Design-Statistical Core

项目摘要 设计/统计核心（DSC）将成为国家老龄化研究所（NIA）不可或缺的组成部分 阿尔茨海默病（AD）/AD相关痴呆（AD/ADRD）医疗保健系统（HCS）合作实验室。它将 与其他协作工作组核心和团队合作，开发知识并提供指导， 开展严格的嵌入式实用临床试验（ePCT），以改善患者的护理和健康结果 痴呆症患者（PWD）及其照顾者（CG）。它将作为一种国家资源， 生物统计专业知识，以合作支持的试点研究，职业发展奖（CDA），和 其他NIA资助的研究人员进行此类试验。DSC将有助于设计的各个方面， 进行和分析这些项目，并将开发新的统计方法的设计和 在HCS内对残疾人进行ePCT分析。为了推进这一领域，并创造一个持久的知识 设计/统计核心将在以下领域提供指导：1）ePCT的稳健设计，2） ePCT的统计分析，3）处理缺失数据、污染和其他异常的方法，4） 处理AD/ADRD特定相关陷阱的策略，5）可复制性和再现性，6） 7）考虑到代表性不足的少数群体和重要的 分组，包括将性别作为一个生物变量处理，8）编制文件和分发软件 和分析代码，9）出版和传播，以及10）初级定量 科学家和临床研究者。设计/统计核心的另一个主要功能是提供 为AD/ADRD合作实验室提供咨询和服务，特别是为试点研究提供咨询和服务， 职业生涯，CDA收件人，和其他NIA资助的研究人员。DSC的工作将由 领导博士石楠Allore博士，医学教授在耶鲁大学医学院，教授， 耶鲁大学公共卫生学院生物统计学和耶鲁大学阿尔茨海默病研究主任 中心的数据管理和统计核心。她是一位经验丰富的审判者和领域的创始人， 老年生物统计学。Allore博士将加入一个由六名杰出执行委员会成员组成的团队 成员们带来了AD/ARDR研究、老龄化研究、集群随机试验和 在老年人中开展ePCT。DSC的目标是：目标1：提供生物统计协助， 指导合作实验室试点研究，CDA接受者和NIA资助的研究者计划或开展 PWD和CG中的ePCT;目标2：开发新的生物统计方法，并创建和传播 与在PWD和HCS中设计和实施ePCT相关的指导文件和产品，目标3： 与技术/数据核心合作，建立和管理对行政数据的访问和共享（例如， 电子健康记录、索赔数据）供AD/ADRD合作实验室研究者使用（例如，试点项目 领导人），在提供可重复的分析和复制研究的指导。

PROJECT SUMMARY The Design/Statistics Core (DSC) will be an indispensable component of the National Institute of Aging (NIA) Alzheimer's disease (AD)/AD-related dementia (AD/ADRD) Healthcare Systems (HCS) Collaboratory. It will work with other Collaboratory Work Group Cores and Teams to develop knowledge and provide guidance to conduct rigorous embedded pragmatic clinical trials (ePCTs) to improve the care and health outcomes of persons with dementia (PWD) and their caregivers (CGs). It will serve as a national resource providing biostatistical expertise to Collaboratory-supported pilot studies, career development awardees (CDAs), and other NIA-funded investigators conducting such trials. The DSC will contribute to all aspects of the design, conduct, and analysis of these projects, and will develop novel statistical methodology for the design and analysis of ePCTs conducted among PWD within HCS. To advance this field and create a durable knowledge repository, the Design/Statistics Core will provide guidance in areas such as: 1) robust design of ePCTs, 2) statistical analysis of ePCTs, 3) methods for handling missing data, contamination, and other irregularities, 4) strategies for dealing with pitfalls of specific relevance to AD/ADRD, 5) replicability and reproducibility, 6) multiplicity and multiple comparisons, 7) consideration of under-represented minorities and important subgroups, including treatment of sex as a biological variable, 8) documentation and dissemination of software and analytic code, 9) publication and dissemination, and 10) training and mentoring of junior quantitative scientists and clinical investigators. The Design/Statistics Core’s other main function will be to provide consultation and services to the AD/ADRD Collaboratory as a whole and particularly to the pilot studies, career, CDA recipients, and other NIA-funded investigators. The work of the DSC will be enabled by the leadership of Dr. Heather Allore PhD, Professor of Medicine in the Yale School of Medicine, and Professor of Biostatistics at the Yale School of Public Health, and Director of the Yale Alzheimer's Disease Research Center's Data Management and Statistics Core. She is an experienced trialist and founder of the field of Gerontological Biostatistics. Dr. Allore will be joined by a team of six exceptional Executive Committee members who bring varied expertise in AD/ARDR research, aging research, cluster randomized trials, and the conduct of ePCTs in older persons. The DSC’s Aims are: Aim 1: To provide biostatistical assistance and guidance to Collaboratory pilot studies, CDAs recipients and NIA-funded investigators planning or conducting ePCTs in PWD and CG; Aim 2: To develop novel biostatistical approaches, and create and disseminate guidance documents and products relevant to the design and conduct of ePCTs in PWD with HCS, Aim 3: To work with the Technical/Data Core, to establish and manage access to and sharing of administrative data (e.g., electronic health records, claims data) for use by AD/ADRD Collaboratory investigators (e.g. pilot project leaders), in providing guidance on reproducible analyses and replication studies.