Statistical Methods in Current Cancer Research

当前癌症研究中的统计方法

• 批准号: 6870163
• 负责人: DANYU LIN
• 金额: $ 20.6万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-04-01 至 2008-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6870163
• 关键词: clinical research; computer program /software; computer simulation; computer system design /evaluation; data collection methodology /evaluation; disease /disorder onset; experimental designs; health care cost /financing; health science research analysis /evaluation; human data; longitudinal human study; mathematical model; method development; model design /development; neoplasm /cancer epidemiology; quality of life; statistics /biometry

DESCRIPTION (provided by applicant): The broad, long-term objectives of this research are the developments of statistical methods for the analysis of censored failure times and incomplete repeated measures from longitudinal cancer studies. The specific aims of this competing renewal application include: (1) investigation of efficient likelihood-based methods for semi-parametric regression models for possibly correlated failure times subject to right or interval censoring; (2) construction of rank-based inference procedures for the regression analysis of incomplete repeated measures; (3) development of statistical methods for detecting genetic linkage based on censored age-of onset phenotypes or incomplete repeated measures of a quantitative trait and for assessing genome-wide statistical significance in linkage analysis; (4) exploration of strategies for accommodating population stratification in the association analysis of censored failure time phenotypes. Some of these topics are longstanding statistical problems while others are emerging issues from current cancer studies. The proposed solutions are built on sound statistical principles. The asymptotic properties of the new estimators and test statistics will be studied rigorously with the use of counting-process martingale theory, modern empirical process theory and semi-parametric efficiency theory. Their operating characteristics in practical settings will be evaluated extensively through computer simulation. The usefulness of the proposed inference procedures will be illustrated with real medical studies, some of which are carried out at the University of North Carolina. The software implementing the new methodologies will be developed for public use. This research will not only advance the fields of longitudinal data analysis, survival analysis and statistical genetics, but will also provide valuable new tools to cancer researchers.

描述（由申请人提供）：这项研究的广泛长期目标是统计方法的发展，用于分析审查失败时间和纵向癌症研究的不完整重复测量。该竞争性更新应用的具体目的包括：（1）研究基于有效的可能性回归模型的有效可能相关的失败时间的方法； （2）构建基于等级的推理程序，以进行不完整的重复措施的回归分析； （3）开发基于审查的发作表型或定量性状的不完整重复测量的统计方法，用于检测遗传联系，并评估链接分析中全基因组统计学的显着性； （4）在审查失败时间表型的关联分析中探索可容纳人口分层的策略。其中一些主题是长期存在的统计问题，而另一些主题是当前癌症研究的出现问题。所提出的解决方案建立在健全的统计原理上。新估计量和测试统计数据的渐近特性将通过使用计数过程中的Martingale理论，现代经验过程理论和半参数效率理论进行严格研究。它们在实际设置中的操作特性将通过计算机模拟进行广泛评估。拟议的推理程序的有用性将通过实际的医学研究来说明，其中一些研究是在北卡罗来纳大学进行的。实施新方法的软件将用于公共使用。这项研究不仅将推进纵向数据分析，生存分析和统计遗传学的领域，而且还将为癌症研究人员提供宝贵的新工具。