STATISTICAL PROBLEMS IN MULTIVARIATE SURVIVAL ANALYSIS

多变量生存分析中的统计问题

• 批准号: 2857907
• 负责人: JIANWEN CAI
• 金额: $ 9.63万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-01-01 至 2001-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2857907
• 关键词: cardiovascular disorder epidemiology; clinical research; computer program /software; data collection methodology /evaluation; human data; mathematical model; statistics /biometry

DESCRIPTION: The purpose of this grant application is to develop new statistical methodologies for analyzing multi-variate censored survival data, and to apply these methodologies to data from cardio vascular disease research. The proposal describes four projects. The first project deals with random clusters (i.e., the clusters are considered as a random sample from an underlying population of such clusters). A latent variable model is proposed for such data. A pseudo-likelihood approach is proposed for estimating the average effects of the main study variables. Asymptotic properties of the proposed statistical methods will be studied. Software will be developed. Data from the Studies of Left Ventricular Dysfunction (SOLVD) will be analyzed using the proposed method. The second project considers the problem of surrogate/missing covariates in survival data. A mean score method is proposed to deal with these surrogate/ missing covariates for univariate and multivariate survival data. Statistical properties of the proposed procedures will be studied. Software will be developed. The proposed methodologies will be applied to data from the Studies of Left Ventricular Dysfunction, the U.S.-U.S.S.R. Collaboration in Area 1 (Pathogenesis of Atherosclerosis), and the Family Heart Study. Comparisons with existing procedures will also be made. The third project concerns data with multiple levels of clustering. Marginal hazard models are proposed for analyzing such data. An estimating equation approach is proposed for estimating the marginal hazard ratio parameters. Asymptotic properties will be investigated. Software will be developed, and analysis of data from the Family Study of the Collaborative Lipid Research Clinics Program (LRC) and the Framingham Heart Study will be performed. The fourth project concerns an evaluation of the effect of a misspecified baseline hazard in the marginal hazard models for multivariate survival data. Bias and efficiency loss will be evaluated in both large and finite samples. Analysis of data from the Family Study of Collaborative Lipid Research Clinics Program (LRC) and the Framingham Heart Study will be performed. Finally, the strengths and weaknesses of the proposed methodologies will be critically examined via simulations and theoretical investigations.

描述：本次拨款申请的目的是开发新的 分析多变量删失生存的统计方法 数据，并将这些方法应用于心血管疾病的数据 研究。 该提案描述了四个项目。 第一个项目成交 具有随机聚类（即，聚类被视为随机样本 来自此类集群的基础群体）。 潜变量模型是 建议此类数据。 提出了一种伪似然方法 估计主要研究变量的平均效应。 渐近 将研究所提出的统计方法的特性。 软件 将被开发。 左心室功能障碍研究的数据 （SOLVD）将使用所提出的方法进行分析。 第二个项目考虑了替代/缺失协变量的问题 生存数据。 提出了平均分法来处理这些问题 单变量和多变量生存数据的替代/缺失协变量。 将研究所提议程序的统计特性。 软件 将被开发。 所提出的方法将应用于来自 左心室功能障碍研究，美苏合作 领域 1（动脉粥样硬化的发病机制）和家庭心脏研究。 还将与现有程序进行比较。 第三个项目涉及多级聚类的数据。 提出了边际风险模型来分析此类数据。 一个估计 提出了方程方法来估计边际风险比 参数。 将研究渐近性质。 软件将是 开发和分析来自合作家庭研究的数据 脂质研究诊所计划 (LRC) 和弗雷明汉心脏研究将 执行。 第四个项目涉及评估错误指定的影响 多变量生存的边际风险模型中的基线风险 数据。 偏差和效率损失将在大型和有限的情况下进行评估 样品。 协作脂质家族研究的数据分析 研究诊所计划 (LRC) 和弗雷明汉心脏研究将 执行。 最后，所提出的方法的优点和缺点将是 通过模拟和理论研究进行严格审查。