Data Management and Statistical Analysis Core (Core C)

数据管理和统计分析核心（核心C）

• 批准号: 10405116
• 负责人: Thomas Glenn Travison
• 金额: $ 42.85万
• 依托单位: HEBREW REHABILITATION CENTER FOR AGED
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-15 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10405116
• 关键词: Address; Aging; Algorithms; Alzheimer' s Disease; Area; Biological; Biological Assay; Biological Markers; Biometry; Brain; Cohort Analysis; Cohort Studies; Collaborations; Complex; Data; Data Analyses; Data Analytics; Data Science; Data Security; Data Storage and Retrieval; Databases; Delirium; Dementia; Development; Enrollment; Ensure; Environment; Experimental Designs; Faculty; Funding; Goals; Human Resources; Image; Image Analysis; Incidence; Information Management; Information Resources; Infrastructure; Interview; Leadership; Machine Learning; Maintenance; Manuscripts; Matched Case-Control Study; Medical Records; Metadata; Methodology; Methods; Modeling; Modernization; Multivariate Analysis; Observational Study; Operations Research; Operative Surgical Procedures; Outcome; Participant; Physical Function; Play; Prevention strategy; Procedures; Production; Productivity; Protocols documentation; Publications; Quality Control; Reporting; Reproducibility; Research; Research Design; Research Personnel; Resources; Risk; Role; Safety; Sample Size; Sampling; Schedule; Science; Scientist; Seasons; Secure; Source; Specimen; Standardization; Statistical Data Interpretation; Structure; Supervision; System; Testing; Time; Visit; Work; case control; clinically significant; cognitive development; cognitive function; cognitive reserve; cohort; computing resources; cost effective; data cleaning; data infrastructure; data management; data quality; design; experience; innovation; method development; multiple chronic conditions; novel; operation; participant enrollment; peer support; preservation; programs; safety study; success; therapy development; tool; web-enabled

ABSTRACT The study of delirium, and its relationship to dementia and Alzheimer's Disease, presents distinct quantitative challenges, including elevated risk of participant attrition and confounding of associations via the influences of surgery and multimorbidity. The Data Management and Statistical Analysis (DMSA) Core (Core C) has been developed to address these challenges. The overall goal of the DMSA Core is to provide data management and biostatistical resources and expertise promoting best statistical and scientific practices within this Program Project. DMSA activities are directed toward the three mutually reinforcing Specific Aims: (1) to develop infrastructure for data capture and metadata management; (2) to develop and maintain secure data management infrastructure; and (3) to provide comprehensive statistical and data management support, including novel methods development, to each of the five projects. The DMSA's leadership has substantial expertise in observational studies, experimental design, longitudinal multivariate analysis, biomarker analysis, scale development, machine learning, and missing data, and is seasoned in the leadership of data science teams. Its skilled staff are substantially experienced in the acquisition and management of high quality data, as illustrated by the extremely successful data capture and completeness initiatives developed in the initial funding cycle. Core faculty maintain active and highly productive collaborative relationships with the SAGES investigators. Additionally, the DMSA provides key venues for collaboration, supervision and peer support of its faculty and personnel; maintenance of efficiency and productivity; and surety of quality control around data and analytic issues. The DMSA has embedded continuous innovation in its operations; examples of this innovation include novel scale development for cognitive and physical function; extended matching algorithms in case/control design, and the development of novel and integrated web-enabled data management and analysis tools, which enhance the reproducibility of scientific findings. The DMSA will provide the venue for efficient and cost effective information management and data analysis of the five projects proposed here; the feasibility of this ambitious effort is demonstrated by our success in the initial funding cycle and our well- developed research operations model. This Program Project has tremendous potential to advance the science of delirium, leading ultimately to the development of interventions targeting its incidence and sequelae. Ultimately, this Program Project holds tremendous potential to advance our understanding of delirium, and to develop more effective strategies for prevention and treatment of delirium and associated conditions and complications. The DMSA will play a critical role in its success.

摘要 谵妄的研究，以及它与痴呆和阿尔茨海默病的关系，提出了不同的定量分析。 挑战，包括参与者流失的风险增加和通过以下因素的影响混淆关联 手术和多发性硬化症数据管理和统计分析（DMSA）核心（核心C）已经 为应对这些挑战而开发。DMSA核心的总体目标是提供数据管理 生物统计资源和专业知识，促进本计划内的最佳统计和科学实践 项目DMSA的活动旨在实现三个相辅相成的具体目标：（1）发展 数据采集和元数据管理的基础设施;（2）开发和维护安全数据 管理基础设施;以及（3）提供全面的统计和数据管理支持， 包括开发新方法。DMSA的领导层 在观察性研究、实验设计、纵向多变量分析、生物标志物分析、 规模开发，机器学习和缺失数据，并在数据科学的领导方面经验丰富 团队其熟练的工作人员在获取和管理高质量数据方面经验丰富， 在最初的数据收集和完整性倡议中， 融资周期。核心教师与SAGES保持积极和高效的合作关系 investigators.此外，DMSA还提供了合作、监督和同行支持的关键场所， 教师和人员;保持效率和生产力;以及围绕数据和 分析问题。DMSA在其业务中不断创新;这种创新的例子 包括认知和身体功能新量表开发; 病例/对照设计，以及开发新颖的集成网络数据管理和 分析工具，提高科学发现的可重复性。DMSA将提供场地， 对这里提出的五个项目进行有效和具有成本效益的信息管理和数据分析; 这一雄心勃勃的努力的可行性体现在我们在最初的筹资周期中取得的成功以及我们的良好- 开发研究业务模型。该计划项目具有推动科学发展的巨大潜力 谵妄，最终导致针对其发病率和后遗症的干预措施的发展。 最终，这个计划项目拥有巨大的潜力，以促进我们对谵妄的理解， 制定更有效的预防和治疗谵妄及相关疾病的策略， 并发症DMSA将在其成功中发挥关键作用。