Summary and Keywords
Recent methodological work on systematic case selection techniques offers ways of choosing cases for in-depth analysis such that the probability of learning from the cases is enhanced. This research has undermined several long-standing ideas about case selection. In particular, random selection of cases, paired or grouped selection of cases for purposes of controlled comparison, typical cases, and extreme cases on the outcome variable all appear to be much less useful than their reputations have suggested. Instead, it appears that scholars gain the most in terms of making new discoveries about causal relationships when they study extreme cases on the causal variable or deviant cases.
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