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Which survival model? Model selection and model averaging issues for analysis of survival and event history data

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If you have a question about this talk, please contact Li Su .

Most model selection methods work in “overall modus”, as for the AIC , BIC, etc.; one is then expected to you use what one gets, regardless of the actual purpose of the analysis. Here I focus the machinery, looking for models that work well for a given purpose, and in particular choose to accept and then work with the view that even with the same data set and the same list of candidate models, one model may be best for explaining e.g. survival for men above sixty whereas another model may be better for e.g. estimating median remaining survival time for women, etc. This ideas in particular lead to version of FIC (focussed information criteria), for multiplicative Cox regression and for additive Aalen regression.

This talk is part of the MRC Biostatistics Unit Seminars series.

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