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Semi-parametric survival analysis with time dependent covariates

Presented by: 
W Johnson [UC at Irvine]
Date: 
Tuesday 7th August 2007 - 11:30 to 12:30
Venue: 
INI Seminar Room 1
Abstract: 

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.

University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons