Core C: Statistics Core

核心 C：统计核心

• 批准号: 10684079
• 负责人: Daniel Joseph Tancredi
• 金额: $ 15.23万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10684079
• 关键词: Acute; Address; Adherence; Analytical Chemistry; Behavioral; Cholinesterase Inhibitors; Chronic; Clinical Research; Code; Collaborations; Complex; Data; Data Analyses; Data Collection; Data Pooling; Data Storage and Retrieval; Database Management Systems; Development; Drug Kinetics; Education; Ensure; Evaluation; Experimental Designs; FAIR principles; Faculty; Human Resources; Image; Interdisciplinary Study; Intoxication; Methodology; Methods; Mission; Neurologic; Organophosphates; Pharmaceutical Chemistry; Pilot Projects; Procedures; Reporting; Reproducibility; Reproduction; Research; Research Design; Research Personnel; Research Project Grants; Research Support; Sample Size; Science; Scientist; Severities; Statistical Data Interpretation; Statistical Methods; Status Epilepticus; Targeted Research; Therapeutic; Therapeutic Effect; Training; Training and Education; Validation; cholinergic; data sharing; data standards; design; education research; experience; experimental study; graduate student; imaging study; improved; meetings; neuroimaging; neurotoxic; novel; novel therapeutic intervention; pre-clinical research; programs; repository; senior faculty; sound; standard of care; statistics; systematic review

Project Summary – Statistics Core – Core C Promoting scientific rigor and reproducibility has become an urgent priority in preclinical research in recent years. Important features of these concepts include sound study design, statistical analysis, and the validation and sharing of study data and statistical programming code to facilitate replication and reproduction, and to maximize impact by pooling data in repositories that aim to facilitate discovery. The Statistics Core’s primary objectives are to (i) provide targeted research support in study design and data analysis; (ii) establish data standards and procedures for data storage to promote adherence to FAIR (Findability, Accessibility, Interoperability, Reusability) Principles, facilitate efficient research collaboration, data sharing and reproducibility of research results; and (iii) advance the educational mission of the Center (in close partnership with the Research Education Core) by providing training to investigators, research staff and graduate students on study design and statistical methods tailored to CounterACT scientific objectives. Using a proven approach that has served us well for the previous UC Davis CounterACT Center, the Core will provide statistical research support in rigorous experimental design, sample size estimation, and effective data analysis methods to minimize bias and to ensure robust results. The Statistics Core consists of a trio of highly experienced CounterACT statisticians, including two full professors. All three have considerable (10+ years) experience in collaborative multidisciplinary research. To distribute efforts across Core C’s faculty statisticians and analytical staff, and to encourage collaboration across Projects and Cores, each experiment is assigned a primary faculty statistician and analyst to support the design, data collection, data analysis, and reporting of results. Brief weekly meetings of Core C personnel provide an efficient forum to discuss statistical and database management challenges and to share ideas and methods for addressing them. By providing targeted statistical expertise, analytical and data storage support, and training, the Statistics Core will promote the scientific rigor, reproducibility, and ultimate impact of research findings by the UC Davis CounterACT Center of Excellence.

项目摘要 - 统计核心 - 核心C 近年来，促进科学严格和可重复性已成为临床前研究的紧迫性。 这些概念的重要特征包括声音研究设计，统计分析和验证和 共享研究数据和统计编程代码，以促进复制和复制，并最大化 通过在旨在促进发现的存储库中汇总数据来影响。统计核心的主要目标是 （i）在研究设计和数据分析中提供了有针对性的研究支持； （ii）建立数据标准和 数据存储的程序以促进依从性（可发现性，可访问性，互操作性， 可重复使用）原理，促进研究合作，数据共享和研究的可重复性 结果; （iii）推进中心的教育任务（与研究教育密切合作 核心）通过向研究人员，研究人员和研究生提供研究设计和统计学的培训 定制以抵消科学目标的方法。使用一种经过验证的方法，为我们提供了很好的服务 前加州大学戴维斯（UC Davis）抵抗中心，核心将在严格的情况下提供统计研究支持 实验设计，样本量估计和有效的数据分析方法，以最大程度地减少偏差并确保 强大的结果。统计核心由三人组成，包括经验丰富的反战统计学家，包括 两位完整的教授。这三个人都考虑了（10多年）的合作多学科研究经验。 在Core C的教师统计学家和分析人员中分发努力，并鼓励合作 在整个项目和核心中，每个实验都被分配了一名主要教师统计学家和分析师，以支持 设计，数据收集，数据分析和结果报告。核心C人员的简短每周会议提供 一个有效的论坛，讨论统计和数据库管理挑战并分享想法和方法 解决他们。通过提供有针对性的统计专业知识，分析和数据存储支持以及培训， 统计核心将促进研究发现对研究结果的科学严谨性，可重复性和最终影响 加州大学戴维斯分校抵消卓越中心。