改进数据前和数据后的推断分析
David Trafimow1, Tingting Tong2, Tonghui Wang2
1Department of Psychology, New Mexico State University.
研究人员可以通过采用新的两步过程来改善统计实践. 这涉及先验程序参数估计数据收集和估计后数据的概率优势,超越传统的意义测试.
科学领域:
- 心理学 心理学 心理学
- 统计 统计 统计 统计
背景情况:
- 传统的研究方法包括数据前的功率分析和数据后的意义测试.
- 零假设显著性测试提供有限的信息,容易被滥用.
- 替代后数据方法可以提供有关概率结果的更有用信息.
研究的目的:
- 为研究人员提出修订的两步统计程序.
- 倡导从传统的意义测试转向概率结果估计.
- 引入先验程序作为传统功率分析的替代品.
主要方法:
- 该研究建议将传统的功率分析取代以先验程序,专注于参数估计.
- 它建议以后数据分析的方式,根据治疗方式,估计更好或更糟的概率,作为后数据分析.
- 这种方法是基于Trafimow及其同事的工作.
主要成果:
- 与意义测试相比,拟议的方法提供了更高等级的有用信息.
- 它允许估计与不同结果相关的概率优势或缺点.
- 这有助于对治疗效果有更细致的了解.
结论:
- 应该取代传统的两步统计过程 (功率分析和显著性测试).
- 建议采用新的两步程序:先验参数估计,然后进行后数据概率性结果评估.
- 这种修订后的方法提高了研究结果的实用性和可解释性.
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