实验数据的变换试验
Charles A Holt1, Sean P Sullivan2
1Department of Economics, University of Virginia, Charlottesville, VA 22903 USA.
概括
非参数转换试验为分析实验数据提供了灵活的框架,特别是对有限的观测数据. 这种方法在各种实验设计和数据结构中提供了强大的统计推理.
科学领域:
- 统计 统计 统计 统计
- 计量经济学 计量经济学
- 社会科学研究 社会科学研究
背景情况:
- 实验数据分析通常需要强大的统计推理方法.
- 传统的统计测试可能有局限性,特别是在社会科学实验中常见的小样本大小.
- 当违反分布假设时,非参数方法提供了替代方法.
研究的目的:
- 调查和倡导在分析实验数据时使用非参数变换测试.
- 为了证明参数测试的灵活性和广泛适用性,超出基于等级的方法.
- 鼓励更广泛地采用排列测试作为实验中的统计推理的综合框架.
主要方法:
- 使用观察到的数据特征的随机化或变换来得出统计推理.
- 构建基于测量观察的测量观察的测试,而不仅仅是等级.
- 将变量概念应用于多种处理,有序效应和复杂数据结构的场景,包括麻烦变量.
主要成果:
- 当只有很少的独立观测可用时,变换试验是有价值的.
- 换位推理是建立了基于等级的测试的基础 (例如,威尔科克森,曼-惠特尼).
- 变试验可以扩展到测量数据,多次处理和复杂的数据结构,比传统方法有优势.
结论:
- 变换测试为实验环境中的统计推理提供了一个灵活和全面的框架.
- 该方法对于小样本大小和复杂的实验设计特别有用.
- 鼓励实验者利用排列测试作为常见过度使用的统计程序的多功能替代方案.
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