Statistical Methods for Interval-Censored AIDS Data

描述（由申请人提供）：本提案的总体目的是解决与艾滋病研究中产生的间隔审查数据分析相关的统计问题并开发统计方法。这些研究在艾滋病治疗的发展和评价、对艾滋病流行的了解以及与健康有关的决策过程中发挥着重要作用。具体而言，该方案包括三个目标，即1)独立审查的间隔审查失效时间数据分析，2)依赖审查的间隔审查失效时间数据分析，以及3)间隔审查计数或纵向数据分析。这三个目标将讨论的三种类型的数据通常出现在艾滋病研究中，例如艾滋病临床试验，这是发展和评价艾滋病治疗的关键组成部分，以及艾滋病队列后续研究，通常用于获得关于艾滋病疾病和艾滋病毒/艾滋病流行过程的知识。对于aim 1中的数据类型，已经提出了一些方法，但大多数方法要么缺乏严谨的研究，要么过于复杂，而对于aim 2中的数据类型，文献研究很少。因此，目标1的主要目标是制定严格和实用的方法，并评估现有的方法。对于目标2，我们的重点将是开发可以同时处理区间和依赖审查的统计方法，同时可以很容易地实现。aim 3中的数据类型在艾滋病研究中变得越来越常见，例如，艾滋病标记物现在通常用于确定艾滋病临床研究的终点。为了对它们进行分析，我们将考虑艾滋病患者的临床就诊或观察时间可能取决于或不取决于感兴趣的反应变量（例如艾滋病标志物）的情况。当观测时间与响应变量无关时，已经提出了一些回归分析方法，但没有专门开发用于治疗比较的非参数方法。请注意，回归分析方法通常需要一些分布和/或模型假设。当观测时间依赖于响应变量时，也没有可用的方法。我们将开发实用和严格的方法，允许观察时间对治疗比较和回归分析的响应变量的依赖。

DESCRIPTION (provided by applicant): The overall purpose of this proposal is to address statistical issues related to and to develop statistical methods for the analysis of interval-censored data arising from AIDS studies. Such studies play an essential role in AIDS treatment development and evaluation, the understanding of AIDS epidemic and the process of health-related policy-making. Specifically, the proposal consists of three aims and they are 1) the analysis of interval-censored failure time data with independent censoring, 2) the analysis of interval-censored failure time data with dependent censoring, and 3) the analysis of interval-censored count or longitudinal data. The three types of data that will be discussed in the three aims commonly occur in AIDS studies such as AIDS clinical trials, the key component of the development and evaluation of AIDS treatments, and AIDS cohort follow-up studies, commonly used to obtain the knowledge about the process of AIDS disease and HIV and AIDS epidemics. For the type of data in aim 1, some methods have been proposed, but most of them are either lack rigorous studies or are complicated, while for the type of data in aim 2, there exists little research in the literature. Thus the main goal for aim 1 is to develop rigorous and practical methods and evaluate existing methods. For aim 2, our focus will be to develop statistical methods that can deal with both interval- and dependent censoring together and in the meantime can be easily implemented. The type of data in aim 3 becomes more and more common in AIDS studies since, for example, AIDS markers are now commonly used to define end points for AIDS clinical studies. For the analysis of them, we will consider situations where clinical visits or observation times of AIDS patients may or may not depend on response variables of interest (e.g., AIDS markers). When observation times are independent of the response variables, some methods have been proposed for regression analysis, but there is no nonparametric method specially developed for treatment comparison. Note that methods for regression analysis commonly require some distribution and/or model assumptions. Also no approach is available when observation times depend on the response variables. We will develop practical and rigorous methods that allow the dependence of observation times on the response variables for both treatment comparison and regression analysis.