MEASUREMENT ERROR IN OCCUPATIONAL COHORT STUDIES

职业队列研究中的测量误差

• 批准号: 2769936
• 负责人: DONNA L SPIEGELMAN
• 金额: $ 20.4万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-09-01 至 2000-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2769936
• 关键词: human data; neoplasm /cancer epidemiology; occupational health /safety; statistics /biometry

DESCRIPTION (Adapted from the Investigators Abstract): Large errors in measurement of the exposure variable are frequently encountered in occupational cancer studies. In general, these errors lead to bias of effect estimates towards the null and underestimation of the width of confidence intervals. Although statisticians have proposed numerous methods for treating this problem, most of these methods are not appropriate for occupational cancer studies, because; a) they make unrealistic assumption about the process generating error in the measurement of the exposure variable, b) they are not applicable to the survival data methods required for the analysis of cohort studies, and c) they do not consider interval estimation, but only address point estimation. In addition, the few developments which do not have the above limitations, have not made their way into standard practice because; a) they have not considered the particular issues which arise when a cumulative exposure variable is of primary interest, and b) the proper use of these methods requires a detailed understanding of the statistical literature and few realistic examples exist of practical applications. The work proposed in this grant, will develop new methods and adapt existing ones for use in occupational cancer studies with cumulative exposure as the variable of interest with none of the above limitations. Fully parametric likelihood methods, as originally proposed by Prentice in (1982), and new, semi-parametric methods, as elaborated by Robins et al. (1994, 1995), will both be considered. These methods will be applied to important data sets taken from occupational epidemiology: Samet et al. s 1991 study of the effects of occupational exposure to radon gas in relation to lung cancer mortality among New Mexico uranium miners, and Savitz et al. s 1995 study of the effects of occupational exposure to magnetic fields in relation to mortality from leukemia and brain cancer among workers in five electric power plants. Both of these studies have detailed validation data from which parametric and non-parametric measurement error models will be constructed, and used to obtain point and interval estimates of the exposure effect which are not contaminated by measurement error. In addition to contributing to the advancement of statistical methods available in this setting, the investigators will advance scientific understanding of the extent of the exposure-disease relationships investigated in these two studies, and provide a more realistic quantification of the uncertainty around this understanding.

描述（改编自研究者摘要）： 暴露变量的测量经常遇到， 职业癌症研究。 一般来说，这些误差会导致 效应估计趋于零和低估的宽度 置信区间 尽管统计学家提出了许多方法 为了治疗这个问题，这些方法中的大多数都不适合于 职业癌症研究，因为; a）他们做出不切实际的假设 关于曝光测量中产生误差的过程 变量，B）它们不适用于所需的生存数据方法 对于队列研究的分析，以及c）他们不考虑间隔 估计，但只有地址点估计。 此外，少数 没有上述限制的发展，还没有使他们的 因为：（1）他们没有考虑到 当累积暴露变量为 主要利益，和B）这些方法的正确使用需要详细的 对统计文献的理解和存在的现实例子很少 的实际应用。 这项工作提出的补助金，将开发新的方法和适应现有的 用于职业性癌症研究，累积暴露量为 感兴趣的变量，没有上述限制。 全参数 似然方法，如最初由普伦蒂斯（1982）提出的，以及新的， Robins等人（1994，1995）阐述的半参数方法将 两者都要考虑。 这些方法将应用于重要的数据集 来自职业流行病学：Samet et al. 1991年的研究， 职业性氡气暴露对肺癌的影响 新墨西哥州铀矿工人的死亡率，以及Savitz等人1995年的研究， 职业暴露于磁场的影响与 五家电力公司工人白血病和脑癌死亡率 电站 这两项研究都有详细的验证数据， 参数和非参数测量误差模型将 构建，并用于获得暴露的点和区间估计值 不受测量误差污染的影响。 除了 为促进统计方法的进步， 在这种情况下，研究人员将促进对 在这两个研究中， 研究，并提供了一个更现实的量化的不确定性 围绕这一理解。