Statistical methods for clinical research

提出的研究计划的目标是开发新的统计方法来分析临床实验中经常遇到的纵向或聚类相关数据。纵向数据的一个重要特征是，一个人的重复反应往往是相关的。例如，在艾滋病临床试验中，患者可能会在多个评估次数上被重复测量，同一患者的纵向反应可能会遵循一定的相关结构。此外，如果从一个家庭的兄弟姐妹中收集基因数据，那么这些数据也可能与兄弟姐妹携带父母基因以及生活在相似环境的事实相关联。这项工作的目标是开发和探索合适的方法来描述相关结构，并研究反应变量（例如，疾病状态）与一些其他解释变量（例如，候选基因，治疗等）的关联。

The objective of the proposed research program is the development of novel statistical methods for analyzing longitudinal or clustered correlated data commonly encountered in clinical experiments. An important feature of longitudinal data is that the repeated responses from an individual are often correlated. For example, in AIDS clinical trials, patients may be measured repeatedly at a number of assessment times, and the longitudinal responses from the same patient may follow a certain correlation structure. Furthermore, if genetic data are collected from siblings in a family, then the data may also be correlated by the fact that the siblings carry their parental genes as well as live in a similar environment. The goal of this work is to develop and explore suitable methods to describe the correlation structure and to investigate the association of a response variable (for example, disease status) with some other explanatory variables (for example, candidate genes, treatments, etc.).