对癌症等随机辐射健康影响的流行病学研究旨在估计作为辐射剂量函数的不利影响的风险，这在很大程度上取决于对所研究的暴露组所接受的辐射剂量的估计。这些估计是基于总是具有不确定性的剂量测定，这种不确定性通常可能相当大。不采用统计方法来校正剂量测定不确定性的研究可能会产生有偏差的风险估计以及这些估计的不正确的置信区间。本文回顾了校正剂量不确定性的辐射风险回归的常用统计方法，重点介绍了一些较新的方法。我们首先描述可能发生的剂量不确定性的类型，包括部分或全部队列共享不确定值的类型，然后演示这些不确定性来源是如何在辐射剂量测定中出现的。我们简要描述了不同类型的剂量测定不确定性对风险估计的影响，然后描述了每种不确定性调整方法。每种方法都有优点和缺点，并且某些方法的适用性有限。我们描述了每种方法可以应用的不确定性类型及其优缺点。最后，我们提供总结建议并简要讨论进一步研究的建议。

Epidemiological studies of stochastic radiation health effects such as cancer, meant to estimate risks of the adverse effects as a function of radiation dose, depend largely on estimates of the radiation doses received by the exposed group under study. Those estimates are based on dosimetry that always has uncertainty, which often can be quite substantial. Studies that do not incorporate statistical methods to correct for dosimetric uncertainty may produce biased estimates of risk and incorrect confidence bounds on those estimates. This paper reviews commonly used statistical methods to correct radiation risk regressions for dosimetric uncertainty, with emphasis on some newer methods. We begin by describing the types of dose uncertainty that may occur, including those in which an uncertain value is shared by part or all of a cohort, and then demonstrate how these sources of uncertainty arise in radiation dosimetry. We briefly describe the effects of different types of dosimetric uncertainty on risk estimates, followed by a description of each method of adjusting for the uncertainty.Each of the method has strengths and weaknesses, and some methods have limited applicability. We describe the types of uncertainty to which each method can be applied and its pros and cons. Finally, we provide summary recommendations and touch briefly on suggestions for further research.