STATISTICAL METHODS FOR SURVIVAL DATA VIA FRAILTY MODELS

描述(摘自申请者的摘要)：这是一辆R29Re- 调查员打算开发统计学的应用程序 方法对多因素生存资料进行分析。脆弱的概念将是 用于对相关的生存数据进行建模。最初，方法将是 是在双变量上下文中开发的，但大多数将随后扩展到 多变的情况。提出了四种估计协方差的方法。 变量效果，预计每一种效果都比 现有的方法在效率方面。大样本理论将是 将研究已开发的和小样本的统计特性。 此外，还提出了两种方法来估计 生存时间之间的关联。这些结果将推广到 调查脆弱模型和交叉设计的使用情况，包括 生存数据。 这项提议的另一个重要目标是发展统计 在遗传流行病学中有用的模型。申请者将会 重点关注两个问题：(1)她提出了新的生存模式 分析MZ和DZ孪晶数据以获得可解释的参数 代表遗传和环境影响；(2)申请人还 提出新的多变量生存模型，可以处理不同的 家庭成员之间的相互关系。她将推广所提出的方法 在具体目标1中，对这些模型的参数进行推断 并对它们的统计特性进行研究；这是特定的 目标2.来自NHLBI的心血管疾病数据集将用于 评估模型的适当性。这些数据是基于一项关于 双胞胎。 对给定数据集的脆弱性假设进行评估的方法 也将在这项研究中进行评估。这将通过以下方式实现 还提出了诊断图和拟合度检验统计 在研究上述方法的性能时， 对脆弱模型的假设是违反的。三个数据集将是 分析以显示所提出的方法的使用，并产生更多 完全了解使用的相对优点和局限性 脆弱模型在实际应用中的应用。

DESCRIPTION (taken from the applicant's abstract): This is an R29 re- application in which the investigator intends to develop statistical methods to analyze multivariate survival data. Frailty concepts will be used to model the correlated survival data. Initially, methods will be developed in a bivariate context, but most will then be extended to the multivariate situation. Four methods are proposed for estimating co- variate effects each of which is expected to perform better than existing methods in terms of efficiency. Large sample theory will be developed and small sample statistical properties will be investigated. In addition, two methods have been proposed for estimating the association between survival times. These results will be extended to investigate the use of frailty models and crossover designs involving survival data. Another important objective of this proposal is to develop statistical models which are useful in genetic epidemiology. The applicant will focus on two issues: (1) she proposes new survival models for the analysis of MZ and DZ twin data to obtain interpretable parameters representing genetic and environmental effects; (2) the applicant also proposes new multivariate survival models that can handle different correlations among family members. She will extend the methods proposed in specific aim 1 to make inference on the parameters of these models and their statistical properties will be investigated; this is specific aim 2. A data set on cardiovascular disease from NHLBI will be used to assess the appropriateness of the models. These data are on a study of twins. The methods for assessing the frailty assumption for a given data set will also be evaluated in this study. This will be accomplished by proposing diagnostic plots and goodness-of-fit test statistics, as well as studying the performance of the preceding methods when the assumptions of frailty models are violated. Three data sets will be analyzed to show the use of the proposed methods and to yield a more complete understanding of the relative merits and limitations of the use of frailty models in practical applications.