Vis Barbara, Dul Jan
Department of Political Science and Public Administration, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Rotterdam School of Management, Erasmus University Rotterdam, Rotterdam, the Netherlands.
Sociol Methods Res. 2018 Nov;47(4):872-899. doi: 10.1177/0049124115626179. Epub 2016 Feb 3.
Analyzing relationships of necessity is important for both scholarly and applied research questions in the social sciences. An often-used technique for identifying such relationships- (fsQCA)-has limited ability to make the most out of the data used. The set-theoretical technique fsQCA makes statements (e.g., "a condition or configuration is necessary or not for an outcome"), thereby ignoring the variation . We propose to apply a recently developed technique for identifying relationships of necessity that can make both statements and , thus making full use of variation in the data: (NCA). With its ability to also make statements ("a specific level of a condition is necessary or not for a specific level of the outcome"), NCA can complement the analysis of necessity with fsQCA.
分析必要性关系对于社会科学中的学术研究问题和应用研究问题都很重要。一种常用于识别此类关系的技术——模糊集定性比较分析（fsQCA）——充分利用所使用数据的能力有限。集理论技术fsQCA做出陈述（例如，“一种条件或配置对于一种结果是否必要”），从而忽略了变异性。我们建议应用一种最近开发的用于识别必要性关系的技术，该技术既可以做出陈述（1）又可以做出陈述（2），从而充分利用数据中的变异性：必要性分析（NCA）。由于必要性分析（NCA）也能够做出陈述（3）（“一种条件的特定水平对于结果的特定水平是否必要”），它可以用模糊集定性比较分析（fsQCA）对必要性的分析进行补充。
