Joint modeling of longitudinal measures and primary endpoints in order to understand the association between the time trajectory of variables such as measures of immunological or virological activity in HIV-infected patients and an outcome of interest such as death has generated considerable recent interest. From a formal statistical modeling persepective, this work involves unifying models and methods for longitudinial analysis and primary endpoint analysis in a single framework. Thus, joint modeling requires familiarity both with techniques for representing longitudinal data and for analysis of the primary endpoint. I will review standard methods for longitudinal analysis, analysis of endpoints such as time to an event, and then indicate how these may be combined in various ways to provide a basis for joint analysis.
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