MISSING DATA, MEASUREMENT ERROR AND APPLICATIONS

描述：(改编自《调查者摘要》)缺失或测量错误 回归变量是癌症分析中经常遇到的变量 研究数据。这个问题是饮食研究中的一个主要问题，因为 举个例子。这项研究的总体目标是发展统计方法。 用于在存在缺失或错误测量的回归的情况下进行数据分析 变量，并将这些方法应用于流行病学和临床研究。 具体研究领域包括：1)开发一种 COX回归的非参数回归校正方法 验证数据可用；2)开发COX回归方法 具有可靠性数据；3)Logistic回归方法的发展 利用条件暴露均值对遗漏或误测进行分析 暴露；以及4)开发表征关联的方法 在多个变量之间。渐近理论将被发展，并且 将进行模拟研究。这些方法将应用于数据 来自妇女健康倡议的一项大型疾病预防试验和 对164,500名妇女进行的观察性研究，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对健康的整体影响 绝经后的女性。调查员说，提议的方法 还将支持两阶段设计，这些设计在 流行病学研究，特别是遗传流行病学。

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.