在定性比较分析中,案例与因素比率和模型规范
Alrik Thiem1, Lusine Mkrtchyan1
1University of Lucerne, Lucerne, Switzerland.
概括
担心定性比较分析 (QCA) 在不利的案例对因素比率下失败是毫无根据的. 基准表,旨在防止QCA中的错误推断,实际上导致的错误比它们可以防止的更多.
科学领域:
- 社会科学 社会科学 社会科学
- 方法论 方法论 方法论
背景情况:
- 定性比较分析 (QCA) 是一种流行的实证研究方法.
- 有关QCA对非因果数据的因果谬误的易感性存在担忧,特别是在不利的案例与因素比率的情况下.
研究的目的:
- 质疑QCA易于因案例对因素比率的推断性分解的概念.
- 证明QCA的既定基准可能会导致更错误的推断.
主要方法:
- 该研究批判性地检查了定性比较分析 (QCA) 的方法论基础.
- 它分析了案例对因素比对QCA推理有效性的影响.
- 该研究评估了用于指导QCA应用的现有基准表的有效性.
主要成果:
- 基于病例对因素比率的QCA推断分解的担忧是毫无根据的.
- 基准表,旨在限制外源因素,矛盾地增加了错误的推断.
- 在QCA中依靠现有的现场知识更有效地进行有效的因果推理.
结论:
- 对定性比较分析 (QCA) 关于案例与因素比率的感知局限性没有支持.
- 质量评估中的方法基准可能会产生反作用,导致有缺陷的因果推断.
- 研究人员应该优先考虑实质知识,而不是严格的方法论基准,以获得可靠的QCA结果.
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