Statistical Methods In Epidemiology--general

该项目为流行病学开发了新的统计方法，具有广泛的应用，并根据正在进行的流行病学项目，特别是与生殖研究有关的项目，开发了所需的方法。今年的工作涉及三个项目。(1)一个项目涉及使用美国出生的双变量出生体重和孕长数据来估计和纠正使用最后一个月经期来估计孕长的测量误差。我们的最终目标是改进每个完整孕周的出生体重和方差标准，并纠正族裔和产妇年龄类别内估计的早产率。我们还希望在这些类别中改进对出生体重、孕长和围产儿死亡风险之间关系的评估。(2)另一个项目涉及以人体样本为基础的昂贵化验生物标记物的综合评估。早先的工作表明，在病例对照环境中，人们可以从病例集合和对照集合中收集样本，并进行基于集合的分析。通过略微修改的Logistic模型，该分析可以估计个体水平的风险参数，并且与基于个体分析的分析相比几乎没有损失。这意味着，如果暴露是基于昂贵的使用人类样本的测试，那么在测试之前将样本汇集在一起可以显著提高效率。在与我的新博士后帕拉米塔·萨哈合作时，我们现在正在将这些方法扩展到怀孕时间数据，其中一个人将样本汇集在由怀孕时间定义的地层中。同样，与单独的水平分析相比，电力几乎不会受到影响，成本大大降低。总的来说，汇集的另一个巨大好处是它保守地使用了不可替代的人类标本。(3)第三个项目开发了一种检验条件Logistic回归应用中所需的同质性假设的方法。例如，一个人可能会进行一项基于兄弟姐妹关系的分析，涉及到遗传和环境因素。如果测量的遗传标记本身不是致病的，而是作为未测量的SNP的连锁替代，那么家庭之间可能存在异质性，这项测试可以检测到这种异质性。

This project develops new statistical methods for epidemiology with broad applications and also methods as needed for ongoing projects in epidemiology, particularly those related to reproductive studies. The work this year involved three projects. (1) One project concerned using the bivariate birth weight and gestational length data for US births to estimate and correct for measurement errors in use of last menstrual period for estimating gestational length. Our goal was ultimately to develop improved standards for birth weights and variances for each completed week of gestation and also to correct the estimated rates of preterm birth within ethnic and maternal age categories. We also hope to improve the assessment of the relationship between birth weight, gestational length and risk of perinatal mortality within those categories. (2) Another project concerns pooled assessment of expensive-to-assay biomarkers based on human samples. Earlier work had shown that in a case-control setting one can pool together specimens from sets of cases and sets of controls and carry out a set-based analysis. With a slightly modified logistic model that analysis can estimate the individual-level risk parameters and loses almost no power compared to analysis based on individual assays. This means that if an exposure is based on an expensive assay that uses human samples, one can markedly improve efficiency by pooling specimens prior to assay. In work with my new post-doc, Paramita Saha, we are now extending these methods to time-to-pregnancy data, where one pools specimens within strata defined by the time to conception. Again the power suffers almost not at all, compared to individual level assays, and the costs are greatly reduced. Another great benefit to pooling in general is in its conservative use of irreplaceable human specimens. (3) A third project developed a method for testing the homogeneity assumption that is required in conditional logistic regression applications. For example, one might carry out a sibship-based analysis involving a genetic and an environmental factor. If the measured genetic marker is not itself causative, but serves as a linked surrogate for an unmeasured SNP, then there could be heterogeneity among families and this test could detect that heterogeneity.