极端数据的复发概率:一个帮助决策的帮助
1Department of Community Medicine, University of Cambridge, UK.
Lancet (London, England)
|October 2, 1993
概括
公共卫生专家现在可以使用一种新的"惊喜程度"方法来评估极端数据结果是否是偶然的. 这种简单的方法有助于检测排序数据的显著差异,以更好地监测公共卫生.
科学领域:
- 公共卫生 公共卫生
- 医疗服务管理 医疗服务管理
- 统计分析 统计分析
背景情况:
- 对公共卫生专家来说,评估常规收集的数据是否具有极端的结果是一个挑战.
- 区分真实模式和随机变化的需要强大的统计方法.
研究的目的:
- 引入一种简单的方法来测量排序数据中的"惊喜程度".
- 帮助检测时间和地点分类数据随机变化的重大偏差.
- 为审查后期数据和绩效指标提供一个工具.
主要方法:
- 描述了一种计算"惊喜程度"的新方法.
- 这种方法使用了一个精确概率值的表.
- 它是为排序数据而设计的,按时间和地点分类.
主要成果:
- 该方法提供了一种定量衡量方法,以评估观察到的模式发生在偶然的可能性.
- 它对于初步选有限数据或补充传统分析特别有用.
结论:
- 这种方法为公共卫生专家,审计师和卫生服务经理提供了宝贵的工具.
- 它提高了在绩效监测和例行数据分析中识别重大偏差的能力.
- 建议谨慎应用,特别是当数据有限或作为现有方法的补充时.
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