Replication data for: Case Selection via Matching

This paper shows how statistical matching methods can be used to select “most similar” cases for qualitative analysis. I first offer a methodological justification for research designs based on selecting most similar cases. I then discuss the applicability of existing matching methods to the task of selecting most similar cases and propose adaptations to meet the unique requirements of qualitative analysis. Through several applications, I show that matching methods have advantages over traditional selection in most-similar case designs: they ensure that “most-similar” cases are in fact most similar, they make scope conditions, assumptions, and measurement explicit, and they make case selection transparent and replicable.

本文探讨了如何运用统计匹配方法（statistical matching methods）选取用于质性分析的「最相似案例」。首先，本文为基于最相似案例选取的研究设计提供了方法论层面的论证依据；随后，本文讨论了现有匹配方法应用于最相似案例选取任务的适用性，并针对质性分析的独特需求提出适配方案。通过多项应用案例，本文证明相较于最相似案例研究设计中的传统选样方法，匹配方法具备多重优势：其一，能够确保所选取的「最相似案例」确实具备高度相似性；其二，可使研究的范围条件、前提假设与测量方式清晰明确；其三，能够让案例选取过程具备透明度与可复现性。