Core C: Biometrics

摘要 生物识别核心提供的基础设施可促进有组织、协同和集中的 UW/Fred Hutch CFAR成员艾滋病毒研究统计方法，重点是提供 对初级调查人员的支持和培训。核心提供的服务有助于确保严谨和 CFAR调查人员进行的艾滋病毒研究的重复性。除了标准的统计支持外， CORE在临床研究的设计、实施和分析方面提供先进的统计方法和专业知识 和实验室研究提供给CFAR调查人员。这包括开发新的方法，当标准 通过在CFAR生物医学研究人员和 华盛顿大学和华盛顿大学的大量生物统计学和其他定量科学教师 弗雷德·哈奇正在开发艾滋病毒研究的新方法。此外，CFAR的临床、行为和 使用Core的实验室研究人员提供用于分析的数据集，这推动了新技术的开发 威斯康星大学和弗雷德·哈奇的生物统计学家、生物数学家和生物信息学家的定量方法。因此， 这种联系使CFAR成员和学术量化科学研究人员受益。最后，核心 提供标准统计方法方面的培训，以及涉及专业技术的更高级主题 方法用于复杂的新数据类型，并为下一代量化 研究人员和领导者。具体来说，微生物组分析和病毒动力学研究的方法都不是 建立得很好，因此使用标准方法进行分析的结果远远不是严格和可重复性的。 因此，在这一领域进一步制定方法的必要性至关重要。最后，我们提供的量化支持 为合作的所有成员的创新、有影响力的、多学科和全球性的研究做出贡献 与我们的核心。为了促进和促进这些多学科的互动，生物识别核心：i)提供 统计、数学和信息学在研究设计、表格设计、评估方面的协作和咨询 以及预试、数据分析、解释和报告；协调数据安全和监测委员会； 提供数据管理服务(目标1)；2)作为核心用户与高级用户之间的联络人 来自华盛顿大学生物统计学、统计学、数学系和应用系的定量需求和专家 数学，以及生物统计学和生物数学中的弗雷德·哈奇方案(目标1和2)；3)发展， 根据CFAR的需要调整和/或实施新的或新颖的统计和数学方法 成员及其项目(目标2)；4)赞助和开展旨在传播 向CFAR调查人员提供统计技能，向艾滋病毒研究人员通报生物识别可提供的服务 核心，并将新的量化方法引入华盛顿大学/弗雷德·哈奇CFAR社区(目标3)；和5) 组织活动，促进现有统计人员之间在艾滋病毒研究方面的交流，并对 可招聘的其他生物统计员，以满足日益增长的艾滋病毒研究需求(所有目标)。

Abstract The Biometrics Core provides the infrastructure that facilitates an organized, synergistic, and centralized approach to statistics in HIV research for the UW/Fred Hutch CFAR members, with an emphasis on providing support and training to junior investigators. The services provided by the Core help ensure rigor and reproducibility in HIV research conducted by CFAR investigators. In addition to standard statistical support, the Core provides advanced statistical methods and expertise in the design, conduct and analysis of clinical research and laboratory studies to CFAR investigators. This includes the development of novel methods when standard approaches are not adequate or optimal by providing a crucial link between CFAR biomedical researchers and the large number of biostatistics and other quantitative sciences faculty at the University of Washington and the Fred Hutch who are developing new methods for HIV research. In addition, the CFAR clinical, behavioral, and laboratory researchers using the Core provide datasets for analysis, which motivate the development of new quantitative methods by biostatisticians, biomathematicians and bioinformaticists at UW and Fred Hutch. Hence, this link benefits CFAR members as well as academic quantitative science researchers. Finally, the Core provides training in both standard statistical methods as well as more advanced topics involving specialized method for complex new data types and provides an opportunity for the next generation of quantitative researchers and leaders. Specifically, methods for both microbiome analysis and viral dynamics studies are not well established so that results from analysis using standard methods are far from rigorous and reproducible. Thus the need for further methods development in this area is crucial. Finally, the quantitative support we provide contributes to the innovative, impactful, multidisciplinary and global research of all members who collaborate with our Core. To promote and facilitate these multidisciplinary interactions, the Biometrics Core: i) provides statistical, mathematical and informatics collaboration and consultation on study design, forms design, evaluation and pre-testing, data analysis, interpretation and reporting; coordinates Data Safety and Monitoring Boards; provides data management services (Aim 1); ii) serves as a liaison between the Core user with advanced quantitative needs and experts from the UW Departments of Biostatistics, Statistics, Mathematics, and Applied Mathematics, and the Fred Hutch Program in Biostatistics and Biomathematics (Aims 1 and 2); 3) develops, adapts and/or implements new or novel statistical and mathematical methods as dictated by the needs of CFAR members and their projects (Aim 2); 4) sponsors and conducts training activities designed to disseminate statistical skills to CFAR investigators, inform the HIV researchers about services available from the Biometrics Core, and introduce novel quantitative approaches to the UW/ Fred Hutch CFAR community (Aim 3); and 5) organizes activities that promote communication among existing statisticians in HIV research and interest from other biostatisticians that can be recruited to meet the growing demand of HIV research (All Aims).