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American Statistical Association
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In this talk, I will describe a model where two or more longitudinal markers are predictors of a univariate outcome. Each longitudinal marker is summarized by a few latent trajectory variables in stage one of the model. In stage two of the model, these latent trajectory variables are used as predictors of the outcome. A fully Bayesian approach is used to obtain estimates for model parameters. The proposed approach is applied to an example germ cell cancer dataset. Preliminary results from a simulation study and methodological challenges in fitting these models will be discussed.
| Date: | Wednesday, May 2, 2007 |
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| Time: | 4:00 P.M. - 5:00 P.M. |
| Location: |
Memorial Sloan-Kettering Cancer Center
Department of Epidemiology and Biostatistics 307 East 63rd Street (between First and Second Avenues) 3rd Floor Conference Room New York, New York Note: To gain access to the building, please follow the directions by the telephone in the foyer. |