Statistical methods for clinical research

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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.).