在普通和有条件的逻辑回归和Poisson回归中调整Berkson错误
Tamer Oraby1, Santanu Chakraborty2, Siva Sivaganesan3
1School of Mathematical and Statistical Sciences, University of Texas Rio Grande Valley, Edinburg, TX, USA. tamer.oraby@utrgv.edu.
BMC medical research methodology
|October 10, 2023
概括
估计职业电磁场 (EMF) 暴露的最佳方法取决于暴露模型. 对于马分布的曝光,算术平均值是最佳的;对于逻辑正常,几何平均值是最好的. 伯克森误差调整可以提高非分层分析的准确性.
科学领域:
- 职业健康 职业健康 职业健康 职业健康
- 流行病学 流行病学
- 环境健康 环境健康
背景情况:
- 该INTEROCC研究调查了七个国家的职业暴露和脑癌风险.
- 职业暴露矩阵 (JEM) 用于估计职业暴露,如电磁场 (EMF),当个人数据不可用时.
- 之前的研究使用了JEM中EMF的日志正常暴露分布.
研究的目的:
- 通过使用加拿大INTEROCC数据,从工作暴露矩阵 (JEM) 中确定最佳的EMF暴露替代物.
- 评估Berkson对EMF暴露替代品的错误调整的有效性.
- 将马分布式暴露模型与以前使用的日志正常模型进行比较.
主要方法:
- 利用了来自INTEROCC队列研究的加拿大数据.
- 比较了三种由JEM衍生的EMF暴露替代品和一个经过错误调整的伯克森替代品.
- 在Poisson和条件后勤回归框架内检查了马分布式暴露模型.
- 在Berkson错误调整中应用了概率函数的数值近似.
主要成果:
- 伯克森误差调整方法在非分层分析中准确估计瘤风险,使用玛暴露模型.
- 算术平均值是马分布暴露的最佳暴露替代品.
- 在分层分析中,没有经过测试的方法能够准确估计风险.
- 最优的暴露替代品取决于模型:对玛的算术平均值,对日志常态分布的几何平均值.
结论:
- 选择电磁场暴露替代品取决于底层暴露分布模型.
- 本研究为基于JEM的职业暴露评估中的伯克森误差调整提供了改进的方法.
- 结果为应用JEM和调整流行病学研究中的Berkson错误提供了实际指导.
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