HABS-HD - Core F - Biostatistics Core

HABS-HD生物统计核心(核心F)-摘要 生物统计核心(核心F)的总体目标是监督数据质量控制(数据质量控制)和 HABS-HD U19的生物统计学工作。Core F还将向数据安全监测委员会提供报告 (DSMB)审查。这些目标将通过延续和扩大 目前正在管理的HABS-HD基础设施下开发的生物统计资源和职能 通过新成立的Core F.Core，Rema Raman博士是生物统计和 南加州大学阿尔茨海默氏症治疗研究所(ATRI)的招募人员。作为一名生物统计学家和临床医生 她在研究设计、数据质量控制、研究监测和统计分析方面拥有数十年的经验， 曾指导多个多中心临床研究项目的数据和生物统计核心和单位 神经病学。雷蒙德·帕尔默博士是一名生物统计学家/流行病学家，受过预防方面的培训 具有30多年健康促进疾病预防经验的医学统计研究方法 包括多层次设计、中介分析和现代缺失数据方法的应用。他 专门研究潜在变量建模和纵向数据分析在结构中的应用 方程式建模框架，包括在不同人群中。核心F包括教员生物统计学家 在每个U19项目所需的专业分析方面有丰富的经验。迈克尔·多诺霍，博士 在分析阿尔茨海默病(AD)病理性淀粉样蛋白的变化轨迹方面带来了丰富的经验 (A)、tau(T)和神经变性(N)标记物以及临床试验设计。尊敬的拉杰什·南迪博士、张帆博士、 和周正阳在人工智能(AI)和机器学习(ML)方法方面拥有丰富的经验 用于复杂成像、基因组学、蛋白质组学和代谢组学的分析。核心F具体目标：目标1：数据 质量控制(数据QC)(核心-核心交互)。以确保科学数据的最高质量 分析。目标2：生物统计学(核心-核心和核心-项目相互作用)。为了提供统计专业知识， 在所有HABS-HD项目的设计、方法、执行和分析方面提供咨询和指导。目标 3：数据精简和发现(核心-核心和核心-项目交互)。与每个核心协作以实现 数据缩减和新颖的数据发现分析。目标4：方法开发和交叉研究合作 (核心-核心和核心-项目互动)。生成创新的统计方法并与 更大的研究界的研究人员。

HABS-HD BIOSTATISTICS CORE (CORE F) - ABSTRACT The overall objective of the Biostatistics Core (Core F) is to oversee data quality control (data QC) and biostatistical efforts of the HABS-HD U19. Core F will also provide reports for Data Safety Monitory Board (DSMB) review. These objectives will be accomplished through the continuation and expansion of the biostatistical resources and functions developed under the ongoing HABS-HD infrastructure now being managed through a newly established Core F. Core lead, Rema Raman, PhD, is the Director of Biostatistics and Recruitment for the USC’s Alzheimer’s Therapeutic Research Institute (ATRI). As a biostatistician and a clinical trialist, she brings decades of experience in study design, data QC, study monitoring and statistical analysis, having directed Data and Biostatistics Cores and Units for several multi-center clinical research programs in Neurology. Core Co-lead, Raymond Palmer, PhD is a biostatistician/epidemiologist trained in Preventive Medicine with over 30 years of experience in Health-Promotion Disease-Prevention statistical research methods including multilevel design, mediation analysis, and the applications of modern missing data methods. He specializes in the application of latent variable modeling and longitudinal data analysis within a structural equation modeling framework, including among diverse populations. Core F includes faculty biostatisticians with extensive experience in the specialized analyses required for each of the U19 projects. Michael Donohue, PhD, brings extensive experience in analyzing trajectories of change of Alzheimer’s disease (AD) pathological amyloid (A), tau (T) and neurodegeneration (N) markers as well as clinical trial design. Drs. Rajesh Nandy, Fan Zhang, and Zhengyang Zhou have extensive experience in artificial intelligence (AI) and machine learning (ML) methods for analysis of complex imaging, genomics, proteomics, and metabolomics. Core F Specific Aims: Aim 1: Data Quality Control (Data QC) (Core – Core Interaction). To ensure highest possible quality of data for scientific analysis. Aim 2: Biostatistics (Core – Core & Core – Project Interactions). To provide statistical expertise, consultation and guidance in the design, methodology, execution, and analysis for all HABS-HD Projects. Aim 3: Data Reduction and Discovery (Core – Core & Core – Project Interactions). Collaborate with each Core for data reduction and novel data discovery analyses. Aim 4: Methods Development & Cross-Study Collaborations (Core – Core & Core – Project Interactions). To generate innovative statistical methods and collaborate with investigators in the larger research community.