Analysis of censored longitudinal data with skewness and a terminal event

作者：Su Xiao; Luo Sheng^*

来源：Communications in Statistics - Simulation and Computation, 2017, 46(7): 5378-5391.

DOI：10.1080/03610918.2016.1157181

• Detection limit
• Informative censoring
• Joint model
• Skew distributions
• Tobit model
• Statistics
• Numerical analysis

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).

• 出版日期2017