Analysis Core

分析核心

• 批准号: 10729953
• 负责人: Michael L. Berbaum
• 金额: $ 9.75万
• 依托单位: UNIVERSITY OF ILLINOIS AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-15 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10729953
• 关键词: Adult; Alzheimer' s Disease; Alzheimer' s disease related dementia; Alzheimer' s disease risk; Area; Awareness; Behavior Therapy; Behavioral Sciences; Caring; Cognition; Cognitive aging; Collaborations; Collection; Communication; Communities; Data; Data Analyses; Data Collection; Dementia; Development; Disparate; Elderly; Evaluation; Evaluation Research; Faculty; Feasibility Studies; Fostering; Goals; Head; Health; Health Promotion; Impaired cognition; Individual; Infrastructure; Intervention; Knowledge; Lead; Leadership; Life; Life Cycle Stages; Longitudinal Surveys; Measurement; Mentors; Mentorship; Methodology; Methods; Mission; Modeling; Observational Study; Paper; Pilot Projects; Population Sciences; Questionnaires; Research; Research Design; Research Personnel; Research Project Grants; Sample Size; Science; Scientific Advances and Accomplishments; Scientist; Social Sciences; Statistical Data Interpretation; Targeted Research; Training; Training and Infrastructure; United States National Institutes of Health; Work; Writing; behavioral and social science; career; data management; design; ethnic disparity; experience; health equity; innovation; member; population health; posters; programs; racial disparity; skills; social science research; sound; therapy development

Abstract Analysis Core (AnC) The Analysis Core will provide needed infrastructure for the training, research, and evaluation goals of the CHECA project, especially the pilot research projects for the early-career investigators. The Analysis Core members have a strong background in research design, sample size planning, exploratory and confirmatory data analysis, and technical and academic writing. These tasks are expected to be done in dialogue and collaboration with the researchers on the other cores, thus providing additional guidance and mentorship to assist the early-career researchers in developing their awareness and skill in these areas. The Analysis Core will also develop and disseminate training materials as needed. An important Analysis Core mission will be assisting with the rigorous collection and management of evaluation research data, and their analysis according to accepted statistical and methodological good practice, and their adaptation where appropriate for sharing without violation of confidentiality. This will be especially relevant in the development of behavioral intervention development training plans, which must combine substantive knowledge of the research questions with sound statistical principles to draw appropriate conclusions. Several themes are expected to be important in CHECA research, such as observational studies (including questionnaires and longitudinal surveys) for identifying individual and community strengths and challenges, and the evaluation of proposed interventions. Accordingly, a broad range of expertise is available for dealing with these disparate design and analysis challenges. Dr. Michael L. Berbaum, the head of the analysis core, has expertise in statistical analysis, writing and administration and coordination of research as well as in the mentoring of early-career researchers. He has extensive experience in research on racial and ethnic disparities on multiple health-related variables relevant to cognition and life functioning. Dr. Tianxiu Wang is an experienced biostatistician and has collaborated extensively on work related to cognitive decline and dementia in older adults. Dr. John J. Dziak has been a lead or co-author on multiple conceptual or applied papers on topics related both longitudinal research, causal inference, latent variable modeling, and intervention development and evaluation, including in clustered or multilevel contexts. He has written tutorials on the practical interpretation of statistical results for substantive researchers. Both Dr. Wang and Dr. Dziak are proficient in longitudinal data analysis, which is important for research based on a life course perspective. .

摘要分析核心(ANC) 分析核心将为以下方面的培训、研究和评估目标提供必要的基础设施 Checa项目，特别是针对职业生涯早期调查人员的试点研究项目。分析核心 成员在研究设计、样本量计划、探索性和验证性方面有很强的背景 数据分析，以及技术和学术写作。这些任务预计将在对话和 与研究人员就其他核心进行合作，从而为 帮助初出茅庐的研究人员培养他们在这些领域的意识和技能。分析核心 还将根据需要编写和分发培训材料。 一项重要的分析核心任务将是协助严格收集和管理评价 研究数据及其根据公认的统计和方法良好做法进行的分析，以及他们的 在不违反保密性的情况下，适当地进行修改，以便共享。这将是特别相关的 制定行为干预发展培训计划，其中必须结合实质性内容 掌握研究问题的知识，具备完善的统计原理，能得出适当的结论。 预计有几个主题将在Checa研究中发挥重要作用，例如观察性研究(包括 问卷和纵向调查)，以确定个人和社区的优势和挑战， 以及对拟议干预措施的评估。因此，可以利用广泛的专业知识进行交易。 面对这些截然不同的设计和分析挑战。 分析核心负责人Michael L.Berbaum博士在统计分析、写作和 研究的管理和协调以及对职业生涯早期研究人员的指导。他有 在多个与健康相关的变量上的种族和民族差异研究方面拥有丰富的经验 认知和生命功能。王天秀博士是一位经验丰富的生物统计学家，并与 广泛从事与老年人认知功能减退和痴呆症相关的工作。约翰·J·兹亚克博士一直是 在与纵向研究、因果关系相关的主题上领导或合著多篇概念性或应用性论文 推理、潜变量建模、干预发展和评估，包括在集群或 多层上下文。他撰写了关于实质性统计结果的实际解释的教程 研究人员。王博士和Dziak博士都精通纵向数据分析，这对 基于生命历程视角的研究。 。