On Friday, Virgilio asked:
How can I get the predicted time of failure using the Cox Model.
I would really appreciate any help.
The suggestion put forward by Roy, to compute the area under the
survival curve, is also what I would say. Here is some code for a very
simple example:
clear
set obs 3
gen t=_n
gen f=1
stset t, f(f)
sts list
stcox, estimate basesurv(s)
sts graph
sort _t
local N1=_N+1
set obs `N1'
replace _t=0 in `N1'
replace s=1 in `N1'
sort _t
twoway line s _t, connect(stairstep) yscale(r(0 1))
gen box=s*(_t[_n+1]-_t)
egen area = sum(box)
list area in 1
In the case where the survivor function eventually reaches zero, as in
my easy example, the area under the curve is finite. But if the last
time in the dataset is a censored time, then the survivor function
remains positive for all t. So, in that case, it isn't clear to me what
you can say about the area. If you run the above code anyway, the area
you get is as if the last time is a failure.
In my last example, I have avoided this problem by making certian the
survival function goes to zero. I am estimating the expected survival
time for a subject of mean age:
clear
sysuse cancer
replace di=1 if st==39
stset st, f(di)
sum age
replace age=age-r(mean)
stcox age, basesurv(s)
stcurve, surv
sort _t
local N1=_N+1
set obs `N1'
replace _t=0 in `N1'
replace s=1 in `N1'
sort _t
twoway line s _t, connect(stairstep)
gen box=s*(_t[_n+1]-_t)
egen area = sum(box)
list area in 1
--May
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