Core B: Biostatistics Core

生物统计学和信息学核心的总体目标是提供统计，信息和 为计划项目提供计算支持，以进行高级和大规模的统计分析， 确定和描述风险因素在预测和筛查肺癌中的准确性。核心教师 和其他研究人员从事与任务有关的研究动机的问题和方法 这些项目带来的挑战。该核心的成员具有广泛的专业知识和兴趣 将他们的活动与项目结合起来。通过形成一个生物统计学和信息学核心， 项目，我们预计计划研究的支持比可能的更强大和更深刻的水平。 如果生物统计学家被嵌套在每个项目中，核心允许我们汇集资源（例如， 统计遗传学、统计学和机器学习方面的专业知识），并利用更广泛的 多个参与机构（如哈佛TH的生物统计学系）的可用资源 陈公共卫生学院和达特茅斯大学生物医学数据科学系。的 核心成员在开发和应用新的统计和 机器学习方法用于研究遗传易感性对癌症的风险预测和风险评估。 他们多年来一直在研究肺癌的发展。核心提供了一个 协调和规划跨计划项目的研究环境，并开发和应用 最先进的统计和机器学习方法，以满足本计划项目的需求。到 支持计划项目，我们提出以下目标：（1）确保所有项目都基于 合理生物统计学和信息学原则，并使用最先进的设计和分析方法;（2） 提供与统计遗传学、生物信息学和机器设计和分析相关的专家建议 （3）开展与任务相关的统计方法研究， 开发新的统计方法，以满足计划项目的定量需求;（4） 通过专题文章、案例研究传播拟议的统计方法发展， （5）通过与国际合作，为研究人员和学生提供教育和培训， 指导委员会和方案调查员。核心成员将协调其工作活动， 通过每月电话会议和定期电子邮件交流，有效支持计划项目。

The overarching goal of the Biostatistics and Informatics Core is to provide statistical, informatic and computational support for the Program Project to conduct advanced and large-scale statistical analyses to identify and characterize the accuracy of risk factors in predicting and screening lung cancer. The Core faculty and other researchers engage in mission-related research motivated by questions and methodological challenges that arise from these projects. The members of this Core have extensive expertise and interests that unite their activities among Projects. By forming a Biostatistics and Informatics Core that functions across projects, we anticipate a more robust and profound level of support for Program research than could be achieved if biostatisticians were nested within each project. The Core allows us to pool resources (e.g. expertise in statistical genetics, statistical and machine learning) across projects and also draw on the broader resources available in multiple participating institutes, such as the Department of Biostatistics at Harvard TH Chan School of Public Health and the Department of Biomedical Data Science at Dartmouth University. The members of the Core have extensive experience in the development and application of new statistical and machine learning methods for the study of genetic susceptibility to cancer risk prediction, and risk assessment. They have worked together over years on studies relating to lung cancer development. The Core provides an environment for coordinating and planning of research across the program projects and to develop and apply state-of-the-art statistical and machine learning methods that meet the needs of this Program Project. To support the Program projects, we propose the following aims: (1) To ensure that all Projects are grounded in sound biostatistical and informatic principles and use state-of-the-art methods for design and analysis; (2) To provide expert advice related to design and analysis in statistical genetics, bioinformatics, and machine learning and statistical learning for all Projects; (3) To conduct mission-related statistical methods research by developing novel statistical methods to address the quantitative needs of the Program Project; (4) To disseminate the proposed statistical methodological developments via expository articles, case studies, and web-shared software; (5) To provide education and training for researchers and students by working with the Steering Committee and the Program investigators. The Core members will coordinate their work activities and effectively support the Program Project by having monthly conference calls and regular email exchanges.