Samuels S J, Lemasters G K, Carson A
Am Ind Hyg Assoc J. 1985 Aug;46(8):427-33. doi: 10.1080/15298668591395111.
An important step in studies relating worker health to industrial exposure is the estimation of mean exposure levels. The investigator frequently has to rely on industrial hygiene measurements collected for other purposes. Samples may have been taken at several companies on different dates, and on each occasion multiple individual samplers may have been employed. Often it is not recognized that readings from such a hierarchical arrangement are correlated; for example, samples taken at the same time and location are more alike than samples taken on different days. This correlation invalidates the commonly used standard errors of sample means and the usual sample standard deviation. A component of variance analysis is suggested which quantifies within-day, between-day and between-company variation. Estimators of mean exposure are presented with correct standard errors. The techniques are illustrated by a small set of data and by a recent study of exposures to styrene in 36 companies manufacturing reinforced plastics.
在将工人健康与工业暴露相关联的研究中,一个重要步骤是估计平均暴露水平。研究者常常不得不依赖于为其他目的而收集的工业卫生测量数据。样本可能是在不同日期从几家公司采集的,而且每次可能都使用了多个个体采样器。人们常常没有认识到,这种分层安排的读数是相关的;例如,在同一时间和地点采集的样本比在不同日期采集的样本更为相似。这种相关性使常用的样本均值标准误差和通常的样本标准差无效。本文提出了一种方差分析方法,该方法可量化日内、日间和公司间的变异。给出了具有正确标准误差的平均暴露估计值。通过一小组数据以及最近一项对36家制造增强塑料公司的苯乙烯暴露情况的研究对这些技术进行了说明。