零假设显著性测试和p值的二分化:错误的人类状态
Edward Mezones-Holguín1, Ali Al-Kassab-Córdova1, Percy Soto-Becerra2
1Centro de Excelencia en Investigaciones Económicas y Sociales en Salud, Universidad San Ignacio de Loyola, Lima, Perú.
Revista peruana de medicina experimental y salud publica
|February 12, 2025
概括
零假设显著性测试 (NHST) 和p值在频率统计学中很常见,但因对科学可重复性危机做出贡献而受到批评. 这篇评论考察了NHST.
科学领域:
- 生物统计学 生物统计学
- 医学研究方法学 医学研究方法学
- 科学完整性 科学完整性
背景情况:
- 医疗保健决策依赖于强有力的科学证据.
- 使用频率主义或贝叶斯式方法的统计分析对于生成证据至关重要.
- 零假设显著性测试 (NHST) 和p值是普遍存在的频率主义方法.
研究的目的:
- 提供NHST发展的历史概述.
- 总结NHST的方法,并讨论相关的争议.
- 解决NHST在生物医学研究中的滥用和误解问题.
主要方法:
- 关于NHST发展和应用的文献综述.
- 对NHST的批评和局限性的分析.
- 检查NHST在可复制性危机中的作用.
主要成果:
- 尽管NHST的使用广泛,但它与重大争议和局限性有关.
- 误解和滥用NHST有助于科学挑战.
- 频率主义方法,特别是NHST,正在审查其对研究可重复性的影响.
结论:
- 由于NHST的局限性,它在生物医学研究中的有用性受到质疑.
- 了解NHST的缺点对于提高科学严谨性至关重要.
- 为了应对可重复性危机,可能需要采用替代的统计方法.
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