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Quantifying the Qualitative
Information Theory for Comparative Case Analysis
By: Ekaterina Drozdova, Kurt Taylor Gaubatz
Paperback | 12 January 2016 | Edition Number 1
At a Glance
192 Pages
23.5 x 19.05 x 1.04
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The approach the authors present is exceedingly simple and transparent and very practical for a wide range of analysts as well as practitioners providing a straightforward metric for comparing factor impacts that can be effectively communicated to the reader. Qualitative and mixed methods analysis stands to benefit from more accessible analytic tools that can reduce bias and improve the knowledge gained from comparative case studies.
The techniques the authors describe require only minimal quantitative skills. Appendix A provides a walkthrough of Excel or Google sheets for needed calculations along with sample Excel sheets and Appendix B provides and implementation of the methods in the open source language for those who prefer that approach. These appendixes are contained in the book and on the accompanying website.
About the Author
Ekaterina aKatyaa Drozdova, PhD, is an assistant professor of political science in the School of Business, Government, and Economics at Seattle Pacific University.
She regularly teaches courses on aWar, Peace, and World Order,a aCounterterrorism and National Security,a aMethods of Political Analysis,a aInternational Political Economya and aThe West and the Worlda as well as supervises independent study and honors research projects. Professor Drozdova earned her PhD in information systems from New York Universityas (NYU) Stern School of Business, Department of Information, Operations, and Management Sciences. Her MA in international policy studies and BA in international relations are from Stanford University. Katyaas work focuses on understanding how systemic risks and technology choices help shape operational strategiesawith emphasis on organizational threat prevention and response applications in diverse contexts: from countering terrorist networks to securing energy, cyber, and other critical infrastructures.
Professor Drozdova is an affiliate with the Empirical Studies of Conflict Project (ESOC) at Stanford and Princeton Universities, and a principal investigator for a research program, aMining Afghan Lessons from Soviet Eraa (MALSE), based in part on archival study with forward-looking applications. MALSE was funded by the U.S. Office of the Secretary of Defenseas (OSD) Human, Social, Cultural and Behavioral (HSCB) sciences program through the Office of Naval Researchas (ONR) Expeditionary Maneuver Warfare and Combating Terrorism Department. She is actively involved with leading military, policy, law enforcement, business, and other professionals in identifying critical challenges and formulating effective threat responses across multiple global security areas.
Her recent research and publications have addressed questions of U.S. national and international security and counterterrorism strategies, with emphasis on understanding and countering asymmetric low-tech threats in the high-tech age as well as on organizationsa use of their human and technological networks for survival in hostile and complex environments. Professor Drozdova has been a fellow at NYUas Alexander Hamilton Center for Political Economy and Stanford Universityas Hoover Institution on War, Revolution, and Peace as well as Stanfordas Center for International Security and Cooperation (CISAC).
At CISAC, she has also been a member of the Consortium for Research on Information Security and Policy funded by the U.S. National Security Agency (NSA) and comprised of leading scholars as well as industry and government practitioners, including former directors of Lawrence Livermore National Laboratory (LLNL) and Defense Advanced Research Projects Agency (DARPA).
Kurt Taylor Gaubatz, PhD, is an associate professor in the Graduate Program in International Studies at Old Dominion University. In addition to courses in international relations and international law, he regularly teaches research methods and advanced statistics. He has previously taught methodology and formal modeling as a faculty member at Stanford University and at Oxford University (Nuffield College), where he was the visiting John G. Winant Lecturer in American Foreign Policy. He has also served as the Susan Luise Dyer Peace Fellow at the Hoover Institution at Stanford University, and received a Pew Faculty Fellowship from the Kennedy School of Government at Harvard University.
Professor Gaubatzas most recent book is A Survivoras Guide to R (SAGE 2015), which is a broad and cross-disciplinary introduction to the R language for statistical programming. He is also the author of Elections and War (Stanford University Press, 1999), which is a study of the electoral politics of military conflict. His work on international law and on the relationship between domestic politics and international relations has appeared in a number of leading journals. His work on political modeling has received funding from the US Department of Defense. Professor Gaubatz earned an AB in economics from U.C. Berkeley, an MALD in international law from the Fletcher School of Law and Diplomacy, an MDiv in theology from Princeton Theological Seminary, and a PhD in political science from Stanford University.
Industry Reviews
CHAPTER 2: The Information Revolution Information Theory for the Information Age Whatas Under the Hood: A Primer on 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 MethodaIf 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 1aEcology: Information Analysis for Tropical Forest Loss Example 2aEducation: Accounting for Teaching Quality Example 3a Medicine: Effective Nursing Care
CHAPTER 6: Sensitivity AnalysisaEntropy, 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 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: Conclusions 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 Extensions
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
ISBN: 9781483392479
ISBN-10: 1483392473
Published: 12th January 2016
Format: Paperback
Language: English
Number of Pages: 192
Audience: College, Tertiary and University
Publisher: SAGE PUBLICATIONS
Country of Publication: GB
Edition Number: 1
Dimensions (cm): 23.5 x 19.05 x 1.04
Weight (kg): 0.32
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