更新顺势疗法算法:处理确认偏差
Lex Rutten1, Rainer Schäferkordt2, José E Eizayaga3
1Independent Researcher, Breda, The Netherlands.
Homeopathy : the journal of the Faculty of Homeopathy
|August 27, 2025
概括
通过使用统计工具来解决确认偏差,可以改进顺势疗法表述算法. 数学纠正与专家知识相结合, 有助于提升顺势疗法症状分析的准确性.
科学领域:
- 顺势疗法
- 医疗信息学
- 统计分析
背景情况:
- 顺势疗法使用算法进行诊断,
- 现代化的顺势疗法需要统计工具和偏差纠正.
研究的目的:
- 在顺势疗法病例数据中分析概率比率 (LRs) 的模式.
- 调查在顺势疗法中纠正确认偏差的方法.
主要方法:
- 系统收集731个"最佳慢性顺势疗法病例" (BCHC).
- 使用统计工具分析概率比率 (LR) 的频率分布.
- 应用数学转换和专家知识进行偏差校正.
主要成果:
- 频率分布的LR显示了在中间的逻辑线性进展,在末端的斜率上升.
- 中间LR的确认偏差是使用指数算法的数学纠正.
- 7的LR被确定为大多数症状的适当最大值,BCHC和历史数据之间没有显著差异.
结论:
- 通过结合理论,专家知识和数学,可以部分纠正顺势疗法的确认偏差.
- 这项研究发现,当代和历史的顺势疗法数据在确认偏差模式中具有显著的相似性.
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