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. .

抽象分析核心（AnC） 分析核心将为培训、研究和评估目标提供所需的基础设施 CHECA 项目，特别是针对早期职业研究者的试点研究项目。分析核心 成员在研究设计、样本量规划、探索性和验证性方面拥有深厚的背景 数据分析以及技术和学术写作。这些任务预计将通过对话和 与其他核心的研究人员合作，从而提供额外的指导和指导 帮助早期职业研究人员发展他们在这些领域的意识和技能。分析核心 还将根据需要制定和传播培训材料。 分析核心的一项重要任务是协助严格收集和管理评估 研究数据，以及根据公认的统计和方法论良好实践进行的分析，及其 在不违反保密性的情况下进行适当的修改以进行共享。这在以下方面尤其重要： 制定行为干预发展培训计划，必须结合实质性内容 了解研究问题并具有合理的统计原理，以得出适当的结论。 预计有几个主题在 CHECA 研究中很重要，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，广泛的专业知识可用于处理 面对这些不同的设计和分析挑战。 分析核心负责人 Michael L. Berbaum 博士拥有统计分析、写作和 研究的管理和协调以及早期职业研究人员的指导。他有 在研究与健康相关的多个变量的种族和民族差异方面拥有丰富的经验 认知和生活功能。王天秀博士是一位经验丰富的生物统计学家，曾与 广泛从事与老年人认知能力下降和痴呆症相关的工作。约翰·J·迪亚克 (John J. Dziak) 博士 主要或共同作者发表多篇概念性或应用性论文，主题涉及纵向研究、因果关系 推理、潜变量建模以及干预开发和评估，包括聚类或 多层次的上下文。他撰写了有关统计结果的实际解释的教程 研究人员。 Wang博士和Dziak博士都精通纵向数据分析，这对于 基于生命历程视角的研究。 。