Focussed model selection and model averaging for the Cox regression model
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Survival data are recorded consisting of life times, censoring indicators, and a whole set of covariates of which not all of them might be worth including in an analysis. A popular model for such data is the Cox model of proportional hazards. Inside this semiparametric model we study the variable selection problem. Models are constructed for various reasons: to estimate the relative risk, a survival probability, a cumulative hazard,... The focussed information criterion provides a way to select the best model depending on this quantity of interest. We also discuss the important issue of inference after model selection, dealt with via model averaging estimators. (This is joint work with Nils Lid Hjort.)
This talk is part of the MRC Biostatistics Unit Seminars series.
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