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Case Studies and Causal Inference delivers a self-contained and balanced discussion of the case study method on the basis of an integrative, but clear-cut framework for small-n research. It deals with case studies that develop new hypotheses for hitherto unexplained phenomena, perform classic hypothesis testing, and address puzzles in order to refine existing hypotheses. The framework further covers small-n research concerned with a range of causal effects (correlations and set relations), causal mechanisms, and the integration of both in causal explanations. By applying the framework to all steps in the research process, Rohlfing demonstrates how it can contribute to the rigor of empirical case studies and the advancement of social science theory. On the methodological side, the integrative perspective forms the basis for improving the case study method in multiple directions. Throughout the book, arguments are illustrated with numerous empirical examples from political science, public administration, and sociology.
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