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Thursday, January 11
Thu, Jan 11, 7:30 AM - 9:00 AM
Crystal Ballroom Prefunction
Continental Breakfast & Poster Session II

WITHDRAWN: Analysis of Longitudinal Survival Data with Multiple Features (304171)

Tao Lu, University of Nevada 

Keywords: longitudinal data; survival data

Longitudinal survival data are often collected from clinical studies. Mixed-effects joint models are commonly used for the analysis of such data. Nevertheless, the following issues may arise in longitudinal survival data analysis: (i) most joint models assume a simple parametric mixed-effects model for longitudinal outcome, which may obscure the important relationship between response and covariates; (ii) clinical data often exhibits asymmetry so that symmetric assumption for model errors may lead to biased estimation of parameters; (iii) response may be missing and missingness may be informative. There is little work concerning all of these issues simultaneously. Motivated by an AIDS clinical data, we develop a Bayesian varying coefficient mixed-effects joint model with skewness and missingness to study the simultaneous influence of these features.