Reducing Uncertainty: Information Analysis for Comparative Case Studies

The increasing integration of qualitative and quantitative analysis has largely focused on the benefits of in-depth case studies for enhancing our understanding of statistical results. This article goes in the other direction to show how some very straightforward quantitative methods drawn from information theory can strengthen comparative case studies. Using several prominent structured, focused comparison studies, we apply the information-theoretic approach to further advance these studies' findings by providing systematic, comparable, and replicable measures of uncertainty and influence for the factors they identified. The proposed analytic tools are simple enough to be used by a wide range of scholars to enhance comparative case study findings and ensure the maximum leverage for discerning between alternative explanations as well as cumulating knowledge from multiple studies. Our approach especially serves qualitative policy-relevant case comparisons in international studies, which have typically avoided more complex or less applicable quantitative tools.