首页> 美国卫生研究院文献>International Journal of Environmental Research and Public Health >Pooling Bio-Specimens in the Presence of Measurement Error and Non-Linearity in Dose-Response: Simulation Study in the Context of a Birth Cohort Investigating Risk Factors for Autism Spectrum Disorders
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Pooling Bio-Specimens in the Presence of Measurement Error and Non-Linearity in Dose-Response: Simulation Study in the Context of a Birth Cohort Investigating Risk Factors for Autism Spectrum Disorders

机译:在剂量反应中存在测量误差和非线性的情况下合并生物样本:在研究队列中自闭症谱系障碍风险因素的背景下进行的模拟研究

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摘要

We sought to determine the potential effects of pooling on power, false positive rate (FPR), and bias of the estimated associations between hypothetical environmental exposures and dichotomous autism spectrum disorders (ASD) status. Simulated birth cohorts in which ASD outcome was assumed to have been ascertained with uncertainty were created. We investigated the impact on the power of the analysis (using logistic regression) to detect true associations with exposure (X1) and the FPR for a non-causal correlate of exposure (X2, r = 0.7) for a dichotomized ASD measure when the pool size, sample size, degree of measurement error variance in exposure, strength of the true association, and shape of the exposure-response curve varied. We found that there was minimal change (bias) in the measures of association for the main effect (X1). There is some loss of power but there is less chance of detecting a false positive result for pooled compared to individual level models. The number of pools had more effect on the power and FPR than the overall sample size. This study supports the use of pooling to reduce laboratory costs while maintaining statistical efficiency in scenarios similar to the simulated prospective risk-enriched ASD cohort.
机译:我们试图确定合并对权力,假阳性率(FPR)和假设的环境暴露与自闭症谱系障碍(ASD)状态之间的估计关联的偏差的潜在影响。创建了模拟出生队列,其中假定ASD结果已确定且不确定。我们调查了分析(使用逻辑回归)的力量的影响(使用逻辑回归分析),以发现与暴露(X1)和FPR相关的非因果关联(X2,r = 0.7)与二分法ASD量度的真实关联。大小,样本大小,曝光中的测量误差程度变化,真实关联的强度以及曝光-响应曲线的形状都不同。我们发现对主要效果(X1)的关联度量存在最小的变化(偏差)。与单个级别的模型相比,功率有些损失,但检测到合并的假阳性结果的机会较小。样本池的数量对功效和FPR的影响大于总样本量。这项研究支持在模拟模拟的前瞻性风险丰富的ASD队列中使用池化来降低实验室成本,同时保持统计效率。

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