Abstract
ABSTRACTThe study on relationship between HIV viral load and CD4 counts is critical for AIDS treatment. We study the varying relationship between viral load and CD4 counts by accounting for factors usually encountered in practice: skewed distribution in data, competing risks time-to-event, and mismeasured covariate. We propose a joint modeling approach to take into account all these factors. A Bayesian approach is adopted to make inference on the joint model. The proposed model and method are applied to an AIDS study. To testify the validity of the method, simulation studies are performed.
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