Core C. Biostatistics Core

核心 C. 生物统计学核心

• 批准号: 10411519
• 负责人: Daniel O Stram
• 金额: $ 23.04万
• 依托单位: UNIVERSITY OF MINNESOTA
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-12-01 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10411519
• 关键词: Biostatistics Core; Complex; Computer software; Cox Models; DNA Methylation; DNA analysis; Data; Data Analyses; Data Security; Data Set; Databases; Development; Doctor of Philosophy; Genetic; Lead; Malignant neoplasm of lung; Methodology; Methods; Modeling; Outcome; Procedures; Program Research Project Grants; Quality Control; Relative Risks; Smoking; Statistical Data Interpretation; Statistical Methods; Survival Analysis; Techniques; cancer risk; case control; cigarette smoking; data integration; data management; design; epigenome-wide association studies; insight; lung cancer prevention; programs; racial and ethnic; racial difference

ABSTRACT The Biostatistics Core is responsible for providing statistical support to all projects. The Core will lead or assist in the development of all study databases and will lead their statistical analysis. The Core will perform a large variety of modeling tasks ranging from survival analyses using either relative risk (Cox) models or excess relative risk models. The Core will provide analysis of DNA methylation data including quality control, data normalization, software selection, and outcome analysis, and perform epigenome-wide association studies of quitting duration, and lung cancer risk. The Core will assist in the development of a CYP2A6 genetic score and in the application of this score to the analysis of lung cancer case control data. The Core will also provide analysis of ethnic and smoking differences, for targeted and untargeted adductomics data, Most statistical analysis will be performed using existing R or SAS procedures. In some cases, new statistical methodology may be developed if existing statistical procedures are inadequate for analysis.

摘要 生物统计核心负责为所有项目提供统计支持。核心将领导或协助 参与所有研究数据库的开发，并将领导其统计分析。核心将执行一个大的 各种建模任务，从使用相对风险（考克斯）模型或超额风险模型的生存分析 相对风险模型核心将提供DNA甲基化数据分析，包括质量控制，数据 标准化，软件选择和结果分析，并进行表观基因组范围的关联研究， 戒烟持续时间和肺癌风险。核心将协助开发CYP2A6遗传评分， 在肺癌病例对照数据分析中应用该评分。核心还将提供 针对靶向和非靶向内收切断术数据的种族和吸烟差异分析，大多数统计学 将使用现有R或SAS程序进行分析。在某些情况下，新的统计方法 如果现有的统计程序不足以进行分析，则可以制定。