Statistical Methods In Epidemiology--general

本项目发展具有广泛应用的流行病学新统计方法，并发展流行病学正在进行的项目所需的方法，特别是与生殖研究有关的项目。今年的工作包括三个主要项目。(1)我们正在开发一种经验贝叶斯方法，用于总结生殖史数据，以预测相同或遗传相关结果的后续风险；(2)我们开发了一种方法来分析怀孕研究的时间，这种方法既有效，又避免了由于违反通常的恒常性假设而产生的偏差；(3)我们开发了一种基于标本池的方法，用于研究病例队列研究中昂贵的测量暴露，这种方法可以保存存档的生物标本，并充分利用分析预算，但统计能力的损失（甚至提高）最小。

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 main projects. (1) We are developing an empirical Bayes approach for summarizing reproductive history data for prediction of subsequent risk of the same or of genetically-related outcomes; (2) We developed methods to analyze time to pregnancy studies in a way that is both powerful and avoids the biases that arise due to violations of the usual constancy assumptions; and (3) We have developed an approach based on specimen pooling for studying expensive-to-measure exposures in case-cohort studies, an approach that conserves archived biospecimens and makes excellent use of the assay budget, but with minimal loss of (or even improvement in) statistical power.