CORE--STATISTICAL

核心--统计

• 批准号: 6957279
• 负责人: Peng Huang
• 金额: $ 3.96万
• 依托单位: MEDICAL UNIVERSITY OF SOUTH CAROLINA
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-15 至 2010-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6957279
• 关键词: aging; biomedical facility; data management; dopamine; experimental designs; longitudinal animal study; mathematical model; method development; statistics /biometry

The overall objective of the Biostatistical Core is to work closely with all 5 projects and the animal core to provide efficient data management, biostatistical design and data analyses, as well as aid in presentations of scientific data. To accomplish this goal, the Biostatistical Core will provide rigorous methodological and biostatistical support to all projects; and will conduct independent research and analyses related to the program projects. As specific aims the Core will provide: (1) efficient data management; (2) routine statistical support for all 5 projects, including assistance with the design of studies, advice on database design and content, summarizing, plotting, analyzing data, interpretation of results, and collaboration in manuscript preparation for publication and/or presentation; and 3) development of new statistical methodology to address and support the statistical design and analyses for all projects. Statistical analysis for the Projects in this grant often involves data modeling, comparison among groups, and parameter estimations. The Biostatistical Core will combine data from different projects and cores of this program project to perform both univariate and multivariate statistical analyses. The Core will also correlate and share data for different projects on the same animals. Special emphasis will be placed on investigating correlations among longitudinal measures (such as motor function in animals of different ages) and endpoint values (such as dopamine levels and morphological correlates) from the same animal. For situations where the conventional parametric or semi-parametric theory is appropriate, the Core investigators will apply ANOVA or the linear mixed models to fit the data with univariate outcome. For multiple dependent outcomes, the Core investigators will use parametric global statistical tests, obtain optimal estimate of parameters of interest and the corresponding confidence intervals. When the parametric assumptions are in doubt, the Core investigators will apply nonparametric global statistical tests for both univarite and multivariate outcomes and repeated measures. For situations when no suitable statistical models in the literature can be applied, the Biostatistical Core will develop suitable statistical models and necessary statistical inference theory for all projects.

生物统计核心的总体目标是与所有 5 个项目和动物核心密切合作，提供高效的数据管理、生物统计设计和数据分析，并帮助展示科学数据。为了实现这一目标，生物统计核心将为所有项目提供严格的方法和生物统计支持；并将开展与计划项目相关的独立研究和分析。作为具体目标，核心将提供：（1）高效的数据管理； (2) 对所有 5 个项目的常规统计支持，包括协助研究设计、对数据库设计和内容提供建议、总结、绘图、分析数据、结果解释以及在准备出版和/或演示的手稿方面进行协作； 3) 开发新的统计方法来解决和支持所有项目的统计设计和分析。本资助项目的统计分析通常涉及数据建模、组间比较和参数估计。生物统计核心将结合来自该计划项目的不同项目和核心的数据，以执行单变量和多元统计分析。核心还将关联和共享同一动物的不同项目的数据。将特别强调调查同一动物的纵向测量（例如不同年龄动物的运动功能）和终点值（例如多巴胺水平和形态相关性）之间的相关性。对于传统的情况 参数或半参数理论是合适的，核心研究人员将应用方差分析或线性混合模型来拟合具有单变量结果的数据。对于多个相关结果，核心研究人员将使用参数全局统计检验，获得感兴趣参数的最佳估计和相应的置信区间。当参数假设有疑问时，核心研究人员将对单变量和多变量结果以及重复测量应用非参数全局统计检验。对于文献中没有合适的统计模型可以应用的情况，生物统计核心将开发 适用于所有项目的统计模型和必要的统计推断理论。