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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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February 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

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