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Modeling Nonlinear Dose-Response Relationships in Epidemiologic Studies: Statistical Approaches and Practical Challenges

机译:流行病学研究中的非线性剂量反应关系建模:统计方法和实际挑战

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摘要

Non-linear dose response relationships pose statistical challenges for their discovery. Even when an initial linear approximation is followed by other approaches, the results may be misleading and, possibly, preclude altogether the discovery of the nonlinear relationship under investigation. We review a variety of straightforward statistical approaches for detecting nonlinear relationships and discuss several factors that hinder their detection. Our specific context is that of epidemiologic studies of exposure-outcome associations and we focus on threshold and J-effect dose response relationships. The examples presented reveal that no single approach is universally appropriate; rather, these (and possibly other) nonlinearities require for their discovery a variety of both graphical and numeric techniques.
机译:非线性剂量反应关系对其发现提出了统计挑战。即使使用其他方法进行初始线性逼近,结果也可能会产生误导,并可能完全排除了所研究的非线性关系的发现。我们回顾了用于检测非线性关系的各种直接统计方法,并讨论了阻碍其检测的几个因素。我们的具体背景是暴露-结果关联的流行病学研究,我们关注阈值和J效应剂量反应关系。所举的例子表明,没有一种方法普遍适用;相反,这些(可能还有其他)非线性需要发现各种图形和数字技术。

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