Impact of model-form selection on the accuracy of rate estimation.

Impact of model-form selection on the accuracy of rate estimation.
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模型形式选择对速率估计准确性的影响。

DOI:
10.1097/00001648-199601000-00009
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发表时间:
1996
期刊:
Epidemiology (Cambridge, Mass.)
影响因子:
--
通讯作者:
Greenland,S
Greenland,S
中科院分区:
--
文献类型:
--
作者:
Maldonado,G;Greenland,S

文献摘要

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在流行病学中使用基于模型的估计的一个关键假设是,结构模型形式是对疾病发生对暴露和协变量的依赖性的充分数学描述(即,模型形式是正确指定的)。如果违反这个假设,基于模型的点估计器和方差估计器可能会有偏差,标准置信区间可能无效,从这些估计器得出的推论可能是不正确的。在实践中,真正的结构模型形式通常是未知的,研究人员经常使用他们的数据来帮助选择模型形式。我们进行了一项模拟研究,以检验在与环境和职业流行病学相似的队列研究情况下,模型形式选择对率估计准确性的影响。对于我们所研究的情况,使用模型形式选择产生的方差增加通常被相应的偏差减少所抵消,有时会导致准确性的急剧提高。当效应更强,样本量更大,候选模型形式包括真实模型形式或允许模型更接近真实模型形式时,模型形式选择相对于不选择最有利。当效果较弱且样本量较小时,即使候选模型形式包括真实模型形式,效果也最差。
A key assumption underlying the use of model-based estimates in epidemiology is that the structural-model form is an adequate mathematical description of the dependence of disease occurrence on exposures and covariates (that is, the model form is correctly specified). If this assumption is violated, model-based point estimators and variance estimators may he biased, standard confidence intervals may be invalid, and inferences derived from these estimators may he incorrect. In practice, the true structural-model form is usually unknown, and investigators frequently use their data to help select a model form. We conducted a simulation study to examine the impact of model-form selection on the accuracy of rate estimation in cohort-study situations resembling those found in environmental and occupational epidemiology. For the situations we examined, the increase in variance produced by using model-form selection was often more than offset by the corresponding reduction in bias, sometimes resulting in a dramatic increase in accuracy. Model-form selection was observed to be most beneficial relative to no selection when effects were stronger, the sample size was larger, and the candidate model forms included the true model form or allowed the model to more closely approximate the true model form. It was least beneficial when effects were weak and the sample size was small, even if the candidate model forms included the true model form.