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Design issues and sample size when exposure measurement is inaccurate.

机译:曝光测量不准确时的设计问题和样本量。

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Measurement error often leads to biased estimates and incorrect tests in epidemiological studies. These problems can be corrected by design modifications which allow for refined statistical models, or in some situations by adjusted sample sizes to compensate a power reduction. The design options are mainly an additional replication or internal validation study. Sample size calculations for these designs are more complex, since usually there is no unique design solution to obtain a prespecified power. Thus, additionally to a power requirement, an optimal design should also fulfill the criteria of minimizing overall costs. In this review corresponding strategies and formulae are described and appraised.
机译:在流行病学研究中,测量误差通常会导致估计偏差和测试不正确。这些问题可以通过允许精化统计模型的设计修改来纠正,或者在某些情况下可以通过调整样本大小来补偿功耗的降低。设计选项主要是其他复制或内部验证研究。这些设计的样本量计算更为复杂,因为通常没有唯一的设计解决方案来获得预定功率。因此,除了功率需求之外,最佳设计还应该满足使总成本最小化的标准。在这篇综述中,描述和评估了相应的策略和公式。

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