On Mar 30, 2009, at 5:55 PM, Marc Schwartz wrote:

Hi all,

Using:

 R version 2.8.1 Patched (2009-03-07 r48068)

on OSX (10.5.6) with survival version:

 Version:            2.35-3
 Date:               2009-02-10


I get the following using the first example in ?summary.survfit:

> summary( survfit( Surv(futime, fustat)~1, data=ovarian))
Call: survfit(formula = Surv(futime, fustat) ~ 1, data = ovarian)

time n.risk n.event survival std.err lower 95% CI upper 95% CI
  59     26       1    0.962  0.0377        0.890        1.000
 115     25       1    0.923  0.0523        0.826        1.000
 156     24       1    0.885  0.0627        0.770        1.000
 268     23       1    0.846  0.0708        0.718        0.997
 329     22       1    0.808  0.0773        0.670        0.974
 353     21       1    0.769  0.0826        0.623        0.949
 365     20       1    0.731  0.0870        0.579        0.923
 431     17       1    0.688  0.0919        0.529        0.894
 464     15       1    0.642  0.0965        0.478        0.862
 475     14       1    0.596  0.0999        0.429        0.828
 563     12       1    0.546  0.1032        0.377        0.791
 638     11       1    0.497  0.1051        0.328        0.752


> summary( survfit( Surv(futime, fustat)~1, data=ovarian), scale = 365.25)
Call: survfit(formula = Surv(futime, fustat) ~ 1, data = ovarian)

time n.risk n.event survival std.err lower 95% CI upper 95% CI
  59     26       1    0.962  0.0377        0.890        1.000
 115     25       1    0.923  0.0523        0.826        1.000
 156     24       1    0.885  0.0627        0.770        1.000
 268     23       1    0.846  0.0708        0.718        0.997
 329     22       1    0.808  0.0773        0.670        0.974
 353     21       1    0.769  0.0826        0.623        0.949
 365     20       1    0.731  0.0870        0.579        0.923
 431     17       1    0.688  0.0919        0.529        0.894
 464     15       1    0.642  0.0965        0.478        0.862
 475     14       1    0.596  0.0999        0.429        0.828
 563     12       1    0.546  0.1032        0.377        0.791
 638     11       1    0.497  0.1051        0.328        0.752

Of course the time periods in the second output should be scaled to years, that is (time / 365.25).

I noted this today running some Sweave code, but not sure when the actual change in behavior occurred. I can replicate the same behavior on a Windows machine here as well, so this is not OSX specific.


A quick follow up here. I reverted to:

  R version 2.8.1 (2008-12-22)

which includes survival version:

Version:       2.34-1
Date:          2008-03-31


In that version, I get:

> summary( survfit( Surv(futime, fustat)~1, data=ovarian), scale = 365.25)
Call: survfit(formula = Surv(futime, fustat) ~ 1, data = ovarian)

  time n.risk n.event survival std.err lower 95% CI upper 95% CI
 0.162     26       1    0.962  0.0377        0.890        1.000
 0.315     25       1    0.923  0.0523        0.826        1.000
 0.427     24       1    0.885  0.0627        0.770        1.000
 0.734     23       1    0.846  0.0708        0.718        0.997
 0.901     22       1    0.808  0.0773        0.670        0.974
 0.966     21       1    0.769  0.0826        0.623        0.949
 0.999     20       1    0.731  0.0870        0.579        0.923
 1.180     17       1    0.688  0.0919        0.529        0.894
 1.270     15       1    0.642  0.0965        0.478        0.862
 1.300     14       1    0.596  0.0999        0.429        0.828
 1.541     12       1    0.546  0.1032        0.377        0.791
 1.747     11       1    0.497  0.1051        0.328        0.752


So the functional loss of the 'scale' argument took place subsequent to that release. From a review of the code in both versions, it would appear that substantive changes took place to the function in the intervening time frame, including the addition of the 'rmean' and 'extend' arguments. One of the changes appears to be the setting of:

  stime <- fit$time/scale

in the old version and I do not see a parallel adjustment in the time scale in the new version and the subsequent use of fit$time later in the new function.

Given the substantive changes to the function code, I am hesitant to propose patches for fear of introducing breakage elsewhere. I also need to get some work done for a client today, before I leave for vacation tomorrow for a week, otherwise I would spend more time evaluating possible patches.

I hope that the above is enough to give Terry and Thomas some narrowed focus.

Regards,

Marc

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