Examining the robustness of observational associations to model, measurement and sampling uncertainty with the vibration of effects framework.
Examining the robustness of observational associations to model, measurement and sampling uncertainty with the vibration of effects framework.
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DOI：
10.1093/ije/dyaa164
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发表时间：
2021-03-03
影响因子：
7.7
通讯作者：
Boulesteix AL
中科院分区：
文献类型：
--
作者：
Klau S;Hoffmann S;Patel CJ;Ioannidis JP;Boulesteix AL
观察相关性研究的结果可能会因研究设计和分析选择以及测量误差而有所不同。重要的是要了解不同因素对产生变量结果的相对贡献，包括低样本量，研究人员在模型选择上的灵活性，以及感兴趣变量和调整变量的测量误差。我们定义了采样不确定度、模型不确定度和测量不确定度，并扩展了效应振动的概念，以便在一个共同的框架中研究这三种不确定度。在实际应用中，我们使用来自国家健康和营养检查调查的数据在Cox模型中检查这些类型的不确定性。此外，我们在模拟研究中分析了不同样本量的抽样、模型和测量不确定度的行为。所有类型的不确定性都与效应估计中潜在的较大变异性有关。在大多数情况下，感兴趣变量的测量误差会减弱真实效果，但偶尔会导致高估。当我们同时考虑感兴趣变量和调整变量的测量误差时，由于可以观察到对真实效果的系统性低估和高估，因此影响的振动甚至更难以预测。模拟数据的结果表明，即使在大样本量下，测量和模型振动仍然是不可忽略的。抽样、模型和测量的不确定性会对观测关联的稳定性产生重要影响。我们建议系统地研究和报告这些类型的不确定性，并在一个共同的框架中对它们进行比较。
The results of studies on observational associations may vary depending on the study design and analysis choices as well as due to measurement error. It is important to understand the relative contribution of different factors towards generating variable results, including low sample sizes, researchers’ flexibility in model choices, and measurement error in variables of interest and adjustment variables. We define sampling, model and measurement uncertainty, and extend the concept of vibration of effects in order to study these three types of uncertainty in a common framework. In a practical application, we examine these types of uncertainty in a Cox model using data from the National Health and Nutrition Examination Survey. In addition, we analyse the behaviour of sampling, model and measurement uncertainty for varying sample sizes in a simulation study. All types of uncertainty are associated with a potentially large variability in effect estimates. Measurement error in the variable of interest attenuates the true effect in most cases, but can occasionally lead to overestimation. When we consider measurement error in both the variable of interest and adjustment variables, the vibration of effects are even less predictable as both systematic under- and over-estimation of the true effect can be observed. The results on simulated data show that measurement and model vibration remain non-negligible even for large sample sizes. Sampling, model and measurement uncertainty can have important consequences for the stability of observational associations. We recommend systematically studying and reporting these types of uncertainty, and comparing them in a common framework.
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