Qualitative Comparative Analysis in Mixed Methods Research and Evaluation

Leila Kahwati - RTI International
Heather Kane - RTI International
Mixed Methods Research Series
Qualitative Comparative Analysis in Mixed Methods Research and Evaluation
January 2019 | 312 pages | Sage US
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Description

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 sagepub.com/mmrs.



Contents

Editors' Introduction

Editors' Introduction

Preface

Preface

Acknowledgments

Acknowledgments

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
  • Overview
  • 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

APPENDIX: Recommended QCA Resources

Glossary

Glossary

References

References

Index

Index

Description

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 sagepub.com/mmrs.



Contents

Editors' Introduction

Editors' Introduction

Preface

Preface

Acknowledgments

Acknowledgments

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
  • Overview
  • 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

APPENDIX: Recommended QCA Resources

Glossary

Glossary

References

References

Index

Index

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Qualitative Comparative Analysis in Mixed Methods Research and Evaluation

Leila Kahwati , Heather Kane
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January 2019 | 312 pages | Sage US

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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 sagepub.com/mmrs.




Table Of Contents:

  • Editors' Introduction
  • Preface
  • Acknowledgments
  • 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
  • Overview
  • 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
  • Glossary
  • References
  • Index

Recent Product Reviews:

“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

Recommendations