Core C: Data Management and Statistical Core

项目摘要摘要-数据管理和统计核心 数据管理和统计核心（DMSC）支持UC Davis（UCD）阿尔茨海默氏症的使命 疾病中心（ADC）通过维护一个安全的中央数据库;提供复杂的统计分析， 纵向数据;并与其他核心和研究人员在研究和指导方面密切合作。 DMSC团队因其知识领导力而被国际公认，有助于科学进步， 合作、教育和培训。 DMSC在当前赠款周期（2011年7月至2016年6月）的主要创新包括： 开发的最先进的数据库管理系统（Lava）的功能， 通过跨ADC协作进行维护和扩展。2)可重复研究原则的应用 以及动态生成集成了数据库、数据分析以及书写和图形的报告的方法 结果的呈现。3)实施相关结果的平行过程纵向模型， 预测器4)高维成像和生物标志物数据分析方法的发展。5)创建 潜在变量模型，用于定义、测量和捕获复杂但重要的结构中的动态变化 比如认知和功能储备。6)认知成套测验的统计协调，以实现合并 来自不同研究的数据集。7)地方，国家和国际合作科学的领导 努力和培养下一代研究人员。 在下一个赠款周期，DMSC将帮助我们进一步了解影响 从正常认知到轻度认知的认知轨迹的异质性 四个方面的障碍和痴呆症。1)我们将监督UCD ADC及其 核心，提供安全的基于Web的中央资源。2)我们将进行统计分析， ADC在年龄相关疾病的发病机制、诊断、治疗和预防方面的跨学科研究 退化性疾病3)我们将根据需要开发新的统计方法，以支持对 ADC的复杂数据。4)我们将与研究教育部门密切合作，指导和培训 下一代AD研究人员在研究设计、分析和结果展示方面的贡献。

PROJECT SUMMARY ABSTRACT – Data Management and Statistics Core The Data Management and Statistics Core (DMSC) supports the mission of the UC Davis (UCD) Alzheimer's Disease Center (ADC) by maintaining a secure, central database; providing statistical analysis of the complex longitudinal data; and collaborating closely with the other Cores and investigators on research and mentoring. The DMSC team is internationally recognized for intellectual leadership that contributes to scientific advances, collaborations, and education and training. Key DMSC innovations in the current grant cycle (07/11–06/16) have included: 1) Refinement and expansion of the functionality of the state-of-the art database management system (Lava) that was developed and is maintained and extended through a cross-ADC collaboration. 2) Application of reproducible research principles and methods to dynamically generate reports that integrate database, data analysis, and written and graphic presentation of results. 3) Implementation of parallel process longitudinal models for correlated outcomes and predictors. 4) Development of analytic methods for high dimension imaging and biomarker data. 5) Creation of latent variable models to define, measure, and capture dynamic change in complex but important constructs like cognitive and functional reserve. 6) Statistical harmonization of cognitive test batteries to enable merging of datasets from different studies. 7) Local, national, and international leadership in collaborative science efforts and in training the next generation of researchers. In the next grant cycle, the DMSC will help to advance our understanding of factors that influence heterogeneity of cognitive trajectories across the spectrum from normal cognition through mild cognitive impairment and into dementia in four areas. 1) We will oversee data management for the UCD ADC and its Cores, providing a secure web-based central resource. 2) We will carry out statistical analyses for interdisciplinary ADC research on pathogenesis, diagnosis, treatment, and prevention of age-related degenerative disease. 3) We will develop new statistical methodology as needed to support the analysis of ADC's complex data. 4) We will work closely with the Research Education Component to mentor and train the next generation of AD researchers in study design, analysis, and presentation of results.