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Analysis of Censored Longitudinal Data with Skewness and a Terminal Event
1Department of Biostatistics, School of Public Health, The University of Texas Health Science Center at Houston, 1200 Pressler St., Houston, Texas 77030, USA.
Abstract:
In HIV/AIDS study, the measurements viral load are often highly skewed and left-censored because of a lower detection limit. Furthermore, a terminal event (e.g., death) stops the follow-up process. The time to terminal event may be dependent on the viral load measurements. In this article, we present a joint analysis framework to model the censored longitudinal data with skewness and a terminal event process. The estimation is carried out by adaptive Gaussian quadrature techniques in SAS procedure NLMIXED. The proposed model is evaluated by a simulation study and is applied to the motivating Multicenter AIDS Cohort Study (MACS).
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