Modelling acute HIV infection using longitudinally measured biomarker data including informative drop-out.
Background. Numerous methods have been developed to model longitudinal data. In HIV/AIDS studies, HIV markers, CD4+ count and viral load are measured over time. Informative drop-out and the lower detection limit of viral load assays can bias the results and influence assumptions of the models. Objec...
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| Language: | en |
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2010
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| Online Access: | http://hdl.handle.net/10413/690 |