选择性推断的幽灵在时空空间趋势分析的分析
Oliver Gutiérrez-Hernández1, Luis V García2
1Department of Geography, University of Málaga. Bulevar Louis Pasteur 27, 29010 Málaga, Spain.
The Science of the total environment
|December 5, 2024
概括
在时空趋势分析中的选择性推断忽略了多个测试问题. 解决多重性问题对于网格数据分析的准确结果至关重要,确保真正的统计学意义.
科学领域:
- 环境科学环境科学
- 地质统计学 在地质统计学
- 统计分析 统计分析
背景情况:
- 时空趋势分析通常涉及对网格数据的众多统计测试.
- 选择性推断,只关注预先定义的显著性值 (例如,p < 0.05),忽视执行的测试总数.
- 这导致多重性问题,膨胀了虚假发现的机会.
研究的目的:
- 审查空间时间趋势分析中的多重性和选择性推断的挑战.
- 讨论在网格数据中管理膨胀虚假结果的方法.
- 促进科学研究的透明度和可复制性.
主要方法:
- 对多重性和选择性推断的现有文献的审查.
- 对p值的统计调整方法的讨论.
- 在趋势分析中使用网格数据的说明性示例.
主要成果:
- 未经纠正的多重性和选择性推断可以创建虚幻的显著趋势.
- 严格的校正方法是必要的,以揭示真正的统计模式.
- 统计学显著性取决于所执行的全部测试,而不仅仅是低于值的测试.
结论:
- 正确解决多重性对于可靠的时空空间趋势分析至关重要.
- 方法和报告的透明度提高了研究的可复制性.
- 了解统计测试的全部上下文,包括非显著的测试,对于准确的解释至关重要.
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