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I have done model selection between candidate Cox models, using AICc
calculated with penalized log likelihoods. Then model averaging was done
to
obtain model averaged parameter estimates. Is there a way to plot
survival
curve from the averaged model, by estimating baseline hazard and
baseline survival?
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You can fit a Cox model with fixed coefficients. Assume "fixbeta" are
the coefficients from your model averaging, then do
ffit <- coxph(Surv(time, status) ~ x1 + x2 + .... , data=mydata,
init=fixbeta, iter=0)
sfit <- survfit(fit)
The standard errors in sfit are incorrect of course. One could
bootstrap the entire model creation process to get accurate values.
Terry Therneau
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