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Mixed-Effects Models for the Evaluation of Long- term Trends in Exposure Levels with an Example from the Nickel Industry

机译:用于评估暴露水平长期趋势的混合效应模型,以镍行业为例

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Longitudinal studies play an important role in evaluating the temporal behavior of occu- pational exposures. The purpose of this paper is to examine certain features of longitudinal data and to present a general conceptual framework by which these features may be taken into account so that statistically valid inferences can be made. Statistical methods that rely on the application of mixed-effects models are proposed for evaluating long-term trends in exposures to workplace contaminants. The mixed-effects model presented herein has fixed effects for trend components and random effects for workers, job groups, buildings and plants. These models differ from conventional techniques in that they accommodate hier- archically structured data and account for the correlation that may arise due to the clustering of measurements based on when and where the data were collected. While primary interest is focused on determining the magnitude of trends in exposure levels over time, the model also provides information about the magnitude of the sources of variation associated with different groupings of workers, Application of the mixed-effects model is illustrated with a large database of shift-ling personal exposure measurements collected on workers exposed to nickel aerosols in the nickel-producing industry.
机译:纵向研究在评估职业性暴露的时间行为方面起着重要作用。本文的目的是检查纵向数据的某些特征,并提出一个可以将这些特征考虑在内的一般概念框架,以便可以进行统计上有效的推断。提出了依赖于混合效应模型的统计方法来评估工作场所污染物暴露的长期趋势。本文介绍的混合效应模型对趋势分量具有固定效应,而对工人,工作组,建筑物和工厂则具有随机效应。这些模型与常规技术的不同之处在于,它们可以容纳分层结构的数据,并考虑到基于收集数据的时间和地点的测量结果聚类而可能引起的相关性。尽管主要关注点是确定暴露水平随时间变化趋势的幅度,但该模型还提供了有关与不同工人类别相关的变异源的幅度的信息,而混合效应模型的应用则通过一个大型数据库进行了说明。镍生产行业中暴露于镍气溶胶的工人的轮班个人暴露测量数据。

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