Replication Data for: \"Guarding Against False Positives in Qualitative Comparative Analysis\"

The various methodological techniques that fall under the umbrella description of qualitative comparative analysis (QCA) are increasingly popular for modeling causal complexity and necessary or sufficient conditions in medium-N settings. Because QCA methods are not designed as statistical techniques, however, there is no way to assess the probability that the patterns they uncover are the result of chance. Moreover, the implications of the multiple hypothesis tests inherent in these techniques for the false positive rate of the results are not widely understood. This article fills both gaps by tailoring a simple permutation test to the needs of QCA users and adjusting the Type I error rate of the test to take into account the multiple hypothesis tests inherent in QCA. An empirical application—a reexamination of a study of protest-movement success in the Arab Spring—highlights the need for such a test by showing that even very strong QCA results may plausibly be the result of chance.

归属于定性比较分析（Qualitative Comparative Analysis，QCA）范畴的各类方法论技术，当前在中等样本量（medium-N）场景下用于建模因果复杂性及必要或充分条件时愈发流行。然而，由于QCA方法并非作为统计技术设计，因此无法评估其所揭示的模式纯属偶然的概率。此外，这些技术内在蕴含的多重假设检验对结果假阳性率的影响，尚未得到广泛认知。本文通过为QCA使用者量身定制一款简易置换检验，并调整该检验的一类错误率以适配QCA中内在的多重假设检验情形，填补了上述两项空白。一项实证应用——即对一项关于阿拉伯之春抗议运动成功与否的研究的重新检验——通过展示即便极具说服力的QCA结果也有可能纯属偶然，凸显了此类检验的必要性。