CORE--STATISTICAL

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，提供有效的数据管理、生物统计设计和数据分析，并协助展示科学数据。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；并将进行与项目相关的独立研究和分析。作为具体目标，核心将提供：(1)有效的数据管理；(2)为所有5个项目提供日常统计支持，包括协助研究设计、对数据库设计和内容提供建议、汇总、绘图、分析数据、解释结果，以及在准备出版和/或展示的稿件中进行合作；3)开发新的统计方法，以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包括数据建模、组间比较和参数估计。生物统计核心将结合来自不同项目和本项目核心的数据，进行单变量和多变量统计分析。Core还将关联和共享同一动物的不同项目的数据。特别强调的是研究同一动物的纵向测量（如不同年龄动物的运动功能）和终点值（如多巴胺水平和形态学相关性）之间的相关性。在常规的情况下

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.