Hi, I have some questions on how to estimate the survival function from a Cox model. I know how to do this in R using survfit(). 


But let's say the model was done is another software, and I was only given the estimate of baseline cumulative hazard "A0(t=10)" at the specified time "t=10" (baseline cumulative hazard refers to when covariate X=0)and the beta estimate "b" for the covariate used in Cox model "X". 


So the survival function at time 10 for a given covariate value x can be calculated as:

A(t=10|X=x) = exp(b*x)*A0(t=10) where A is cumulative hazard when X=x
S(t=10|X=x) = exp(-A(t=10|X=x)) where S is survival function to be calculated

Now I want to calculate confidence interval for S(t=10|X=x). I think I need to calculate the CI for cumulative hazard A(t=10|X=x) first and then exponentiate it to get CI for S, based on the relationship S = exp(-A).

To get CI for A, I need to calculate the estimate of standard error of A. I know the other software can give me the standard error of A0, the baseline cumulative hazard. Based on the relationship A = exp(b*x)*A0, I guess I'll need the standard error for b. But how do I calculate the standard error for A based on standard errors for A0 and b?

Any insights would be greatly appreciated!

John
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