Research Designs
A Survey of Empirical Applications
Notes
3. Set Theory
Crisp and Fuzzy Sets
Set Operations
Truth Tables
Necessary and Sufficient Conditions
Assessing Set Relations
Notes
4. Causation and Causal Complexity
Theories of Causation in the Social Sciences
Causal Complexity
Causal Analysis
Notes
5. Calibrating Sets
Measurement and Calibration
Calibration Procedures
Types of Data
The Direct Method of Calibration
Calibration: Applied Examples
Common Misconceptions about Calibration
Good Practices of Calibration
Notes
6. Measures of Fit
Set-Theoretic Consistency
Set-Theoretic Coverage
Proportional Reduction in Inconsistency
Relevance of Necessity
Notes
7. Set-Theoretic Analysis
Analyzing Necessary Conditions
Truth Table Construction
Truth Table Analysis
Solution Terms
Counterfactual Analysis
Notes
8. QCA Variants
Multi-Value QCA
Temporal QCA
Two-Step QCA
Fuzzy Set Ideal Type Analysis
Related Methods and Approaches
Notes
9. QCA and Its Critics
Analytical Robustness
Comparisons with Other Methods
Formalization and Algorithms
Causal Analysis and Solution Terms
Recognizing QCA's Strengths and Limitations
Notes
10. Conclusion
Good Research Practice
Documenting and Communicating QCA Results
QCA Resources
The Way Ahead
Notes
Appendix: Link to Online R Manual
Glossary
References
Index
About the Author
