[R] simple save question

Tom La Bone booboo at gforcecable.com
Tue Jul 12 20:31:24 CEST 2011


Here is a worked example. Can you point out to me where in temp rmean is
stored? Thanks.

Tom


> library(survival)
> library(ISwR)
> 
> dat.s <- Surv(melanom$days,melanom$status==1)
> fit <- survfit(dat.s~1)
> plot(fit)
> summary(fit)
Call: survfit(formula = dat.s ~ 1)

 time n.risk n.event survival std.err lower 95% CI upper 95% CI
  185    201       1    0.995 0.00496        0.985        1.000
  204    200       1    0.990 0.00700        0.976        1.000
  210    199       1    0.985 0.00855        0.968        1.000
  232    198       1    0.980 0.00985        0.961        1.000
  279    196       1    0.975 0.01100        0.954        0.997
  295    195       1    0.970 0.01202        0.947        0.994
  386    193       1    0.965 0.01297        0.940        0.991
  426    192       1    0.960 0.01384        0.933        0.988
  469    191       1    0.955 0.01465        0.927        0.984
  529    189       1    0.950 0.01542        0.920        0.981
  621    188       1    0.945 0.01615        0.914        0.977
  629    187       1    0.940 0.01683        0.907        0.973
  659    186       1    0.935 0.01748        0.901        0.970
  667    185       1    0.930 0.01811        0.895        0.966
  718    184       1    0.925 0.01870        0.889        0.962
  752    183       1    0.920 0.01927        0.883        0.958
  779    182       1    0.915 0.01981        0.877        0.954
  793    181       1    0.910 0.02034        0.871        0.950
  817    180       1    0.904 0.02084        0.865        0.946
  833    178       1    0.899 0.02134        0.859        0.942
  858    177       1    0.894 0.02181        0.853        0.938
  869    176       1    0.889 0.02227        0.847        0.934
  872    175       1    0.884 0.02272        0.841        0.930
  967    174       1    0.879 0.02315        0.835        0.926
  977    173       1    0.874 0.02357        0.829        0.921
  982    172       1    0.869 0.02397        0.823        0.917
 1041    171       1    0.864 0.02436        0.817        0.913
 1055    170       1    0.859 0.02474        0.812        0.909
 1062    169       1    0.854 0.02511        0.806        0.904
 1075    168       1    0.849 0.02547        0.800        0.900
 1156    167       1    0.844 0.02582        0.794        0.896
 1228    166       1    0.838 0.02616        0.789        0.891
 1252    165       1    0.833 0.02649        0.783        0.887
 1271    164       1    0.828 0.02681        0.777        0.883
 1312    163       1    0.823 0.02713        0.772        0.878
 1435    161       1    0.818 0.02744        0.766        0.874
 1506    159       1    0.813 0.02774        0.760        0.869
 1516    155       1    0.808 0.02805        0.755        0.865
 1548    152       1    0.802 0.02837        0.749        0.860
 1560    150       1    0.797 0.02868        0.743        0.855
 1584    148       1    0.792 0.02899        0.737        0.851
 1621    146       1    0.786 0.02929        0.731        0.846
 1667    137       1    0.780 0.02963        0.725        0.841
 1690    134       1    0.775 0.02998        0.718        0.836
 1726    131       1    0.769 0.03033        0.712        0.831
 1933    110       1    0.762 0.03085        0.704        0.825
 2061     95       1    0.754 0.03155        0.694        0.818
 2062     94       1    0.746 0.03221        0.685        0.812
 2103     90       1    0.737 0.03290        0.676        0.805
 2108     88       1    0.729 0.03358        0.666        0.798
 2256     80       1    0.720 0.03438        0.656        0.791
 2388     75       1    0.710 0.03523        0.645        0.783
 2467     69       1    0.700 0.03619        0.633        0.775
 2565     63       1    0.689 0.03729        0.620        0.766
 2782     57       1    0.677 0.03854        0.605        0.757
 3042     52       1    0.664 0.03994        0.590        0.747
 3338     35       1    0.645 0.04307        0.566        0.735
> 
> print(fit, print.rmean=TRUE)
Call: survfit(formula = dat.s ~ 1)

   records      n.max    n.start     events     *rmean *se(rmean)     median 
       205        205        205         57       4125        161         NA 
   0.95LCL    0.95UCL 
        NA         NA 
    * restricted mean with upper limit =  5565 
> 
> temp <- summary(fit)
> str(temp)
List of 12
 $ surv    : num [1:57] 0.995 0.99 0.985 0.98 0.975 ...
 $ time    : num [1:57] 185 204 210 232 279 295 386 426 469 529 ...
 $ n.risk  : num [1:57] 201 200 199 198 196 195 193 192 191 189 ...
 $ n.event : num [1:57] 1 1 1 1 1 1 1 1 1 1 ...
 $ conf.int: num 0.95
 $ type    : chr "right"
 $ table   : Named num [1:7] 205 205 205 57 NA NA NA
  ..- attr(*, "names")= chr [1:7] "records" "n.max" "n.start" "events" ...
 $ n.censor: num [1:57] 0 0 0 1 0 0 0 0 0 0 ...
 $ std.err : num [1:57] 0.00496 0.007 0.00855 0.00985 0.011 ...
 $ lower   : num [1:57] 0.985 0.976 0.968 0.961 0.954 ...
 $ upper   : num [1:57] 1 1 1 1 0.997 ...
 $ call    : language survfit(formula = dat.s ~ 1)
 - attr(*, "class")= chr "summary.survfit"


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