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职业队列时间尺度。

Occupational Cohort Time Scales.

作者信息

Deubner David C, Roth H Daniel

机构信息

From Materion Brush Inc. (Dr Deubner), Elmore; and Roth Associates (Dr Roth), Englewood, Ohio.

出版信息

J Occup Environ Med. 2015 Jun;57(6):643-8. doi: 10.1097/JOM.0000000000000412.

Abstract

PURPOSE

This study explores how highly correlated time variables (occupational cohort time scales) contribute to confounding and ambiguity of interpretation.

METHODS

Occupational cohort time scales were identified and organized through simple equations of three time scales (relational triads) and the connections between these triads (time scale web). The behavior of the time scales was examined when constraints were imposed on variable ranges and interrelationships.

RESULTS

Constraints on a time scale in a triad create high correlations between the other two time scales. These correlations combine with the connections between relational triads to produce association paths. High correlation between time scales leads to ambiguity of interpretation.

CONCLUSIONS

Understanding the properties of occupational cohort time scales, their relational triads, and the time scale web is helpful in understanding the origins of otherwise obscure confounding bias and ambiguity of interpretation.

摘要

目的

本研究探讨高度相关的时间变量(职业队列时间尺度)如何导致混杂和解释的模糊性。

方法

通过三个时间尺度(关系三元组)的简单方程以及这些三元组之间的联系(时间尺度网络)来识别和组织职业队列时间尺度。当对变量范围和相互关系施加约束时,研究时间尺度的行为。

结果

对三元组中一个时间尺度的约束会在其他两个时间尺度之间产生高度相关性。这些相关性与关系三元组之间的联系相结合,产生关联路径。时间尺度之间的高度相关性导致解释的模糊性。

结论

了解职业队列时间尺度的属性、它们的关系三元组以及时间尺度网络,有助于理解原本模糊的混杂偏倚和解释模糊性的根源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e519/4448669/188338358d37/joem-57-643-g001.jpg

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