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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