On Sat, 10 Jun 2006, Gregory Pierce wrote:
Hello friends and fellow R users,
I have successfully tabulated and entered my survival data into R and
have generated survival curves. But I would like to be able to determine
what the survival rates are now at one month, three months, six months
and one year.
I have a data set, via.wall, which I have entered into R, and which
generates the following Surv object:
Surv(Days,Status==1)
[1] 648+ 3 109 241 997 849+ 1053+ 539+ 121 42 490
21 870+
[16] 175 20 434 289 826+ 831+ 664 698+ 5 24 655+ 187+
85+ 65+
[31] 547+ 81 55+ 69 499+ 448+ 0 158+ 31 246+ 230+ 19
118+ 54
[46] 48+ 45+ 21+ 670+ 585 558+ 544+ 494 481+ 474+ 472+ 461 447
446+ 443+
[61] 429+ 423+ 401 395+ 390 390+ 389+ 383+ 383+ 373+ 362+ 354 344+
342 336+
[76] 335+ 326+ 306 300+ 292 284+ 280+ 271 246+ 237+ 234 233+ 233
230+ 230+
[91] 226+ 225+ 218+ 215 211+ 199+ 191+ 191 190+ 184+ 169+ 163+ 161+
153 150
[106] 129+ 110+ 107+ 100+ 84+ 77+ 69+ 52+ 38+ 11+
names(wall.via)
[1] Description Patient Physician MRN Age
[6] Status DaysCr INR BR
[11] MELDtype
I can guess pretty accurately by looking at the graph what the survival
rates are at each interval, but I would like to understand how to
instruct R to calculate it. Hope I have made this clear. I am just a
beginner, so forgive me if this is trivial. It just isn't clear to me.
You will have generated survival curves with survfit(). Give them to
summary() and specify the times you want. For example, using one of the
built-in data sets:
fit - survfit(Surv(time, status) ~ x, data = aml)
summary(fit,times=c(10,20,30,40))
Call: survfit(formula = Surv(time, status) ~ x, data = aml)
x=Maintained
time n.risk n.event survival std.err lower 95% CI upper 95% CI
10 10 10.909 0.08670.7541.000
20 7 20.716 0.13970.4881.000
30 5 10.614 0.15260.3770.999
40 3 20.368 0.16270.1550.875
x=Nonmaintained
time n.risk n.event survival std.err lower 95% CI upper 95% CI
10 8 40.667 0.136 0.44680.995
20 6 10.583 0.142 0.36160.941
30 4 30.292 0.139 0.11480.741
40 2 10.194 0.122 0.05690.664
-thomas
Thomas Lumley Assoc. Professor, Biostatistics
[EMAIL PROTECTED] University of Washington, Seattle
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