This application aims to develop a set of new statistical tools and software to analyze complex longitudinal data generated in HIV prevention research. These new tools will be used to improve our understanding of the health implications of longitudinal outcomes, such as drug adherence, in HIV translational research and clinical care. In this project, we aim to develop a set of new statistical tools to cope with the complexity involved. Speciﬁcally, we aim to develop methods
Aim 1. Develop methods for assessing the longitudinal pattern of recurrent events over time.
Aim 2. Develop methods of threshold regression models for longitudinal data subject to interval censoring.
Aim 3. Develop methods for multi-level event history studies with high-dimensional covariates subject to interval censoring.
Aim 4. Develop methods for analyzing data collected from complex sampling design.