EPIDEMIOLOGIC METHODS FOR CASE-CONTROL/ECOLOGIC STUDIES

病例对照/生态学研究的流行病学方法

• 批准号: 3177796
• 负责人: ROBERT F WOOLSON
• 金额: $ 7.16万
• 依托单位: UNIVERSITY OF IOWA
• 依托单位国家: 美国
• 财政年份: 1985
• 资助国家: 美国
• 起止时间: 1985-09-01 至 1988-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/3177796
• 关键词: cancer information system; computer simulation; environment related neoplasm /cancer; mathematical model; neoplasm /cancer epidemiology

The principal aims of this project are to study a number of statistical problems in the analysis of epidemiologic data. The problems studied are relevant to the analysis of case-control data and ecologic epidemiologic data. Since odds ratios form the nucleus of many epidemiologic analyses, this research addresses issues in model building with odds ratios, or more generally log-linear modeling. This research will contrast selected statistical estimation and testing procedures using both computer and theoretical techniques and the methodology will be applied to select cancer case-control data sets. The focus will be on problems associated with log-linear modeling in the face of numerous predictor and stratification variables. Such situations inevitably lead to problems in the selection of variables for analysis. Furthermore, with numerous variables the resulting cross-tabulations lead to sparse, perhaps incomplete multidimensional tables. These problems will be studied in this research. For ecologic epidemiological data, the issue of standardization of incidence rates arises. In this research various methods of rate standardization or regression adjustment will be compared. Emphasis will be on the problems which typically arise in the analysis of epidemiologic data. This research will lead to improved statistical methodology for the analysis of complex epidemiologic data. The issues studied have immediate implications for the analysis of epidemiologic data.

该项目的主要目的是研究一些统计数据 流行病学数据分析中的问题。 研究的问题有 与病例对照数据和生态流行病学分析相关 数据。 由于比值比构成许多流行病学分析的核心， 这项研究解决了比值比或更多模型构建的问题 通常对数线性建模。 本研究将对比所选 使用计算机和计算机进行统计估计和测试程序 理论技术和方法将应用于选择癌症 病例对照数据集。 重点将放在与以下相关的问题上 面对众多预测变量和分层的对数线性建模 变量。 这种情况不可避免地会导致选择问题。 用于分析的变量。 此外，由于存在许多变量，结果 交叉制表导致稀疏的，也许不完整的多维 表。 这些问题将在本研究中进行研究。 对于生态流行病学数据，标准化问题 发病率出现。 本研究中采用了多种方法 将比较标准化或回归调整。 强调将 针对流行病学分析中通常出现的问题 数据。 这项研究将改进统计方法 分析复杂的流行病学数据。 研究的问题具有直接意义 对流行病学数据分析的影响。