Hi,

I have fitted a cox model with time-varying covariates (counting process style) using the cph function of the Design package.
Now I want to know the survival probability of a single individual at every time of his history.

I know the survest function, but I am not sure how to interpretet its output when using time-varying covariates. 
When the input consists of multiple values, does survest just compute the probabilities as if it are independent individuals or can/does it take in consideration that it is the history of a single individual? 
Is the latter even possible with a counting process cox model?

An example: Individual x has a history of 3 months and the cox model is fitted with two time-varying covariates: a & b

testcase <- data.frame(a =c(4,5,2), b = c(1,0,1))
survest(coxmodel, testcase, time = c(1,2,3))

Is this the right way to compute the probabilities of a single individual?

Thank you in advance!

Regards, 

Laurens Alberts


 

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