MISSING DATA, MEASUREMENT ERROR AND APPLICATIONS

数据缺失、测量错误和应用

• 批准号: 2449990
• 负责人: CHING-YUN WANG
• 金额: $ 11.93万
• 依托单位: FRED HUTCHINSON CANCER RESEARCH CENTER
• 依托单位国家: 美国
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-12-15 至 2002-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2449990
• 关键词: cancer risk; data collection methodology /evaluation; dietary calcium; dietary supplements; female; hormone therapy; human data; method development; neoplasm /cancer epidemiology; nutrition related tag; postmenopause; statistics /biometry; vitamin D; vitamin therapy; women's health

DESCRIPTION: (Adapted from Investigator's Abstract) Missing or mismeasured regression variables are frequently encountered in the analysis of cancer research data. This problem is a major issue in dietary research, for example. The broad goal of this research is to develop statistical methods for data analysis in the presence of missing or mismeasured regression variables, and to apply these methods to epidemiologic and clinical studies. Specific areas of research include the following: 1) development of a nonparametric regression calibration method for Cox regression when validation data are available; 2) development of methods for Cox regression with reliability data; 3) development of methods for logistic regression analysis using conditional exposure mean for missing or mismeasured exposures; and 4) development of methods for characterizing associations between multiple variables. Asymptotic theory will be developed and simulation studies will be conducted. The methods will be applied to data from the Women's Health Initiative, a large disease prevention trial and observational study involving 164,500 women with the objective of evaluating the benefits and risks of dietary modification, hormone replacement therapy and supplementation with calcium and vitamin D on the overall health of postmenopausal women. The investigator states that the proposed methods will also accommodate two-stage designs which are becoming popular in epidemiologic research and particular in genetic epidemiology.

描述：（改编自研究者摘要）缺失或测量错误 回归变量在癌症分析中经常遇到 研究数据。 这个问题是饮食研究中的一个主要问题，因为 example. 这项研究的主要目标是发展统计方法 用于存在缺失或误测回归的数据分析 变量，并将这些方法应用于流行病学和临床研究。 具体的研究领域包括：1）开发一个 考克斯回归的非参数回归校准方法， 验证数据可用; 2）开发考克斯回归方法 可靠性数据; 3）发展逻辑回归方法 使用缺失或测量错误的条件暴露均值进行分析 暴露;以及4）开发表征关联的方法 多个变量之间。 渐近理论将得到发展， 将进行模拟研究。 这些方法将应用于数据 来自妇女健康倡议，一项大型疾病预防试验， 一项涉及164，500名女性的观察性研究，目的是评估 饮食调整、激素替代疗法的益处和风险 补充钙和维生素D对整体健康的影响 绝经后妇女。 研究人员指出，所提出的方法 也将容纳两个阶段的设计，这是越来越流行的， 流行病学研究，特别是遗传流行病学。