Statistical Methods for Interval-Censored AIDS Data

说明(申请人提供)：本提案的总体目的是处理与艾滋病研究产生的间隔审查数据相关的统计问题，并发展统计方法。这些研究对艾滋病治疗的发展和评估、对艾滋病流行的了解以及与健康相关的政策制定过程都起着至关重要的作用。具体地说，该方案包括三个目标：1)区间截尾失效时间数据的独立截尾分析，2)相依截尾失效时间数据的分析，3)区间截尾计数或纵向数据的分析。将在三个目标中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，艾滋病治疗开发和评估的关键组成部分，以及艾滋病队列跟踪研究，通常用于获得关于艾滋病疾病过程和艾滋病毒/艾滋病流行的知识。对于目标1中的数据类型，已经提出了一些方法，但大多数要么缺乏严谨的研究，要么很复杂，而对于目标2中的数据类型，文献中的研究很少。因此，目标1的主要目标是制定严格和实用的方法，并评估现有方法。对于目标2，我们的重点将是开发统计方法，既可以同时处理区间截尾和相依截尾，同时又可以很容易地实现。AIM 3中的数据类型在艾滋病研究中变得越来越常见，因为，例如，艾滋病标志物现在通常被用来定义艾滋病临床研究的终点。在进行分析时，我们会考虑爱滋病患者的临床探访或观察时间可能会或可能不会视乎有关的反应变量(例如爱滋病标志物)而定的情况。当观察时间与响应变量无关时，已有一些回归分析方法被提出，但还没有专门用于处理比较的非参数方法。请注意，回归分析方法通常需要一些分布和/或模型假设。此外，当观测时间取决于响应变量时，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反应变量的依赖。

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.