米特宁宁和努尔明宁的得分统计数据经过修订
Antonio Martín Andrés1, Francisco Gayá Moreno2, María Álvarez Hernández3
1Biostatistics, Faculty of Medicine, University of Granada, Granada, Spain.
Journal of biopharmaceutical statistics
|February 9, 2024
概括
新的统计数据 (AU类型和AUM类型) 与S类型和MN类型的统计数据相比,在两个比例上改善了推断. 在AUM类型的统计数据中,差异,比率和赔率比率测试表现最好.
科学领域:
- 生物统计学 生物统计学
- 统计推理 统计推理
- 进行比较分析分析.
背景情况:
- 对两个比例 (差异,比率,赔率比率) 的推理对于独立样本至关重要.
- 现有的得分 (S型) 和Miettinen-Nurminen (MN型) 统计数据在偏差纠正方面存在局限性.
研究的目的:
- 引入和评估新的非对称统计 (AU类型和AUM类型) 用于比例推断.
- 为了比较S型,MN型,AU型和AUM型统计数据的性能.
- 将分析扩展到多项式分布.
主要方法:
- 对于非对称统计的纠正因子的推导.
- 在不同测试 (一/两尾) 和参数 (差异,比率,赔率比率) 中对S,MN,AU和AUM统计数据的性能评估.
- 根据多项分布假设进行评估.
主要成果:
- 在MN类型的统计中使用的 (N-1) / N因子仅对两个比例的平等测试是正确的.
- AU类型和AUM类型的统计数据提供了更正的因子.
- AUM类型的统计表现出卓越的表现,紧随其后的是MN类型和AU类型的统计.
结论:
- 建议使用AUM类型的统计数据来对两个比例进行可靠的推断.
- 该研究为各种比较分析提供了准确的统计方法.
- 新发现扩展到多项式数据,MN和AU的统计数据显示了几率比率测试的相似性.
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