一个双阶段的随机效应估计器,用于对每统计寿命值的元分析
Stephen C Newbold1, Chris Dockins2, Nathalie Simon2
1Department of Economics, University of Wyoming, Laramie, Wyoming, United States of America.
PloS one
|June 13, 2025
概括
一种新的元分析方法通过计算各种错误来改善每统计寿命 (VSL) 估计的价值. 这种方法提供了更好的统计效率,并与政策相关研究的现有方法相比较有利.
科学领域:
- 计量经济学 计量经济学
- 环境经济学环境经济学
- 卫生经济学 卫生经济学
背景情况:
- 综合公布的每统计寿命 (VSL) 的估计值对经济政策和风险评估至关重要.
- 现有的元分析方法可能无法充分解决VSL研究中数据不平衡和各种错误来源的复杂性.
- 准确的VSL估计需要强大的统计方法,可以处理初级研究中的异质性.
研究的目的:
- 开发和评估一种新的两阶段随机效应元分析估计器,用于VSL.
- 用蒙特卡洛模拟来评估拟议估计器的性能.
- 将新估计器与其他常用的元分析技术进行比较.
主要方法:
- 开发一个双阶段随机效应元分析模型.
- 适应不平衡的面板,区分集团内部和集团间的错误 (采样和非采样).
- 在构建数据集上的蒙特卡洛模拟实验,以在不同条件下测试估计器性能.
主要成果:
- 当在组内非采样误差差异均时,拟议的元估计器的性能最好.
- 这种同质性假设通过保留两个非采样错误级别的自由度来提高统计效率.
- 与其他几种替代元分析方法相比,新估计器表现良好,包括其他两阶段方法.
结论:
- 开发的双阶段随机效应元分析估计器为合成VSL估计提供了一个统计学上高效和稳健的方法.
- 该方法有效地处理了VSL文献中常见的数据复杂性和错误结构.
- 在113个VSL估计数据集上的演示证实了其在政策相关的经济研究中的实际适用性.
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