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.

定性分析与定量分析的融合趋势日益凸显，既往相关研究多聚焦于深度个案研究对深化统计结果认知的积极价值。本文则反其道而行之，探讨如何运用源自信息论（information theory）的简易定量方法，优化比较个案研究。本文依托多项具有代表性的「结构化聚焦比较（structured, focused comparison）」研究，通过为这些研究中所识别的各类因素提供系统性、可比较且可复现的不确定性与影响力测度，进一步拓展其研究结论。本文所提出的分析工具足够简易，可被广泛学者用于完善比较个案研究的结论，同时最大化其在甄别替代性解释、积累多项研究知识方面的效用。该方法尤其适用于国际研究中与政策相关的质性个案比较——这类研究此前往往回避使用更为复杂或适配性欠佳的定量工具。