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Qualitative Comparative Analysis in Mixed Methods Research and Evaluation

Qualitative Comparative Analysis in Mixed Methods Research and Evaluation

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January 2019 | 312 pages | SAGE Publications, Inc

Qualitative Comparative Analysis in Mixed Methods Research and Evaluation provides a user-friendly introduction for using Qualitative Comparative Analysis (QCA) as part of a mixed methods approach to research and evaluation. Offering practical, in-depth, and applied guidance for this unique analytic technique that is not provided in any current mixed methods textbook, the chapters of this guide skillfully build upon one another to walk researchers through the steps of QCA in logical order. To enhance and further reinforce learning, authors Leila C. Kahwati and Heather L. Kane provide supportive learning objectives, summaries, and exercises, as well as author-created datasets for use in R via the companion site.  

Qualitative Comparative Analysis in Mixed Methods Research and Evaluation is Volume 6 in SAGE’s Mixed Methods Research Series. To learn more about each text in the series, please visit

Editors' Introduction
About the Authors
Chapter 1: Qualitative Comparative Analysis as Part of a Mixed Methods Approach
Overview of Mixed Methods Study Designs  
How QCA Compares to Other Quantitative and Qualitative Methods  
Underlying Assumptions of Causal Complexity  
QCA in Mixed Methods Studies  
Overview of the Rest of the Book and Guiding QCA Heuristic  
Chapter 2: Overview of QCA Concepts and Terminology
Configural Research Questions  
The Concept of Sets  
Set Operators and Symbolic Notation  
From Concepts to Real-World Application  
Chapter 3: Selecting Cases and Choosing Conditions and Outcome
Overview of Case, Condition, and Outcome Selection  
Apply Theoretical, Empirical, and Practical Considerations for Selecting Cases  
Apply Theoretical, Empirical, and Practical Considerations for Selecting Conditions and Outcomes  
Identify Strategies for Optimizing the Number of Cases and Conditions  
School Health Features and Academic Performance Example  
Chapter 4: Calibrating Sets and Managing Data
Data Types and Sources  
Calibration versus Measurement  
Types of Calibration and Processes Used  
Calibration Examples  
Good Calibration Practices and Data Management Strategies  
Chapter 5: Analyzing the Data—Initial Analyses
Overview of Analysis  
Transform a Data Matrix into a Truth Table  
Strategies for Managing Contradictory Truth Table Rows  
Revisiting the Data to Manage Contradictory Truth Table Rows  
Inspect the Truth Table for Potential Issues  
Conduct an Analysis of Necessary Conditions and Combinations of Conditions  
Conduct Analysis of Sufficient Conditions and Combinations of Conditions  
Chapter 6: Analyzing the Data—Model Analytics
Overview of Model Analytics  
Interpret Solution Parameters of Fit  
Evaluating Assumptions  
Evaluating Assumptions: An Applied Example  
Model Ambiguity  
Evaluating Model Ambiguity: An Applied Example  
Assessing Robustness  
Evaluating Robustness: An Applied Example  
Iterative Respecification  
Chapter 7: Interpreting Results: Within- and Cross-Case Analysis
Overview of Interpretation  
Considerations for Conducting Within- and Cross-Case Analysis  
Study Aims and Case Selection for Within- and Cross-case Analysis  
Example: School health and Wellness Policies and Academic Performance  
Chapter 8: Advanced Topics in QCA
Multi-value QCA  
Incorporating Time in QCA  
Critiques of QCA  
Chapter 9: Preparing Proposals, Reports, Manuscripts, and Presentations
Reporting QCA Methods  
Summarizing Findings and Limitations  
Improving Accessibility to Readers  
Responding to Peer Review Critiques  
Chapter 10: Examples of Mixed Methods Approaches using QCA
QCA Within a Mixed Methods Approach  
Example of Convergent Design: Evaluation of the Jobs to Careers Program  
Example of Sequential Design: A Configurational Approach to Understanding Project Delays  
APPENDIX: Recommended QCA Resources


Student Study Site

Datasets and accompanying exercises are available for download.

“This book is written in a way that is easy to follow and should expand the range of fields in which QCA is used. Also, there are quite a few principles and practice tips articulated, especially in later chapters, which are applicable more broadly across social sciences and evaluation work. Novice researchers will find those suggestions especially helpful, even if QCA does not become a major tool in their practice.”

Elizabeth H. McEneaney
University of Massachusetts Amherst

“The practical, how-to, nature of the text is very appealing to me as an instructor. I like the examples and appreciate the numerous figures used to illustrate processes and arguments for visual learners.”

James R. Martin
Creighton University

“The text introduces an important, specific approach to research.”

Tamar Ginossar
University of New Mexico

“I think the key strengths of this text are its organization and breadth. From an organization perspective, the wealth of resources and focus is essential for guiding the reader/learner toward practical keywords, i.e. language, and skills necessary to implement.”

Raymond Blanton
University of the Incarnate Word
Key features
  • Use of a concrete example that is woven across multiple chapters provides a thread of continuity that allows readers to follow the step-by-step process for understanding the method. 
  • A guiding heuristic helps orient the reader at the beginning of each chapter to understand where they are in the process of conducting an analysis.
  • Analytic checklists easily summarize the analytic process described in the chapter and serve as a reference.
  • Practice exercises provide essential practice and reinforce key concepts.
  • Helpful summaries and key points succinctly summarize main points of each chapter.

For instructors

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