Core E: Comparative Data Analytics Core

比较数据分析核心(CDAC)不仅将提供高级定制统计支持 对于在UAB的不同模式生物中研究衰老和能量学的基础科学研究人员来说， 开发专门用于这类研究的新方法的场所，以及培训其他人的空白 超越UAB在这类研究中的地位，并为将这种方法传播到老龄化研究提供了一个平台 整个社区。核心领导层由拥有20年研究历史的统计科学家组成 衰老、能量和身体成分的界面。他们不仅带来了他们的统计专业知识，而且还带来了他们的 对衰老和能量学交界处的比较研究科学的经验和热情。 在老龄化研究方面，显然需要专门的统计专业知识、培训和支持。统计 对老龄化研究数据的分析带来了许多挑战。老龄化研究涉及纵向分析和 对随时间进行的多个观测的相关性进行建模，并适应丢失的数据 这通常发生在纵向研究中。与事件发生时间(例如，生存)结果、左侧、右侧和 间隔审查进一步增加了复杂性。比较生物学中的统计方法面临着以下挑战 由于模型残留物之间的系统发育依赖，使推理复杂化。 非统计学家的研究人员受益于统计科学家的支持和参与，他们对 参与主题的人，谁能根据手头的情况量身定做方法，谁与生物学家一起工作 从一开始作为研究团队的一员，谁就可以和生物学家讨论方法 并解释统计程序以及谁可以为特定需求开发新的统计方法。 为此，UAB CDAC提供了以下具体目标： 1.为UAB调查人员研究衰老的比较能量学提供统计支持，包括 传统的、专门的和定制的方法。 2.为研究衰老的比较能量学的非UAB调查人员提供统计支持， 包括传统的、专门的和定制的方法。 3.对二手数据进行高水平的统计调查，以回答有关 衰老的比较能量学。 4.发展和评估衰老比较能量学领域所需的统计方法。 5.提供一系列关于统计方法的有组织的教育课程，供比较 衰老的能量学，它允许将专业知识传播给更广泛的科学 社区。 对这一核心的投资将通过催化更多的信息和严格的研究来实现红利 UAB NSC内的老龄化以及广大老龄研究人员的社区。

The Comparative Data Analytics Core (CDAC) will provide not only high-level customized statistical support for basic science investigators studying aging and energetics in diverse model organisms at UAB, but also a venue for development of de novo methods specially for such research, a nidus for training others at and beyond UAB in such research, and a platform for the dissemination of such methods to the aging research community at large. The core leadership comprises statistical scientists with a 20-year history of studying the interface of aging, energetics and body composition. They bring not only their statistical expertise, but their experience with and zeal for the science of comparative studies at the interface of aging and energetics. The need for specialized statistical expertise, training, and support in aging research is clear. Statistical analyses of aging research data provide many challenges. Aging research involves longitudinal analyses and modeling the dependency of multiple observations taken over time, and accommodating the missing data which commonly occurs with longitudinal studies. With time-to-event (e.g., survival) outcomes, left, right, and interval censoring add further complexities. Statistical approaches in comparative biology face challenges such as phylogenetic dependence among model residuals, complicating inference. Non-statistician researchers benefit from the support and involvement of statistical scientists who are deeply involved in the subject matter, who can tailor methods to the situation at hand, who work with the biologists from the beginning as an engaged part of the research team, who can discuss the methods with the biologists and explain the statistical procedures and who can develop new statistical methods for specific needs. To that end, the UAB CDAC offers the following specific aims: 1. To provide statistical support for UAB investigators studying the comparative energetics of aging, including traditional, specialized, and bespoke methods. 2. To provide statistical support for non-UAB investigators studying the comparative energetics of aging, including traditional, specialized, and bespoke methods. 3. To conduct high-level statistical investigations of secondary data to answer questions about the comparative energetics of aging. 4. To develop and evaluate statistical methods needed in the field of the comparative energetics of aging. 5. To provide an organized series of educational offerings on statistical methods for the comparative energetics of aging which permit dissemination of expertise and knowledge to the broader scientific community. An investment in this core will achieve dividends by catalyzing more informative and rigorous research on aging within the UAB NSC and for the community of aging researchers at large.