How do i compute predicted failure time from a cox model?
Eleni Rapsomaniki wrote:
Given a cox model: library(Hmisc); library(survival); (library(Design); cox.model=cph(Surv(futime, fustat) ~ age, data=ovarian, surv=T) str(cox.model) What I need is the total estimated time until failure (death), not the probability of failing at a given time (survival probability), or hazard etc, which is what I get from survest and predict for example. I suspect the answer is embarrassing simple... (BTW sorry for the duplicate email, the earlier HTML version of my message could not be viewed) Eleni Rapsomaniki Research Associate Strangeways Research Laboratory Department of Public Health and Primary Care
Eleni, You can't get the predicted mean from a Cox model unless the longest followed subject died. You can get the mean restricted life: library(Design) # implies Hmisc and survival f <- cph(..., surv=TRUE) M <- Mean(f, tmax=3) # area under S(t) from 0 to 3 time units M( ) # evaluate the mean at a vector of linear predictor values M(predict(f, data.frame( ))) # evaluate at user-chosen predictor values The mean restricted life is the life expectency given failure before time tmax. You have to use a parametric model to get the unrestricted mean lifetime estimate. Also see the Quantile function in Design to derive a function to estimate various quantiles of survival time. In Design, functions beginning with an upper case letter (like Mean, Quantile, Function, Hazard) are function generators. Frank
Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University