Community-Based Studies in Cancer and Environment

癌症与环境的社区研究

• 批准号: 6573264
• 负责人: Yi Li
• 金额: $ 24.37万
• 依托单位: DANA-FARBER CANCER INST
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-04-14 至 2007-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6573264
• 关键词: clinical research; community; environment related neoplasm /cancer; long term survivor; mathematical model; statistics /biometry

DESCRIPTION (provided by applicant): This is a grant application for methodological research in statistical issues related to community-based studies in cancer and environment. The proposed activities are motivated by the projects of cancer prevention and environmental epidemiology that the PI is currently involved in. Specifically, the PI plans to: (1) Establish models for spatial survival data. We propose two classes of models: spatial frailty survival models and marginal spatial survival models. We develop the imputed partial likelihood score method to draw inference based on the frailty models. For the marginal survival models, we adapt the composite likelihood approach and develop an estimating equation to estimate the regression coefficients and the variance components simultaneously. (2) Study two special aspects of spatial survival data. We analyze spatial failure time data with general censoring types, including right, left and interval censoring. We develop models for spatially correlated failure time data with measurement errors in covariates. (3) Develop models for spatially correlated data that are observed in discrete time (for example, at regular, pre-specified follow-up times). Specifically, we consider models for spatially correlated grouped survival data and spatial transitional regression models for the analysis of repeated discrete responses, e.g. binary status, observed in a spatial setting. To cope with informative or non-ignorable dropout, we also propose jointly modeling the grouped survival and the transitional processes. Empirical data analysis will play a central role in all specific aims. Available relevant data include Workers Against Risk of Tobacco Study, East Boston Asthma Study and Established Populations for the Epidemiologic Study of the Elderly. Although motivated by applied problems in cancer and environmental health studies, the proposed research offers useful contributions to general statistical methodology in survival analysis, spatial analysis, longitudinal data analysis and measurement error modeling.

描述（由申请人提供）：这是一项拨款申请，用于与癌症和环境社区研究相关的统计问题的方法学研究。拟议活动的动机是 PI 目前参与的癌症预防和环境流行病学项目。具体而言，PI 计划： (1)建立空间生存数据模型。我们提出两类模型：空间脆弱生存模型和边际空间生存模型。我们开发了估算部分似然评分方法，以根据脆弱性模型进行推断。对于边际生存模型，我们采用复合似然方法并开发一个估计方程来同时估计回归系数和方差分量。 (2)研究空间生存数据的两个特殊方面。我们使用一般审查类型（包括右审查、左审查和间隔审查）来分析空间故障时间数据。我们开发了具有协变量测量误差的空间相关故障时间数据模型。 (3) 为在离散时间（例如，在定期的、预先指定的后续时间）观察到的空间相关数据开发模型。具体来说，我们考虑空间相关分组生存数据的模型和用于分析重复离散响应的空间过渡回归模型，例如在空间环境中观察到的二元状态。为了应对信息丰富或不可忽视的丢失，我们还建议对分组生存和过渡过程进行联合建模。 实证数据分析将在所有具体目标中发挥核心作用。现有的相关数据包括工人对抗烟草风险研究、东波士顿哮喘研究和老年人流行病学研究。尽管受到癌症和环境健康研究中应用问题的推动，拟议的研究为生存分析、空间分析、纵向数据分析和测量误差建模中的一般统计方法做出了有益的贡献。