Hierarchical and Joint Longitudinal and Survival Modeling Using WinBUGS
*Bradley P. Carlin, University of Minnesota 


In this second part of the two-part presentation, we extend our investigation of hierarchical Bayesian models to the analysis of longitudinal and survival data. Here we consider traditional longitudinal data modeling, both parametric and nonparametric (Cox) survival modeling, and joint models which incorporate both of these features simultaneously. Again we use WinBUGS as our computational platform, and offer students a chance for hands-on experience with the software through a series of real-data examples. Students are encouraged to bring their own laptops (with WinBUGS and R already installed) to the workshop.

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For more information send email: ichps@amstat.orgHPSS 2005