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).

Case Selection

Before we can turn to our much-anticipated step-by-step guide to using information analysis for comparative case studies, we need to pause for a serious conversation about case selection. It should go without saying that the selection of cases is a critical element of case study research strategies. But this subject is of such paramount importance that we need to devote a full chapter to its meanings and methods. Of course, case selection is an important issue for large-N studies as well. In that world, however, there is a simple clarion call for making sure that case selection is plausibly random or, failing that, for the use of compensatory quantitative techniques. Small-n work, by definition, is much more vulnerable to case selection issues. ...

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