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Semi-parametric survival analysis with time dependent covariates

Johnson, W (UC at Irvine)
Tuesday 07 August 2007, 11:30-12:30

Seminar Room 1, Newton Institute


We discuss semi-parametric modeling of survival data with tiime dependent covariates. The traditional Cox model, the Cox and Oakes model, and extensions of the proportional odds model and the accelerated failure time model are all considered. Baseline survival is modeled with a mixture of finite polya trees in each instance. Model selection among semi-parametric families is accomplished using the log pseudo marginal likelihood approach discussed in Geisser and Eddy (1979). Joint modeling of longitudinal and survival data is discussed and compared with fixed versus imputed values for the longitudinal process, using a particular data set.


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