Quantifying the Qualitative

Quantifying the Qualitative
Information Theory for Comparative Case Analysis

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© 2017 | 192 pages | SAGE Publications, Inc
Quantifying the Qualitative presents a systematic approach to comparative case analysis based on insights from information theory. This new method, which requires minimal quantitative skills, helps students, policymakers, professionals, and scholars learn more from comparative cases. The approach avoids the limitations of traditional statistics in the small-n context and allows analysts to systematically assess and compare the impact of a set of factors on case outcomes with easy-to-use analytics. Rigorous tools reduce bias, improve the knowledge gained from case studies, and provide straightforward metrics for effectively communicating results to a range of readers and leaders.
CHAPTER 1: Enhancing Small-n Analysis: Information Theory and the Method of Structured-Focused Comparison
Why Quantify the Qualitative? Enhancing Qualitative Analysis With Information Theory  
Who Needs to Quantify the Qualitative?  
Information and Action Under Uncertainty  
Origins and Motivations  
From Cryptography and Communication to Comparative Case Studies  
Making Qualitative Analysis of Information Systematic: The Method of Structured-Focused Comparison  
Information Theory and Metrics for Qualitative Learning  
A Roadmap for Quantifying the Qualitative  
CHAPTER 2: The Information Revolution
Information Theory for the Information Age  
What’s Under the Hood: A Primer A Primer on Logarithms and Probability for Small-n Analysis  
Information Uncertainty Measures  
Fundamental Contributions of Information Theory  
The Growing Use of Information Metrics  
A Note for Practitioners: From Analytics to Action  
CHAPTER 3: Case Selection
Research Design and Information Theory  
Case Selection Strategies and Challenges  
Coding Cases  
Case Selection and the Advantages of Information Theoretic Analysis  
CHAPTER 4: The Information Method—If You Can Count, You Can Do It
Quantify: Setting up a Truth Table for Comparative Case Analysis  
Count: Calculating the Probabilities  
Compute: Computing the Uncertainty Measures  
Compare: Understanding the Outcomes  
CHAPTER 5: Information Metrics at Work—Three Examples
Example 1—Ecology: Information Analysis for Tropical Forest Loss  
Example 2—Education: Accounting for Teaching Quality  
Example 3— Medicine: Effective Nursing Care  
CHAPTER 6: Sensitivity Analysis—Entropy, Inference, and Error
Confidence Intervals and the Information Metric  
Analytic Leverage for a Study of Environmental Incentives  
The Information Metric and the Problem of Inference  
Sensitivity Analysis  
Dropped-Case Analysis  
Outcome Coding Sensitivity  
CHAPTER 7: The QCA Connection
Understanding Qualitative Case Analysis (QCA)  
QCA and Causal Complexity  
Where QCA and Information Metrics Differ  
Examples of Enhancing QCA with Information Metrics  
Selected Introductory QCA Resources  
QCA Software and Web Resources  
CHAPTER 8: Conclusion
Information, Research, and the Digital Era  
Reducing Uncertainty and Improving Judgment: Using Information Analysis in the Real World  
The Limits and Further Possibilities for Information Analysis  
APPENDIX A: Using Excel for Information Metrics
Step One: Enter Data  
Step Two: Probability Calculations  
Step Three: Entropy and Mutual Information Metrics  
APPENDIX B: Using R for Information Metrics
Example 1: Deriving Information Metrics from Conditional Probabilities  
Example 2: Deriving Information Metrics with the abcd Method  


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Key features


  • Wide interdisciplinary applicability with step-by-step examples drawn from a number of sciences and professional fields, including defense, medicine, education, and ecology, demonstrate the powerful application of information metrics to comparative case studies.
  • Presentation of techniques that can be used broadly allows readers to apply what they learn in settings including business, finance, health care, environmental policy, security, and other settings where consequential decisions are made under conditions of uncertainty and complexity.
  • Clear and accessible prose illustrated by concrete and carefully explained examples makes the methods easy to understand and immediately applicable.
  • A concise review of the exciting intellectual foundations of information theory motivates student interest by linking research with critical real-world problems, from World War II cryptography to Cold War nuclear deterrence to solving modern cyber-security and strategic challenges.
  • Appendices available both in the book and online provide a walkthrough of Excel or Google sheets for automating simple calculations, along with sample Excel sheets (Appendix A) and an implementation of the methods in the open source language, R (Appendix B).

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ISBN: 9781483392479