HIERARCHICAL MODELING FOR ASSESSING BREAST CANCER CARE

本申请中提出的研究旨在解决几个问题 乳腺癌护理流行病学中的关键方法学问题 一类新的统计模型，称为分层模型。 我们将 说明其应用程序的两个数据集的重要性 乳腺癌的治疗 虽然乳腺癌护理是 这些新方法的发展的主要领域，我们表明， 分层模型允许广泛的流行病学问题， 从一个共同的概念基础出发。 的具体问题 这些新方法所解决的问题将包括对学位的考试 遵守乳腺癌护理临床指南， 量化各区域遵守率的变化幅度 医院和供应商。 层次模型允许调查人员将多个来源 数据的变异性，并跨单位汇总（例如，医院， 医生），从而利用单位内的相似性， 考虑到单位之间的差异。 因此，它们可以用于 通过借用 合奏。 我们将比较本补助金中提出的方法与传统方法 评估乳腺癌护理的方法， 分层模型的潜在优势。 研究 本提案中所述的将汇集一个统计网络， 流行病学和医学研究人员，包括一个 每个领域的领导者，以确保验证和 将这些新方法融入流行病学研究。 我们将 通过一系列论文传播我们的方法和结果， 与咨询委员会的会议，并通过在科学会议上的发言， 会议.

The research proposed in this application is designed to address several key methodological issues in the epidemiology of breast cancer care using a new class of statistical models called hierarchical models. We will illustrate their application to two data sets of importance in the epidemiology of breast cancer care. Although breast cancer care is the primary area for development of these new methodologies, we show that hierarchical models permit a wide range of epidemiological problems to be approached from a common conceptual foundation. the specific problems addressed by these new methods will include an examination of the degree of compliance with clinical guidelines for breast cancer care and quantification of the magnitude of variation in compliance rates across hospitals and providers. Hierarchical models permit investigators to incorporate multiple sources of variability in the data, and to pool across units (e.g., hospitals, physicians), thus capitalizing on similarities within units while accounting for differences across units. thus, they may be used to provide better inferences for individual units by borrowing strength from the ensemble. We will compare the methods proposed in this grant with conventional methods for assessing breast cancer care to facilitate an understanding of the potential advantages of hierarchical models. The research described in this proposal will bring together a network of statistical, epidemiological and medical researchers, including an Advisory Board of leaders in each of these areas, in an effort to ensure validation and integration of these new methods in epidemiology research. We will disseminate our methods and results through a series of papers and meetings with the Advisory Board, and through presentations at scientific meetings.