Case-based methods have a long history in the social sciences. They are extensively used and raise many practical and theoretical questions. This book provides a comprehensive, critical examination of case-oriented research. It offers concrete proposals about the best research methods and provides an unparalleled guide to the emergence and complexity of the field.
"Analytic Induction (AI) focuses on a select set of cases displaying the same outcome and seeks to identify antecedent conditions shared by such cases. Shared antecedent conditions, in turn, may be interpreted as "causal recipes" for the outcome, especially when they make sense as jointly contributing conditions. As a method of social research, AI differs fundamentally from conventional, variation-based approaches. AI's outcome is a constant; the set of cases selected for analysis all display the same outcome. Conventional variable-oriented research, by contrast, is centered on the task of accounting for variation in a dependent variable. The approach introduced in this book offers an array of set-analytic tools for answering research questions regarding qualitative outcomes and provides a new template for cross-case analysis"--