Kaplan-Meier Analysis
Connor Landreth
2023-04-05
R Markdown
Load in relevant packages
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## ℹ Use the ]8;;http://conflicted.r-lib.org/conflicted package]8;; to force all conflicts to become errorslibrary(survey)## Warning: package 'survey' was built under R version 4.2.3## Loading required package: grid
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## Loading required package: survival## Warning: package 'survival' was built under R version 4.2.3##
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## dotchartlibrary(knitr)
library(survival)
library(survminer)## Warning: package 'survminer' was built under R version 4.2.3## Loading required package: ggpubr## Warning: package 'ggpubr' was built under R version 4.2.3##
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## myelomaRead in DATA, sample is ‘survivor.csv’
Create cencored variable (right censoring, here voluntary, know event outcome, describe/predict 1). So if an individual left the company voluntarily and their end is described in the data, we assign them a 1. If they did not experience the event, we assign them a zero, whether they were involuntarily fired or it wasn’t recorded.
survive$censored[survive$Turnover == 1] <- 1 #Experienced event
survive$censored[survive$Turnover == 0 | survive$Turnover ==2 ] <- 0Below - Introduce and Inspect Distribution of Length of Service (LOS) variable
hist(survive$LOS)
hist(subset(survive, Turnover==0)$LOS,
xlim=c(250,2500)) #Pople who stayed in org, 1 is voluntary turnover
Kaplan-Meier Analysis (KM) -Life Table Generation
Specify KMA Model, how do survival rates differ by group (introduce different groups surveyed by IRS possible) Here depicted as race, sub for 40/41(?)
km_fit1 <- survfit(Surv(LOS, censored) ~ 1, #NULL model, basic a line of best fit and probability
data=survive,
type="kaplan-meier")
print(km_fit1)## Call: survfit(formula = Surv(LOS, censored) ~ 1, data = survive, type = "kaplan-meier")
##
## n events median 0.95LCL 0.95UCL
## [1,] 701 463 1459 1417 1495Summarize KMA results using default time intervals & create life table
summary(km_fit1)## Call: survfit(formula = Surv(LOS, censored) ~ 1, data = survive, type = "kaplan-meier")
##
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 1001 701 1 0.9986 0.00143 0.9958 1.000
## 1003 699 1 0.9971 0.00202 0.9932 1.000
## 1004 698 1 0.9957 0.00247 0.9909 1.000
## 1005 697 1 0.9943 0.00285 0.9887 1.000
## 1006 696 1 0.9929 0.00318 0.9866 0.999
## 1007 695 1 0.9914 0.00348 0.9846 0.998
## 1008 694 1 0.9900 0.00376 0.9827 0.997
## 1009 693 1 0.9886 0.00402 0.9807 0.996
## 1010 692 1 0.9871 0.00426 0.9788 0.996
## 1012 691 1 0.9857 0.00448 0.9770 0.995
## 1016 690 1 0.9843 0.00470 0.9751 0.994
## 1018 688 1 0.9829 0.00491 0.9733 0.993
## 1020 687 1 0.9814 0.00510 0.9715 0.991
## 1021 686 1 0.9800 0.00529 0.9697 0.990
## 1022 685 1 0.9786 0.00547 0.9679 0.989
## 1023 684 1 0.9771 0.00565 0.9661 0.988
## 1024 683 1 0.9757 0.00582 0.9644 0.987
## 1025 682 1 0.9743 0.00599 0.9626 0.986
## 1027 680 1 0.9728 0.00615 0.9609 0.985
## 1028 679 1 0.9714 0.00630 0.9591 0.984
## 1029 678 1 0.9700 0.00645 0.9574 0.983
## 1030 677 1 0.9685 0.00660 0.9557 0.982
## 1031 676 1 0.9671 0.00674 0.9540 0.980
## 1032 675 1 0.9657 0.00689 0.9523 0.979
## 1033 674 1 0.9642 0.00702 0.9506 0.978
## 1034 673 1 0.9628 0.00716 0.9489 0.977
## 1035 672 1 0.9614 0.00729 0.9472 0.976
## 1036 671 1 0.9599 0.00742 0.9455 0.975
## 1037 670 1 0.9585 0.00754 0.9438 0.973
## 1038 669 1 0.9571 0.00767 0.9422 0.972
## 1039 668 1 0.9556 0.00779 0.9405 0.971
## 1040 667 1 0.9542 0.00791 0.9388 0.970
## 1041 666 1 0.9528 0.00802 0.9372 0.969
## 1042 665 1 0.9513 0.00814 0.9355 0.967
## 1044 663 1 0.9499 0.00825 0.9339 0.966
## 1045 662 1 0.9485 0.00836 0.9322 0.965
## 1046 661 1 0.9470 0.00847 0.9306 0.964
## 1047 660 1 0.9456 0.00858 0.9289 0.963
## 1049 659 1 0.9442 0.00869 0.9273 0.961
## 1052 658 1 0.9427 0.00879 0.9257 0.960
## 1053 657 1 0.9413 0.00889 0.9240 0.959
## 1054 656 1 0.9399 0.00900 0.9224 0.958
## 1055 655 1 0.9384 0.00910 0.9208 0.956
## 1056 654 1 0.9370 0.00919 0.9192 0.955
## 1057 653 1 0.9356 0.00929 0.9175 0.954
## 1058 652 1 0.9341 0.00939 0.9159 0.953
## 1059 651 1 0.9327 0.00948 0.9143 0.951
## 1061 649 1 0.9313 0.00958 0.9127 0.950
## 1062 648 1 0.9298 0.00967 0.9111 0.949
## 1063 647 1 0.9284 0.00976 0.9095 0.948
## 1064 646 1 0.9269 0.00985 0.9078 0.946
## 1066 644 1 0.9255 0.00994 0.9062 0.945
## 1067 643 1 0.9241 0.01003 0.9046 0.944
## 1068 642 1 0.9226 0.01011 0.9030 0.943
## 1069 641 1 0.9212 0.01020 0.9014 0.941
## 1070 640 1 0.9197 0.01029 0.8998 0.940
## 1071 639 1 0.9183 0.01037 0.8982 0.939
## 1072 638 1 0.9169 0.01045 0.8966 0.938
## 1073 637 1 0.9154 0.01053 0.8950 0.936
## 1074 636 1 0.9140 0.01062 0.8934 0.935
## 1075 635 1 0.9126 0.01070 0.8918 0.934
## 1077 634 1 0.9111 0.01078 0.8902 0.932
## 1078 633 1 0.9097 0.01085 0.8886 0.931
## 1079 632 1 0.9082 0.01093 0.8871 0.930
## 1080 631 1 0.9068 0.01101 0.8855 0.929
## 1081 630 1 0.9054 0.01109 0.8839 0.927
## 1082 629 1 0.9039 0.01116 0.8823 0.926
## 1083 628 1 0.9025 0.01124 0.8807 0.925
## 1085 626 1 0.9010 0.01131 0.8791 0.923
## 1086 625 1 0.8996 0.01138 0.8776 0.922
## 1087 624 1 0.8982 0.01146 0.8760 0.921
## 1088 623 1 0.8967 0.01153 0.8744 0.920
## 1089 622 1 0.8953 0.01160 0.8728 0.918
## 1090 621 1 0.8938 0.01167 0.8712 0.917
## 1091 620 1 0.8924 0.01174 0.8697 0.916
## 1092 619 1 0.8909 0.01181 0.8681 0.914
## 1094 618 1 0.8895 0.01188 0.8665 0.913
## 1095 617 1 0.8881 0.01195 0.8650 0.912
## 1096 616 1 0.8866 0.01201 0.8634 0.910
## 1097 615 1 0.8852 0.01208 0.8618 0.909
## 1099 614 1 0.8837 0.01215 0.8602 0.908
## 1100 613 1 0.8823 0.01221 0.8587 0.907
## 1101 612 1 0.8809 0.01228 0.8571 0.905
## 1102 611 1 0.8794 0.01234 0.8556 0.904
## 1103 610 1 0.8780 0.01240 0.8540 0.903
## 1104 609 1 0.8765 0.01247 0.8524 0.901
## 1106 607 1 0.8751 0.01253 0.8509 0.900
## 1107 606 1 0.8736 0.01259 0.8493 0.899
## 1108 605 1 0.8722 0.01265 0.8477 0.897
## 1109 604 1 0.8708 0.01271 0.8462 0.896
## 1110 603 1 0.8693 0.01278 0.8446 0.895
## 1111 602 1 0.8679 0.01284 0.8431 0.893
## 1113 601 1 0.8664 0.01290 0.8415 0.892
## 1115 599 1 0.8650 0.01295 0.8400 0.891
## 1116 598 1 0.8635 0.01301 0.8384 0.889
## 1117 597 1 0.8621 0.01307 0.8368 0.888
## 1118 596 1 0.8606 0.01313 0.8353 0.887
## 1119 595 1 0.8592 0.01319 0.8337 0.885
## 1120 594 1 0.8577 0.01324 0.8322 0.884
## 1122 592 1 0.8563 0.01330 0.8306 0.883
## 1123 591 1 0.8548 0.01336 0.8291 0.881
## 1124 590 1 0.8534 0.01341 0.8275 0.880
## 1125 589 1 0.8519 0.01347 0.8260 0.879
## 1126 588 1 0.8505 0.01352 0.8244 0.877
## 1127 587 1 0.8490 0.01358 0.8229 0.876
## 1130 585 1 0.8476 0.01363 0.8213 0.875
## 1131 584 1 0.8461 0.01368 0.8197 0.873
## 1132 583 1 0.8447 0.01374 0.8182 0.872
## 1133 582 1 0.8432 0.01379 0.8166 0.871
## 1135 581 1 0.8418 0.01384 0.8151 0.869
## 1136 580 1 0.8403 0.01390 0.8135 0.868
## 1138 578 1 0.8389 0.01395 0.8120 0.867
## 1139 577 1 0.8374 0.01400 0.8104 0.865
## 1140 576 1 0.8360 0.01405 0.8089 0.864
## 1141 575 1 0.8345 0.01410 0.8073 0.863
## 1142 574 1 0.8331 0.01415 0.8058 0.861
## 1143 573 1 0.8316 0.01420 0.8042 0.860
## 1145 572 1 0.8302 0.01425 0.8027 0.859
## 1146 571 1 0.8287 0.01430 0.8012 0.857
## 1147 570 1 0.8273 0.01435 0.7996 0.856
## 1148 569 1 0.8258 0.01440 0.7981 0.855
## 1149 568 1 0.8243 0.01444 0.7965 0.853
## 1150 567 1 0.8229 0.01449 0.7950 0.852
## 1151 566 1 0.8214 0.01454 0.7934 0.850
## 1152 565 1 0.8200 0.01458 0.7919 0.849
## 1153 564 1 0.8185 0.01463 0.7904 0.848
## 1154 563 1 0.8171 0.01468 0.7888 0.846
## 1157 560 1 0.8156 0.01472 0.7873 0.845
## 1159 558 1 0.8142 0.01477 0.7857 0.844
## 1160 557 1 0.8127 0.01481 0.7842 0.842
## 1161 556 1 0.8112 0.01486 0.7826 0.841
## 1162 555 1 0.8098 0.01491 0.7811 0.840
## 1163 554 1 0.8083 0.01495 0.7795 0.838
## 1164 553 1 0.8068 0.01499 0.7780 0.837
## 1165 552 1 0.8054 0.01504 0.7764 0.835
## 1166 551 1 0.8039 0.01508 0.7749 0.834
## 1167 550 1 0.8025 0.01512 0.7734 0.833
## 1168 549 1 0.8010 0.01517 0.7718 0.831
## 1169 548 1 0.7995 0.01521 0.7703 0.830
## 1170 547 1 0.7981 0.01525 0.7687 0.829
## 1171 546 1 0.7966 0.01529 0.7672 0.827
## 1172 545 1 0.7952 0.01534 0.7657 0.826
## 1173 544 1 0.7937 0.01538 0.7641 0.824
## 1174 543 1 0.7922 0.01542 0.7626 0.823
## 1176 542 1 0.7908 0.01546 0.7610 0.822
## 1177 541 1 0.7893 0.01550 0.7595 0.820
## 1179 539 1 0.7878 0.01554 0.7580 0.819
## 1180 538 1 0.7864 0.01558 0.7564 0.818
## 1181 537 1 0.7849 0.01562 0.7549 0.816
## 1182 536 1 0.7835 0.01566 0.7534 0.815
## 1183 535 1 0.7820 0.01570 0.7518 0.813
## 1184 534 1 0.7805 0.01574 0.7503 0.812
## 1185 533 1 0.7791 0.01577 0.7487 0.811
## 1186 532 1 0.7776 0.01581 0.7472 0.809
## 1187 531 1 0.7761 0.01585 0.7457 0.808
## 1189 530 1 0.7747 0.01589 0.7441 0.806
## 1190 529 1 0.7732 0.01593 0.7426 0.805
## 1191 528 1 0.7717 0.01596 0.7411 0.804
## 1193 527 1 0.7703 0.01600 0.7395 0.802
## 1194 526 1 0.7688 0.01604 0.7380 0.801
## 1195 525 1 0.7673 0.01607 0.7365 0.799
## 1196 524 1 0.7659 0.01611 0.7349 0.798
## 1203 517 1 0.7644 0.01615 0.7334 0.797
## 1204 516 1 0.7629 0.01618 0.7318 0.795
## 1205 515 1 0.7614 0.01622 0.7303 0.794
## 1206 514 1 0.7600 0.01625 0.7288 0.792
## 1207 513 1 0.7585 0.01629 0.7272 0.791
## 1208 512 1 0.7570 0.01632 0.7257 0.790
## 1209 511 1 0.7555 0.01636 0.7241 0.788
## 1211 510 1 0.7540 0.01639 0.7226 0.787
## 1212 509 1 0.7525 0.01643 0.7210 0.785
## 1213 508 1 0.7511 0.01646 0.7195 0.784
## 1214 507 1 0.7496 0.01650 0.7179 0.783
## 1217 505 1 0.7481 0.01653 0.7164 0.781
## 1218 504 1 0.7466 0.01657 0.7148 0.780
## 1219 503 1 0.7451 0.01660 0.7133 0.778
## 1220 502 1 0.7436 0.01663 0.7118 0.777
## 1221 501 1 0.7422 0.01666 0.7102 0.776
## 1222 500 1 0.7407 0.01670 0.7087 0.774
## 1223 499 1 0.7392 0.01673 0.7071 0.773
## 1227 495 1 0.7377 0.01676 0.7056 0.771
## 1228 494 1 0.7362 0.01680 0.7040 0.770
## 1229 493 1 0.7347 0.01683 0.7025 0.768
## 1230 492 1 0.7332 0.01686 0.7009 0.767
## 1231 491 1 0.7317 0.01689 0.6994 0.766
## 1233 489 1 0.7302 0.01692 0.6978 0.764
## 1234 488 1 0.7287 0.01695 0.6963 0.763
## 1235 487 1 0.7272 0.01698 0.6947 0.761
## 1236 486 1 0.7257 0.01702 0.6931 0.760
## 1237 485 1 0.7242 0.01705 0.6916 0.758
## 1241 481 1 0.7227 0.01708 0.6900 0.757
## 1242 480 1 0.7212 0.01711 0.6885 0.756
## 1243 479 1 0.7197 0.01714 0.6869 0.754
## 1244 478 1 0.7182 0.01717 0.6853 0.753
## 1245 477 1 0.7167 0.01720 0.6838 0.751
## 1246 476 1 0.7152 0.01723 0.6822 0.750
## 1247 475 1 0.7137 0.01726 0.6807 0.748
## 1248 474 1 0.7122 0.01729 0.6791 0.747
## 1249 473 1 0.7107 0.01732 0.6776 0.745
## 1250 472 1 0.7092 0.01734 0.6760 0.744
## 1252 470 1 0.7077 0.01737 0.6744 0.743
## 1253 469 1 0.7062 0.01740 0.6729 0.741
## 1254 468 1 0.7047 0.01743 0.6713 0.740
## 1255 467 1 0.7032 0.01746 0.6698 0.738
## 1256 466 1 0.7016 0.01748 0.6682 0.737
## 1257 465 1 0.7001 0.01751 0.6666 0.735
## 1258 464 1 0.6986 0.01754 0.6651 0.734
## 1260 463 1 0.6971 0.01757 0.6635 0.732
## 1261 462 1 0.6956 0.01759 0.6620 0.731
## 1262 461 1 0.6941 0.01762 0.6604 0.730
## 1270 453 1 0.6926 0.01765 0.6588 0.728
## 1272 452 1 0.6910 0.01767 0.6572 0.727
## 1273 451 1 0.6895 0.01770 0.6557 0.725
## 1274 450 1 0.6880 0.01773 0.6541 0.724
## 1275 449 1 0.6864 0.01775 0.6525 0.722
## 1276 448 1 0.6849 0.01778 0.6509 0.721
## 1277 447 1 0.6834 0.01781 0.6493 0.719
## 1278 446 1 0.6818 0.01783 0.6478 0.718
## 1279 445 1 0.6803 0.01786 0.6462 0.716
## 1280 444 1 0.6788 0.01788 0.6446 0.715
## 1281 443 1 0.6772 0.01791 0.6430 0.713
## 1282 442 1 0.6757 0.01793 0.6415 0.712
## 1283 441 1 0.6742 0.01796 0.6399 0.710
## 1284 440 1 0.6726 0.01798 0.6383 0.709
## 1285 439 1 0.6711 0.01801 0.6367 0.707
## 1286 438 1 0.6696 0.01803 0.6352 0.706
## 1287 437 1 0.6680 0.01806 0.6336 0.704
## 1290 434 1 0.6665 0.01808 0.6320 0.703
## 1291 433 1 0.6650 0.01810 0.6304 0.701
## 1292 432 1 0.6634 0.01813 0.6288 0.700
## 1293 431 1 0.6619 0.01815 0.6273 0.698
## 1294 430 1 0.6604 0.01817 0.6257 0.697
## 1295 429 1 0.6588 0.01820 0.6241 0.695
## 1296 428 1 0.6573 0.01822 0.6225 0.694
## 1297 427 1 0.6557 0.01824 0.6209 0.692
## 1298 426 1 0.6542 0.01826 0.6194 0.691
## 1299 425 1 0.6527 0.01828 0.6178 0.689
## 1300 424 1 0.6511 0.01831 0.6162 0.688
## 1302 423 1 0.6496 0.01833 0.6146 0.687
## 1303 422 1 0.6480 0.01835 0.6131 0.685
## 1304 421 1 0.6465 0.01837 0.6115 0.684
## 1305 420 1 0.6450 0.01839 0.6099 0.682
## 1306 419 1 0.6434 0.01841 0.6083 0.681
## 1308 418 1 0.6419 0.01843 0.6068 0.679
## 1309 417 1 0.6403 0.01845 0.6052 0.678
## 1316 411 1 0.6388 0.01847 0.6036 0.676
## 1317 410 1 0.6372 0.01849 0.6020 0.675
## 1319 409 1 0.6357 0.01851 0.6004 0.673
## 1320 408 1 0.6341 0.01853 0.5988 0.671
## 1321 407 1 0.6326 0.01855 0.5972 0.670
## 1322 406 1 0.6310 0.01857 0.5956 0.668
## 1324 405 1 0.6294 0.01859 0.5940 0.667
## 1325 404 1 0.6279 0.01861 0.5924 0.665
## 1326 403 1 0.6263 0.01863 0.5909 0.664
## 1327 402 1 0.6248 0.01865 0.5893 0.662
## 1328 401 1 0.6232 0.01867 0.5877 0.661
## 1329 400 1 0.6216 0.01868 0.5861 0.659
## 1330 399 1 0.6201 0.01870 0.5845 0.658
## 1331 398 1 0.6185 0.01872 0.5829 0.656
## 1333 397 1 0.6170 0.01874 0.5813 0.655
## 1335 396 1 0.6154 0.01875 0.5797 0.653
## 1336 395 1 0.6139 0.01877 0.5781 0.652
## 1337 394 1 0.6123 0.01879 0.5766 0.650
## 1349 383 1 0.6107 0.01881 0.5749 0.649
## 1350 382 1 0.6091 0.01883 0.5733 0.647
## 1351 381 1 0.6075 0.01884 0.5717 0.646
## 1352 380 1 0.6059 0.01886 0.5700 0.644
## 1353 379 1 0.6043 0.01888 0.5684 0.642
## 1354 378 1 0.6027 0.01890 0.5668 0.641
## 1355 377 1 0.6011 0.01892 0.5652 0.639
## 1356 376 1 0.5995 0.01893 0.5635 0.638
## 1357 375 1 0.5979 0.01895 0.5619 0.636
## 1358 374 1 0.5963 0.01897 0.5603 0.635
## 1359 373 1 0.5947 0.01898 0.5586 0.633
## 1360 372 1 0.5931 0.01900 0.5570 0.632
## 1361 371 1 0.5915 0.01901 0.5554 0.630
## 1362 370 1 0.5899 0.01903 0.5538 0.628
## 1363 369 1 0.5883 0.01905 0.5521 0.627
## 1364 368 1 0.5867 0.01906 0.5505 0.625
## 1365 367 1 0.5851 0.01908 0.5489 0.624
## 1366 366 1 0.5835 0.01909 0.5473 0.622
## 1367 365 1 0.5819 0.01911 0.5457 0.621
## 1368 364 1 0.5803 0.01912 0.5440 0.619
## 1379 354 1 0.5787 0.01914 0.5424 0.617
## 1380 353 1 0.5770 0.01915 0.5407 0.616
## 1381 352 1 0.5754 0.01917 0.5390 0.614
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## 1387 346 1 0.5672 0.01924 0.5307 0.606
## 1388 345 1 0.5656 0.01926 0.5290 0.605
## 1389 344 1 0.5639 0.01927 0.5274 0.603
## 1390 343 1 0.5623 0.01928 0.5257 0.601
## 1391 342 1 0.5606 0.01930 0.5240 0.600
## 1392 341 1 0.5590 0.01931 0.5224 0.598
## 1393 340 1 0.5573 0.01932 0.5207 0.597
## 1394 339 1 0.5557 0.01934 0.5191 0.595
## 1405 328 1 0.5540 0.01935 0.5173 0.593
## 1406 327 1 0.5523 0.01937 0.5156 0.592
## 1407 326 1 0.5506 0.01938 0.5139 0.590
## 1408 325 1 0.5489 0.01940 0.5122 0.588
## 1409 324 1 0.5472 0.01941 0.5105 0.587
## 1410 323 1 0.5455 0.01942 0.5088 0.585
## 1411 322 1 0.5438 0.01944 0.5070 0.583
## 1412 321 1 0.5421 0.01945 0.5053 0.582
## 1413 320 1 0.5404 0.01946 0.5036 0.580
## 1414 319 1 0.5388 0.01948 0.5019 0.578
## 1416 318 1 0.5371 0.01949 0.5002 0.577
## 1417 317 1 0.5354 0.01950 0.4985 0.575
## 1418 316 1 0.5337 0.01951 0.4968 0.573
## 1419 315 1 0.5320 0.01952 0.4951 0.572
## 1420 314 1 0.5303 0.01953 0.4933 0.570
## 1421 313 1 0.5286 0.01955 0.4916 0.568
## 1422 312 1 0.5269 0.01956 0.4899 0.567
## 1436 302 1 0.5251 0.01957 0.4882 0.565
## 1437 301 1 0.5234 0.01958 0.4864 0.563
## 1438 300 1 0.5217 0.01959 0.4846 0.562
## 1440 299 1 0.5199 0.01961 0.4829 0.560
## 1441 298 1 0.5182 0.01962 0.4811 0.558
## 1442 297 1 0.5164 0.01963 0.4793 0.556
## 1444 295 1 0.5147 0.01964 0.4776 0.555
## 1445 294 1 0.5129 0.01965 0.4758 0.553
## 1447 293 1 0.5112 0.01966 0.4741 0.551
## 1448 292 1 0.5094 0.01967 0.4723 0.549
## 1454 286 1 0.5076 0.01968 0.4705 0.548
## 1455 285 1 0.5059 0.01970 0.4687 0.546
## 1456 284 1 0.5041 0.01971 0.4669 0.544
## 1457 283 1 0.5023 0.01972 0.4651 0.542
## 1458 282 1 0.5005 0.01973 0.4633 0.541
## 1459 281 1 0.4987 0.01974 0.4615 0.539
## 1460 280 1 0.4970 0.01975 0.4597 0.537
## 1462 279 1 0.4952 0.01976 0.4579 0.535
## 1463 278 1 0.4934 0.01977 0.4561 0.534
## 1464 277 1 0.4916 0.01977 0.4543 0.532
## 1465 276 1 0.4898 0.01978 0.4525 0.530
## 1466 275 1 0.4880 0.01979 0.4508 0.528
## 1467 274 1 0.4863 0.01980 0.4490 0.527
## 1468 273 1 0.4845 0.01981 0.4472 0.525
## 1469 272 1 0.4827 0.01981 0.4454 0.523
## 1470 271 1 0.4809 0.01982 0.4436 0.521
## 1471 270 1 0.4791 0.01983 0.4418 0.520
## 1485 258 1 0.4773 0.01984 0.4399 0.518
## 1486 257 1 0.4754 0.01985 0.4381 0.516
## 1487 256 1 0.4736 0.01986 0.4362 0.514
## 1488 255 1 0.4717 0.01986 0.4343 0.512
## 1489 254 1 0.4699 0.01987 0.4325 0.510
## 1490 253 1 0.4680 0.01988 0.4306 0.509
## 1491 252 1 0.4661 0.01989 0.4287 0.507
## 1492 251 1 0.4643 0.01990 0.4269 0.505
## 1493 250 1 0.4624 0.01990 0.4250 0.503
## 1494 249 1 0.4606 0.01991 0.4232 0.501
## 1495 248 1 0.4587 0.01991 0.4213 0.499
## 1496 247 1 0.4569 0.01992 0.4194 0.498
## 1506 237 1 0.4549 0.01993 0.4175 0.496
## 1509 235 1 0.4530 0.01994 0.4156 0.494
## 1511 234 1 0.4511 0.01995 0.4136 0.492
## 1512 233 1 0.4491 0.01996 0.4117 0.490
## 1513 232 1 0.4472 0.01996 0.4097 0.488
## 1521 225 1 0.4452 0.01997 0.4077 0.486
## 1522 224 1 0.4432 0.01998 0.4057 0.484
## 1523 223 1 0.4412 0.01999 0.4037 0.482
## 1524 222 1 0.4392 0.02000 0.4017 0.480
## 1526 221 1 0.4372 0.02001 0.3997 0.478
## 1527 220 1 0.4353 0.02002 0.3977 0.476
## 1528 219 1 0.4333 0.02002 0.3958 0.474
## 1530 218 1 0.4313 0.02003 0.3938 0.472
## 1531 217 1 0.4293 0.02004 0.3918 0.470
## 1532 216 1 0.4273 0.02004 0.3898 0.468
## 1533 215 1 0.4253 0.02005 0.3878 0.466
## 1535 214 1 0.4233 0.02005 0.3858 0.465
## 1536 213 1 0.4213 0.02005 0.3838 0.463
## 1537 212 1 0.4194 0.02006 0.3818 0.461
## 1538 211 1 0.4174 0.02006 0.3798 0.459
## 1539 210 1 0.4154 0.02006 0.3779 0.457
## 1540 209 1 0.4134 0.02007 0.3759 0.455
## 1541 208 1 0.4114 0.02007 0.3739 0.453
## 1542 207 1 0.4094 0.02007 0.3719 0.451
## 1550 200 1 0.4074 0.02007 0.3699 0.449
## 1551 199 1 0.4053 0.02008 0.3678 0.447
## 1552 198 1 0.4033 0.02008 0.3658 0.445
## 1553 197 1 0.4012 0.02008 0.3637 0.443
## 1555 196 1 0.3992 0.02008 0.3617 0.441
## 1556 195 1 0.3971 0.02008 0.3597 0.439
## 1557 194 1 0.3951 0.02008 0.3576 0.436
## 1558 193 1 0.3930 0.02008 0.3556 0.434
## 1559 192 1 0.3910 0.02008 0.3536 0.432
## 1560 191 1 0.3890 0.02008 0.3515 0.430
## 1576 175 1 0.3867 0.02009 0.3493 0.428
## 1577 174 1 0.3845 0.02010 0.3471 0.426
## 1578 173 1 0.3823 0.02010 0.3448 0.424
## 1579 172 1 0.3801 0.02011 0.3426 0.422
## 1580 171 1 0.3778 0.02011 0.3404 0.419
## 1581 170 1 0.3756 0.02012 0.3382 0.417
## 1594 159 1 0.3733 0.02013 0.3358 0.415
## 1595 158 1 0.3709 0.02014 0.3334 0.413
## 1596 157 1 0.3685 0.02015 0.3311 0.410
## 1597 156 1 0.3662 0.02016 0.3287 0.408
## 1598 155 1 0.3638 0.02017 0.3263 0.406
## 1599 154 1 0.3614 0.02017 0.3240 0.403
## 1600 153 1 0.3591 0.02018 0.3216 0.401
## 1601 152 1 0.3567 0.02019 0.3193 0.399
## 1602 151 1 0.3544 0.02019 0.3169 0.396
## 1610 144 1 0.3519 0.02020 0.3145 0.394
## 1611 143 1 0.3494 0.02021 0.3120 0.391
## 1612 142 1 0.3470 0.02021 0.3095 0.389
## 1613 141 1 0.3445 0.02022 0.3071 0.387
## 1614 140 1 0.3420 0.02022 0.3046 0.384
## 1615 139 1 0.3396 0.02023 0.3022 0.382
## 1616 138 1 0.3371 0.02023 0.2997 0.379
## 1617 137 1 0.3347 0.02023 0.2973 0.377
## 1618 136 1 0.3322 0.02023 0.2948 0.374
## 1630 127 1 0.3296 0.02024 0.2922 0.372
## 1631 126 1 0.3270 0.02025 0.2896 0.369
## 1633 124 1 0.3243 0.02026 0.2870 0.367
## 1634 123 1 0.3217 0.02026 0.2843 0.364
## 1635 122 1 0.3191 0.02027 0.2817 0.361
## 1644 113 1 0.3162 0.02028 0.2789 0.359
## 1645 112 1 0.3134 0.02030 0.2761 0.356
## 1646 111 1 0.3106 0.02031 0.2732 0.353
## 1647 110 1 0.3078 0.02032 0.2704 0.350
## 1648 109 1 0.3049 0.02033 0.2676 0.348
## 1658 99 1 0.3019 0.02036 0.2645 0.345
## 1659 98 1 0.2988 0.02038 0.2614 0.342
## 1660 97 1 0.2957 0.02040 0.2583 0.339
## 1661 96 1 0.2926 0.02042 0.2552 0.336
## 1662 95 1 0.2895 0.02044 0.2521 0.333
## 1663 94 1 0.2865 0.02045 0.2491 0.329
## 1670 88 1 0.2832 0.02048 0.2458 0.326
## 1671 87 1 0.2800 0.02050 0.2425 0.323
## 1672 86 1 0.2767 0.02052 0.2393 0.320
## 1673 85 1 0.2734 0.02053 0.2360 0.317
## 1674 84 1 0.2702 0.02054 0.2328 0.314
## 1681 77 1 0.2667 0.02057 0.2293 0.310
## 1682 76 1 0.2632 0.02060 0.2257 0.307
## 1683 75 1 0.2597 0.02062 0.2222 0.303
## 1684 74 1 0.2562 0.02064 0.2187 0.300
## 1685 73 1 0.2526 0.02065 0.2152 0.297
## 1693 65 1 0.2488 0.02070 0.2113 0.293
## 1694 64 1 0.2449 0.02074 0.2074 0.289
## 1695 63 1 0.2410 0.02077 0.2035 0.285
## 1697 61 1 0.2370 0.02080 0.1996 0.282
## 1698 60 1 0.2331 0.02083 0.1956 0.278
## 1705 55 1 0.2288 0.02087 0.1914 0.274
## 1706 54 1 0.2246 0.02091 0.1871 0.270
## 1709 52 1 0.2203 0.02095 0.1828 0.265
## 1710 51 1 0.2160 0.02098 0.1785 0.261
## 1713 48 1 0.2115 0.02102 0.1740 0.257
## 1714 47 1 0.2070 0.02105 0.1696 0.253
## 1715 46 1 0.2025 0.02107 0.1651 0.248
## 1716 45 1 0.1980 0.02107 0.1607 0.244
## 1724 37 1 0.1926 0.02117 0.1553 0.239
## 1725 36 1 0.1873 0.02125 0.1499 0.234
## 1727 34 1 0.1818 0.02133 0.1444 0.229
## 1728 33 1 0.1763 0.02138 0.1390 0.224
## 1737 25 1 0.1692 0.02166 0.1317 0.217
## 1739 24 1 0.1622 0.02187 0.1245 0.211
## 1743 20 1 0.1540 0.02223 0.1161 0.204
## 1749 15 1 0.1438 0.02300 0.1051 0.197
## 1750 14 1 0.1335 0.02354 0.0945 0.189
## 1754 10 1 0.1202 0.02468 0.0803 0.180
## 1755 9 1 0.1068 0.02529 0.0671 0.170
## 1756 8 1 0.0935 0.02541 0.0548 0.159Top 701 - 701 people were at risk for experiencing voluntary turnover during that interval, n.event is the amount of people who experienced it survival is the cumulative survival rate of people who survived through the event 95% CI SE
Summarize the KMA results by pre-specified Time intervals Create life table: This says show the first 30 days, second set of 30 days, then thid set of 30 days, then 90 days 30 times.
summary(km_fit1, times=c(30, 60, 90*(1:30)))## Call: survfit(formula = Surv(LOS, censored) ~ 1, data = survive, type = "kaplan-meier")
##
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 30 701 0 1.000 0.0000 1.000 1.000
## 60 701 0 1.000 0.0000 1.000 1.000
## 90 701 0 1.000 0.0000 1.000 1.000
## 180 701 0 1.000 0.0000 1.000 1.000
## 270 701 0 1.000 0.0000 1.000 1.000
## 360 701 0 1.000 0.0000 1.000 1.000
## 450 701 0 1.000 0.0000 1.000 1.000
## 540 701 0 1.000 0.0000 1.000 1.000
## 630 701 0 1.000 0.0000 1.000 1.000
## 720 701 0 1.000 0.0000 1.000 1.000
## 810 701 0 1.000 0.0000 1.000 1.000
## 900 701 0 1.000 0.0000 1.000 1.000
## 990 701 0 1.000 0.0000 1.000 1.000
## 1080 631 65 0.907 0.0110 0.885 0.929
## 1170 547 75 0.798 0.0153 0.769 0.829
## 1260 463 68 0.697 0.0176 0.664 0.732
## 1350 382 57 0.609 0.0188 0.573 0.647
## 1440 299 54 0.520 0.0196 0.483 0.560
## 1530 218 48 0.431 0.0200 0.394 0.472
## 1620 135 45 0.332 0.0202 0.295 0.374
## 1710 51 35 0.216 0.0210 0.179 0.261plot cumulative survival rates
library(survminer)
plot(km_fit1)
Now we’ll just make that look less ugly
ggsurvplot(km_fit1, data=survive, risk.table=TRUE, conf.int=TRUE,
ggtheme=theme_minimal())
Now in defining the next KM we’ll rope in an additional variable (race) which will break up the groups in the KMA chart
#Define next KM
km_fit2 <- survfit(Surv(LOS, censored) ~ Race,
data=survive,
type="kaplan-meier")
summary(km_fit2)## Call: survfit(formula = Surv(LOS, censored) ~ Race, data = survive,
## type = "kaplan-meier")
##
## Race=Black
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 1001 283 1 0.9965 0.00353 0.9896 1.000
## 1007 282 1 0.9929 0.00498 0.9832 1.000
## 1008 281 1 0.9894 0.00609 0.9775 1.000
## 1012 280 1 0.9859 0.00702 0.9722 1.000
## 1016 279 1 0.9823 0.00783 0.9671 0.998
## 1018 278 1 0.9788 0.00856 0.9622 0.996
## 1020 277 1 0.9753 0.00923 0.9573 0.994
## 1021 276 1 0.9717 0.00985 0.9526 0.991
## 1024 275 1 0.9682 0.01043 0.9480 0.989
## 1027 273 1 0.9647 0.01098 0.9434 0.986
## 1028 272 1 0.9611 0.01150 0.9388 0.984
## 1033 271 1 0.9576 0.01199 0.9343 0.981
## 1036 270 1 0.9540 0.01246 0.9299 0.979
## 1044 269 1 0.9505 0.01291 0.9255 0.976
## 1045 268 1 0.9469 0.01334 0.9211 0.973
## 1047 267 1 0.9434 0.01375 0.9168 0.971
## 1049 266 1 0.9398 0.01415 0.9125 0.968
## 1053 265 1 0.9363 0.01453 0.9082 0.965
## 1057 264 1 0.9327 0.01490 0.9040 0.962
## 1062 262 1 0.9292 0.01527 0.8997 0.960
## 1063 261 1 0.9256 0.01562 0.8955 0.957
## 1064 260 1 0.9221 0.01596 0.8913 0.954
## 1068 259 1 0.9185 0.01629 0.8871 0.951
## 1069 258 1 0.9149 0.01661 0.8829 0.948
## 1071 257 1 0.9114 0.01692 0.8788 0.945
## 1073 256 1 0.9078 0.01723 0.8747 0.942
## 1074 255 1 0.9043 0.01752 0.8706 0.939
## 1075 254 1 0.9007 0.01781 0.8664 0.936
## 1079 253 1 0.8971 0.01809 0.8624 0.933
## 1080 252 1 0.8936 0.01837 0.8583 0.930
## 1082 251 1 0.8900 0.01864 0.8542 0.927
## 1089 250 1 0.8865 0.01890 0.8502 0.924
## 1095 249 1 0.8829 0.01916 0.8461 0.921
## 1096 248 1 0.8793 0.01941 0.8421 0.918
## 1100 247 1 0.8758 0.01965 0.8381 0.915
## 1101 246 1 0.8722 0.01989 0.8341 0.912
## 1102 245 1 0.8687 0.02013 0.8301 0.909
## 1103 244 1 0.8651 0.02036 0.8261 0.906
## 1106 243 1 0.8615 0.02058 0.8221 0.903
## 1108 242 1 0.8580 0.02080 0.8182 0.900
## 1109 241 1 0.8544 0.02102 0.8142 0.897
## 1117 240 1 0.8509 0.02123 0.8102 0.893
## 1118 239 1 0.8473 0.02144 0.8063 0.890
## 1119 238 1 0.8437 0.02164 0.8024 0.887
## 1122 237 1 0.8402 0.02184 0.7984 0.884
## 1125 236 1 0.8366 0.02204 0.7945 0.881
## 1126 235 1 0.8331 0.02223 0.7906 0.878
## 1130 234 1 0.8295 0.02242 0.7867 0.875
## 1142 232 1 0.8259 0.02260 0.7828 0.871
## 1143 231 1 0.8223 0.02279 0.7789 0.868
## 1146 230 1 0.8188 0.02297 0.7750 0.865
## 1149 229 1 0.8152 0.02314 0.7711 0.862
## 1152 228 1 0.8116 0.02332 0.7672 0.859
## 1153 227 1 0.8080 0.02349 0.7633 0.855
## 1163 225 1 0.8044 0.02366 0.7594 0.852
## 1173 224 1 0.8009 0.02382 0.7555 0.849
## 1180 223 1 0.7973 0.02398 0.7516 0.846
## 1186 222 1 0.7937 0.02414 0.7477 0.842
## 1190 221 1 0.7901 0.02430 0.7439 0.839
## 1191 220 1 0.7865 0.02445 0.7400 0.836
## 1205 218 1 0.7829 0.02460 0.7361 0.833
## 1213 217 1 0.7793 0.02475 0.7322 0.829
## 1214 216 1 0.7757 0.02490 0.7284 0.826
## 1217 215 1 0.7721 0.02505 0.7245 0.823
## 1218 214 1 0.7685 0.02519 0.7206 0.819
## 1219 213 1 0.7648 0.02533 0.7168 0.816
## 1223 212 1 0.7612 0.02546 0.7129 0.813
## 1227 211 1 0.7576 0.02560 0.7091 0.809
## 1230 210 1 0.7540 0.02573 0.7052 0.806
## 1231 209 1 0.7504 0.02586 0.7014 0.803
## 1233 207 1 0.7468 0.02598 0.6976 0.799
## 1235 206 1 0.7432 0.02611 0.6937 0.796
## 1244 203 1 0.7395 0.02624 0.6898 0.793
## 1246 202 1 0.7358 0.02636 0.6859 0.789
## 1249 201 1 0.7322 0.02648 0.6821 0.786
## 1252 199 1 0.7285 0.02660 0.6782 0.783
## 1254 198 1 0.7248 0.02672 0.6743 0.779
## 1255 197 1 0.7211 0.02684 0.6704 0.776
## 1256 196 1 0.7175 0.02695 0.6665 0.772
## 1260 195 1 0.7138 0.02706 0.6627 0.769
## 1262 194 1 0.7101 0.02717 0.6588 0.765
## 1276 189 1 0.7063 0.02729 0.6548 0.762
## 1278 188 1 0.7026 0.02740 0.6509 0.758
## 1281 187 1 0.6988 0.02751 0.6469 0.755
## 1282 186 1 0.6951 0.02762 0.6430 0.751
## 1286 185 1 0.6913 0.02772 0.6391 0.748
## 1292 182 1 0.6875 0.02783 0.6351 0.744
## 1293 181 1 0.6837 0.02793 0.6311 0.741
## 1294 180 1 0.6799 0.02804 0.6271 0.737
## 1299 179 1 0.6761 0.02814 0.6232 0.734
## 1302 178 1 0.6723 0.02823 0.6192 0.730
## 1303 177 1 0.6685 0.02833 0.6153 0.726
## 1305 176 1 0.6647 0.02842 0.6113 0.723
## 1306 175 1 0.6609 0.02851 0.6073 0.719
## 1316 173 1 0.6571 0.02860 0.6034 0.716
## 1317 172 1 0.6533 0.02869 0.5994 0.712
## 1320 171 1 0.6495 0.02877 0.5955 0.708
## 1322 170 1 0.6456 0.02886 0.5915 0.705
## 1329 169 1 0.6418 0.02894 0.5875 0.701
## 1330 168 1 0.6380 0.02902 0.5836 0.697
## 1349 163 1 0.6341 0.02910 0.5795 0.694
## 1350 162 1 0.6302 0.02918 0.5755 0.690
## 1358 161 1 0.6263 0.02926 0.5715 0.686
## 1360 160 1 0.6224 0.02934 0.5674 0.683
## 1361 159 1 0.6184 0.02942 0.5634 0.679
## 1364 158 1 0.6145 0.02949 0.5594 0.675
## 1366 157 1 0.6106 0.02956 0.5553 0.671
## 1367 156 1 0.6067 0.02963 0.5513 0.668
## 1379 151 1 0.6027 0.02970 0.5472 0.664
## 1386 149 1 0.5986 0.02978 0.5430 0.660
## 1388 148 1 0.5946 0.02985 0.5389 0.656
## 1389 147 1 0.5905 0.02992 0.5347 0.652
## 1391 146 1 0.5865 0.02999 0.5306 0.648
## 1394 145 1 0.5825 0.03005 0.5264 0.644
## 1405 141 1 0.5783 0.03012 0.5222 0.640
## 1407 140 1 0.5742 0.03019 0.5180 0.637
## 1413 139 1 0.5701 0.03025 0.5137 0.633
## 1414 138 1 0.5659 0.03031 0.5095 0.629
## 1420 137 1 0.5618 0.03037 0.5053 0.625
## 1421 136 1 0.5577 0.03043 0.5011 0.621
## 1422 135 1 0.5535 0.03048 0.4969 0.617
## 1441 129 1 0.5492 0.03055 0.4925 0.613
## 1442 128 1 0.5450 0.03061 0.4881 0.608
## 1445 126 1 0.5406 0.03067 0.4837 0.604
## 1447 125 1 0.5363 0.03073 0.4793 0.600
## 1448 124 1 0.5320 0.03078 0.4749 0.596
## 1454 122 1 0.5276 0.03084 0.4705 0.592
## 1456 121 1 0.5233 0.03089 0.4661 0.587
## 1466 120 1 0.5189 0.03094 0.4617 0.583
## 1467 119 1 0.5145 0.03098 0.4573 0.579
## 1469 118 1 0.5102 0.03103 0.4528 0.575
## 1486 113 1 0.5057 0.03108 0.4483 0.570
## 1488 112 1 0.5011 0.03113 0.4437 0.566
## 1489 111 1 0.4966 0.03117 0.4391 0.562
## 1490 110 1 0.4921 0.03122 0.4346 0.557
## 1491 109 1 0.4876 0.03125 0.4300 0.553
## 1493 108 1 0.4831 0.03129 0.4255 0.548
## 1494 107 1 0.4786 0.03132 0.4210 0.544
## 1495 106 1 0.4741 0.03135 0.4164 0.540
## 1506 102 1 0.4694 0.03138 0.4118 0.535
## 1509 101 1 0.4648 0.03142 0.4071 0.531
## 1512 100 1 0.4601 0.03144 0.4024 0.526
## 1513 99 1 0.4555 0.03147 0.3978 0.522
## 1521 97 1 0.4508 0.03149 0.3931 0.517
## 1526 96 1 0.4461 0.03151 0.3884 0.512
## 1530 95 1 0.4414 0.03153 0.3837 0.508
## 1531 94 1 0.4367 0.03154 0.3790 0.503
## 1536 93 1 0.4320 0.03155 0.3744 0.498
## 1537 92 1 0.4273 0.03155 0.3697 0.494
## 1538 91 1 0.4226 0.03155 0.3651 0.489
## 1541 90 1 0.4179 0.03155 0.3604 0.485
## 1542 89 1 0.4132 0.03154 0.3558 0.480
## 1551 84 1 0.4083 0.03155 0.3509 0.475
## 1553 83 1 0.4034 0.03155 0.3460 0.470
## 1555 82 1 0.3985 0.03155 0.3412 0.465
## 1557 81 1 0.3935 0.03154 0.3363 0.460
## 1577 77 1 0.3884 0.03154 0.3313 0.455
## 1597 73 1 0.3831 0.03155 0.3260 0.450
## 1598 72 1 0.3778 0.03156 0.3207 0.445
## 1617 69 1 0.3723 0.03157 0.3153 0.440
## 1618 68 1 0.3668 0.03158 0.3099 0.434
## 1634 64 1 0.3611 0.03160 0.3042 0.429
## 1635 63 1 0.3554 0.03162 0.2985 0.423
## 1644 59 1 0.3493 0.03165 0.2925 0.417
## 1658 53 1 0.3428 0.03173 0.2859 0.411
## 1660 52 1 0.3362 0.03180 0.2793 0.405
## 1661 51 1 0.3296 0.03185 0.2727 0.398
## 1662 50 1 0.3230 0.03189 0.2662 0.392
## 1663 49 1 0.3164 0.03191 0.2596 0.386
## 1670 44 1 0.3092 0.03199 0.2524 0.379
## 1671 43 1 0.3020 0.03204 0.2453 0.372
## 1672 42 1 0.2948 0.03207 0.2382 0.365
## 1674 41 1 0.2876 0.03209 0.2311 0.358
## 1682 36 1 0.2796 0.03218 0.2232 0.350
## 1684 35 1 0.2716 0.03223 0.2153 0.343
## 1694 31 1 0.2629 0.03236 0.2065 0.335
## 1695 30 1 0.2541 0.03245 0.1979 0.326
## 1698 28 1 0.2450 0.03253 0.1889 0.318
## 1705 25 1 0.2352 0.03268 0.1792 0.309
## 1706 24 1 0.2254 0.03275 0.1696 0.300
## 1710 22 1 0.2152 0.03283 0.1596 0.290
## 1713 21 1 0.2049 0.03282 0.1497 0.281
## 1715 20 1 0.1947 0.03274 0.1400 0.271
## 1725 17 1 0.1832 0.03276 0.1291 0.260
## 1737 14 1 0.1702 0.03293 0.1164 0.249
## 1743 12 1 0.1560 0.03310 0.1029 0.236
## 1749 11 1 0.1418 0.03299 0.0899 0.224
## 1750 10 1 0.1276 0.03259 0.0774 0.211
## 1755 7 1 0.1094 0.03264 0.0609 0.196
## 1756 6 1 0.0912 0.03189 0.0459 0.181
##
## Race=HispanicLatino
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 1031 79 1 0.987 0.0126 0.9630 1.000
## 1034 78 1 0.975 0.0177 0.9407 1.000
## 1039 77 1 0.962 0.0215 0.9208 1.000
## 1061 76 1 0.949 0.0247 0.9022 0.999
## 1085 75 1 0.937 0.0274 0.8845 0.992
## 1087 74 1 0.924 0.0298 0.8674 0.984
## 1097 73 1 0.911 0.0320 0.8508 0.976
## 1115 72 1 0.899 0.0339 0.8346 0.968
## 1120 71 1 0.886 0.0357 0.8187 0.959
## 1127 70 1 0.873 0.0374 0.8031 0.950
## 1132 69 1 0.861 0.0390 0.7877 0.941
## 1135 68 1 0.848 0.0404 0.7725 0.931
## 1136 67 1 0.835 0.0417 0.7576 0.921
## 1145 66 1 0.823 0.0430 0.7427 0.911
## 1166 65 1 0.810 0.0441 0.7281 0.901
## 1167 64 1 0.797 0.0452 0.7136 0.891
## 1168 63 1 0.785 0.0462 0.6992 0.881
## 1170 62 1 0.772 0.0472 0.6850 0.870
## 1181 61 1 0.759 0.0481 0.6709 0.860
## 1183 60 1 0.747 0.0489 0.6569 0.849
## 1184 59 1 0.734 0.0497 0.6429 0.838
## 1185 58 1 0.722 0.0504 0.6291 0.827
## 1203 57 1 0.709 0.0511 0.6154 0.816
## 1208 56 1 0.696 0.0517 0.6018 0.805
## 1209 55 1 0.684 0.0523 0.5883 0.794
## 1229 54 1 0.671 0.0529 0.5749 0.783
## 1257 53 1 0.658 0.0534 0.5615 0.772
## 1270 52 1 0.646 0.0538 0.5483 0.760
## 1283 51 1 0.633 0.0542 0.5351 0.749
## 1285 50 1 0.620 0.0546 0.5220 0.737
## 1287 49 1 0.608 0.0549 0.5089 0.725
## 1328 46 1 0.594 0.0553 0.4953 0.713
## 1335 45 1 0.581 0.0556 0.4818 0.701
## 1353 43 1 0.568 0.0560 0.4679 0.689
## 1362 42 1 0.554 0.0562 0.4542 0.676
## 1380 41 1 0.541 0.0565 0.4406 0.663
## 1382 40 1 0.527 0.0566 0.4270 0.651
## 1390 39 1 0.514 0.0568 0.4135 0.638
## 1410 38 1 0.500 0.0569 0.4002 0.625
## 1440 34 1 0.485 0.0571 0.3855 0.611
## 1462 33 1 0.471 0.0572 0.3709 0.597
## 1464 32 1 0.456 0.0573 0.3564 0.583
## 1470 31 1 0.441 0.0573 0.3421 0.569
## 1485 26 1 0.424 0.0575 0.3252 0.553
## 1522 22 1 0.405 0.0581 0.3058 0.536
## 1533 21 1 0.386 0.0584 0.2866 0.519
## 1558 20 1 0.366 0.0586 0.2678 0.501
## 1595 17 1 0.345 0.0590 0.2466 0.482
## 1610 15 1 0.322 0.0594 0.2242 0.462
## 1615 14 1 0.299 0.0594 0.2025 0.441
## 1616 13 1 0.276 0.0591 0.1813 0.420
## 1631 12 1 0.253 0.0585 0.1607 0.398
## 1646 10 1 0.228 0.0579 0.1383 0.375
## 1647 9 1 0.202 0.0567 0.1168 0.350
## 1709 6 1 0.169 0.0564 0.0875 0.325
## 1714 4 1 0.126 0.0559 0.0532 0.301
## 1754 1 1 0.000 NaN NA NA
##
## Race=White
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 1003 338 1 0.997 0.00295 0.991 1.000
## 1004 337 1 0.994 0.00417 0.986 1.000
## 1005 336 1 0.991 0.00510 0.981 1.000
## 1006 335 1 0.988 0.00588 0.977 1.000
## 1009 334 1 0.985 0.00657 0.972 0.998
## 1010 333 1 0.982 0.00718 0.968 0.996
## 1022 331 1 0.979 0.00775 0.964 0.995
## 1023 330 1 0.976 0.00827 0.960 0.993
## 1025 329 1 0.973 0.00877 0.956 0.991
## 1029 328 1 0.970 0.00923 0.952 0.989
## 1030 327 1 0.967 0.00966 0.949 0.987
## 1032 326 1 0.964 0.01008 0.945 0.984
## 1035 325 1 0.961 0.01048 0.941 0.982
## 1037 324 1 0.959 0.01086 0.937 0.980
## 1038 323 1 0.956 0.01122 0.934 0.978
## 1040 322 1 0.953 0.01157 0.930 0.976
## 1041 321 1 0.950 0.01191 0.927 0.973
## 1042 320 1 0.947 0.01224 0.923 0.971
## 1046 318 1 0.944 0.01256 0.919 0.969
## 1052 317 1 0.941 0.01286 0.916 0.966
## 1054 316 1 0.938 0.01316 0.912 0.964
## 1055 315 1 0.935 0.01345 0.909 0.961
## 1056 314 1 0.932 0.01374 0.905 0.959
## 1058 313 1 0.929 0.01401 0.902 0.957
## 1059 312 1 0.926 0.01428 0.898 0.954
## 1066 310 1 0.923 0.01454 0.895 0.952
## 1067 309 1 0.920 0.01480 0.891 0.949
## 1070 308 1 0.917 0.01505 0.888 0.947
## 1072 307 1 0.914 0.01529 0.884 0.944
## 1077 306 1 0.911 0.01553 0.881 0.942
## 1078 305 1 0.908 0.01577 0.878 0.939
## 1081 304 1 0.905 0.01599 0.874 0.937
## 1083 303 1 0.902 0.01622 0.871 0.934
## 1086 301 1 0.899 0.01644 0.867 0.932
## 1088 300 1 0.896 0.01665 0.864 0.929
## 1090 299 1 0.893 0.01687 0.860 0.927
## 1091 298 1 0.890 0.01707 0.857 0.924
## 1092 297 1 0.887 0.01728 0.854 0.921
## 1094 296 1 0.884 0.01748 0.850 0.919
## 1099 295 1 0.881 0.01767 0.847 0.916
## 1104 294 1 0.878 0.01786 0.844 0.914
## 1107 292 1 0.875 0.01805 0.840 0.911
## 1110 291 1 0.872 0.01824 0.837 0.908
## 1111 290 1 0.869 0.01842 0.834 0.906
## 1113 289 1 0.866 0.01860 0.830 0.903
## 1116 287 1 0.863 0.01878 0.827 0.901
## 1123 285 1 0.860 0.01896 0.823 0.898
## 1124 284 1 0.857 0.01913 0.820 0.895
## 1131 282 1 0.854 0.01930 0.817 0.892
## 1133 281 1 0.851 0.01947 0.813 0.890
## 1138 280 1 0.848 0.01964 0.810 0.887
## 1139 279 1 0.845 0.01980 0.807 0.884
## 1140 278 1 0.842 0.01996 0.803 0.882
## 1141 277 1 0.839 0.02012 0.800 0.879
## 1147 276 1 0.836 0.02028 0.797 0.876
## 1148 275 1 0.833 0.02043 0.793 0.874
## 1150 274 1 0.829 0.02058 0.790 0.871
## 1151 273 1 0.826 0.02073 0.787 0.868
## 1154 272 1 0.823 0.02087 0.784 0.865
## 1157 269 1 0.820 0.02102 0.780 0.863
## 1159 268 1 0.817 0.02116 0.777 0.860
## 1160 267 1 0.814 0.02130 0.774 0.857
## 1161 266 1 0.811 0.02144 0.770 0.854
## 1162 265 1 0.808 0.02158 0.767 0.852
## 1164 264 1 0.805 0.02171 0.764 0.849
## 1165 263 1 0.802 0.02184 0.760 0.846
## 1169 262 1 0.799 0.02197 0.757 0.843
## 1171 261 1 0.796 0.02210 0.754 0.840
## 1172 260 1 0.793 0.02223 0.750 0.838
## 1174 259 1 0.790 0.02235 0.747 0.835
## 1176 258 1 0.787 0.02247 0.744 0.832
## 1177 257 1 0.784 0.02259 0.741 0.829
## 1179 255 1 0.781 0.02271 0.737 0.826
## 1182 254 1 0.777 0.02283 0.734 0.824
## 1187 253 1 0.774 0.02295 0.731 0.821
## 1189 252 1 0.771 0.02306 0.727 0.818
## 1193 251 1 0.768 0.02317 0.724 0.815
## 1194 250 1 0.765 0.02328 0.721 0.812
## 1195 249 1 0.762 0.02339 0.718 0.809
## 1196 248 1 0.759 0.02350 0.714 0.807
## 1204 242 1 0.756 0.02361 0.711 0.804
## 1206 241 1 0.753 0.02372 0.708 0.801
## 1207 240 1 0.750 0.02383 0.704 0.798
## 1211 239 1 0.746 0.02393 0.701 0.795
## 1212 238 1 0.743 0.02404 0.698 0.792
## 1220 236 1 0.740 0.02414 0.694 0.789
## 1221 235 1 0.737 0.02424 0.691 0.786
## 1222 234 1 0.734 0.02434 0.688 0.783
## 1228 230 1 0.731 0.02444 0.684 0.780
## 1234 229 1 0.728 0.02454 0.681 0.777
## 1236 228 1 0.724 0.02464 0.678 0.774
## 1237 227 1 0.721 0.02474 0.674 0.771
## 1241 225 1 0.718 0.02484 0.671 0.768
## 1242 224 1 0.715 0.02493 0.667 0.765
## 1243 223 1 0.712 0.02503 0.664 0.762
## 1245 222 1 0.708 0.02512 0.661 0.759
## 1247 221 1 0.705 0.02521 0.657 0.756
## 1248 220 1 0.702 0.02530 0.654 0.753
## 1250 219 1 0.699 0.02538 0.651 0.750
## 1253 218 1 0.696 0.02547 0.647 0.747
## 1258 217 1 0.692 0.02555 0.644 0.744
## 1261 216 1 0.689 0.02563 0.641 0.741
## 1272 212 1 0.686 0.02572 0.637 0.738
## 1273 211 1 0.683 0.02580 0.634 0.735
## 1274 210 1 0.679 0.02588 0.630 0.732
## 1275 209 1 0.676 0.02596 0.627 0.729
## 1277 208 1 0.673 0.02604 0.624 0.726
## 1279 207 1 0.670 0.02612 0.620 0.723
## 1280 206 1 0.666 0.02619 0.617 0.720
## 1284 205 1 0.663 0.02626 0.614 0.717
## 1290 204 1 0.660 0.02633 0.610 0.714
## 1291 203 1 0.657 0.02640 0.607 0.710
## 1295 202 1 0.653 0.02647 0.603 0.707
## 1296 201 1 0.650 0.02654 0.600 0.704
## 1297 200 1 0.647 0.02661 0.597 0.701
## 1298 199 1 0.644 0.02667 0.593 0.698
## 1300 198 1 0.640 0.02673 0.590 0.695
## 1304 197 1 0.637 0.02679 0.587 0.692
## 1308 196 1 0.634 0.02685 0.583 0.689
## 1309 195 1 0.631 0.02691 0.580 0.686
## 1319 192 1 0.627 0.02697 0.577 0.682
## 1321 191 1 0.624 0.02703 0.573 0.679
## 1324 190 1 0.621 0.02709 0.570 0.676
## 1325 189 1 0.617 0.02714 0.566 0.673
## 1326 188 1 0.614 0.02719 0.563 0.670
## 1327 187 1 0.611 0.02725 0.560 0.667
## 1331 186 1 0.608 0.02730 0.556 0.664
## 1333 185 1 0.604 0.02735 0.553 0.660
## 1336 184 1 0.601 0.02739 0.550 0.657
## 1337 183 1 0.598 0.02744 0.546 0.654
## 1351 177 1 0.594 0.02749 0.543 0.651
## 1352 176 1 0.591 0.02754 0.539 0.648
## 1354 175 1 0.588 0.02759 0.536 0.644
## 1355 174 1 0.584 0.02764 0.532 0.641
## 1356 173 1 0.581 0.02769 0.529 0.638
## 1357 172 1 0.577 0.02773 0.526 0.634
## 1359 171 1 0.574 0.02777 0.522 0.631
## 1363 170 1 0.571 0.02781 0.519 0.628
## 1365 169 1 0.567 0.02785 0.515 0.625
## 1368 168 1 0.564 0.02789 0.512 0.621
## 1381 162 1 0.560 0.02794 0.508 0.618
## 1383 161 1 0.557 0.02798 0.505 0.615
## 1384 160 1 0.554 0.02802 0.501 0.611
## 1387 159 1 0.550 0.02806 0.498 0.608
## 1392 158 1 0.547 0.02810 0.494 0.605
## 1393 157 1 0.543 0.02813 0.491 0.601
## 1406 149 1 0.539 0.02818 0.487 0.598
## 1408 148 1 0.536 0.02822 0.483 0.594
## 1409 147 1 0.532 0.02827 0.480 0.591
## 1411 146 1 0.529 0.02831 0.476 0.587
## 1412 145 1 0.525 0.02834 0.472 0.583
## 1416 144 1 0.521 0.02838 0.468 0.580
## 1417 143 1 0.518 0.02842 0.465 0.576
## 1418 142 1 0.514 0.02845 0.461 0.573
## 1419 141 1 0.510 0.02848 0.457 0.569
## 1436 139 1 0.507 0.02851 0.454 0.566
## 1437 138 1 0.503 0.02854 0.450 0.562
## 1438 137 1 0.499 0.02856 0.446 0.559
## 1444 136 1 0.496 0.02859 0.443 0.555
## 1455 131 1 0.492 0.02862 0.439 0.551
## 1457 130 1 0.488 0.02865 0.435 0.548
## 1458 129 1 0.484 0.02868 0.431 0.544
## 1459 128 1 0.480 0.02870 0.427 0.540
## 1460 127 1 0.477 0.02872 0.424 0.536
## 1463 126 1 0.473 0.02874 0.420 0.533
## 1465 125 1 0.469 0.02876 0.416 0.529
## 1468 124 1 0.465 0.02878 0.412 0.525
## 1471 123 1 0.462 0.02879 0.408 0.522
## 1487 119 1 0.458 0.02881 0.405 0.518
## 1492 118 1 0.454 0.02882 0.401 0.514
## 1496 117 1 0.450 0.02884 0.397 0.510
## 1511 110 1 0.446 0.02886 0.393 0.506
## 1523 106 1 0.442 0.02890 0.388 0.502
## 1524 105 1 0.437 0.02893 0.384 0.498
## 1527 104 1 0.433 0.02895 0.380 0.494
## 1528 103 1 0.429 0.02897 0.376 0.490
## 1532 102 1 0.425 0.02899 0.372 0.486
## 1535 101 1 0.421 0.02901 0.367 0.481
## 1539 100 1 0.416 0.02902 0.363 0.477
## 1540 99 1 0.412 0.02903 0.359 0.473
## 1550 96 1 0.408 0.02905 0.355 0.469
## 1552 95 1 0.404 0.02906 0.350 0.465
## 1556 94 1 0.399 0.02906 0.346 0.461
## 1559 93 1 0.395 0.02907 0.342 0.456
## 1560 92 1 0.391 0.02907 0.338 0.452
## 1576 80 1 0.386 0.02911 0.333 0.447
## 1578 79 1 0.381 0.02915 0.328 0.443
## 1579 78 1 0.376 0.02918 0.323 0.438
## 1580 77 1 0.371 0.02921 0.318 0.433
## 1581 76 1 0.366 0.02923 0.313 0.428
## 1594 69 1 0.361 0.02928 0.308 0.423
## 1596 68 1 0.356 0.02933 0.303 0.418
## 1599 67 1 0.350 0.02937 0.297 0.413
## 1600 66 1 0.345 0.02940 0.292 0.408
## 1601 65 1 0.340 0.02942 0.287 0.403
## 1602 64 1 0.334 0.02944 0.281 0.397
## 1611 60 1 0.329 0.02947 0.276 0.392
## 1612 59 1 0.323 0.02949 0.270 0.387
## 1613 58 1 0.318 0.02951 0.265 0.381
## 1614 57 1 0.312 0.02951 0.259 0.376
## 1630 51 1 0.306 0.02956 0.253 0.370
## 1633 49 1 0.300 0.02961 0.247 0.364
## 1645 44 1 0.293 0.02971 0.240 0.357
## 1648 43 1 0.286 0.02979 0.233 0.351
## 1659 38 1 0.279 0.02994 0.226 0.344
## 1673 37 1 0.271 0.03006 0.218 0.337
## 1681 35 1 0.263 0.03019 0.210 0.330
## 1683 34 1 0.256 0.03028 0.203 0.322
## 1685 33 1 0.248 0.03033 0.195 0.315
## 1693 28 1 0.239 0.03051 0.186 0.307
## 1697 27 1 0.230 0.03064 0.177 0.299
## 1716 23 1 0.220 0.03090 0.167 0.290
## 1724 17 1 0.207 0.03168 0.154 0.280
## 1727 16 1 0.194 0.03224 0.140 0.269
## 1728 15 1 0.181 0.03259 0.127 0.258
## 1739 10 1 0.163 0.03400 0.108 0.245Same time break up(optional)
summary(km_fit2, times=c(30,60,90*(1:30)))## Call: survfit(formula = Surv(LOS, censored) ~ Race, data = survive,
## type = "kaplan-meier")
##
## Race=Black
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 30 283 0 1.000 0.0000 1.000 1.000
## 60 283 0 1.000 0.0000 1.000 1.000
## 90 283 0 1.000 0.0000 1.000 1.000
## 180 283 0 1.000 0.0000 1.000 1.000
## 270 283 0 1.000 0.0000 1.000 1.000
## 360 283 0 1.000 0.0000 1.000 1.000
## 450 283 0 1.000 0.0000 1.000 1.000
## 540 283 0 1.000 0.0000 1.000 1.000
## 630 283 0 1.000 0.0000 1.000 1.000
## 720 283 0 1.000 0.0000 1.000 1.000
## 810 283 0 1.000 0.0000 1.000 1.000
## 900 283 0 1.000 0.0000 1.000 1.000
## 990 283 0 1.000 0.0000 1.000 1.000
## 1080 252 30 0.894 0.0184 0.858 0.930
## 1170 224 25 0.804 0.0237 0.759 0.852
## 1260 195 25 0.714 0.0271 0.663 0.769
## 1350 162 22 0.630 0.0292 0.576 0.690
## 1440 129 19 0.554 0.0305 0.497 0.617
## 1530 95 25 0.441 0.0315 0.384 0.508
## 1620 67 15 0.367 0.0316 0.310 0.434
## 1710 22 20 0.215 0.0328 0.160 0.290
##
## Race=HispanicLatino
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 30 79 0 1.000 0.0000 1.0000 1.000
## 60 79 0 1.000 0.0000 1.0000 1.000
## 90 79 0 1.000 0.0000 1.0000 1.000
## 180 79 0 1.000 0.0000 1.0000 1.000
## 270 79 0 1.000 0.0000 1.0000 1.000
## 360 79 0 1.000 0.0000 1.0000 1.000
## 450 79 0 1.000 0.0000 1.0000 1.000
## 540 79 0 1.000 0.0000 1.0000 1.000
## 630 79 0 1.000 0.0000 1.0000 1.000
## 720 79 0 1.000 0.0000 1.0000 1.000
## 810 79 0 1.000 0.0000 1.0000 1.000
## 900 79 0 1.000 0.0000 1.0000 1.000
## 990 79 0 1.000 0.0000 1.0000 1.000
## 1080 75 4 0.949 0.0247 0.9022 0.999
## 1170 62 14 0.772 0.0472 0.6850 0.870
## 1260 52 9 0.658 0.0534 0.5615 0.772
## 1350 43 6 0.581 0.0556 0.4818 0.701
## 1440 34 7 0.485 0.0571 0.3855 0.611
## 1530 21 5 0.405 0.0581 0.3058 0.536
## 1620 12 6 0.276 0.0591 0.1813 0.420
## 1710 5 4 0.169 0.0564 0.0875 0.325
##
## Race=White
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 30 339 0 1.000 0.0000 1.000 1.000
## 60 339 0 1.000 0.0000 1.000 1.000
## 90 339 0 1.000 0.0000 1.000 1.000
## 180 339 0 1.000 0.0000 1.000 1.000
## 270 339 0 1.000 0.0000 1.000 1.000
## 360 339 0 1.000 0.0000 1.000 1.000
## 450 339 0 1.000 0.0000 1.000 1.000
## 540 339 0 1.000 0.0000 1.000 1.000
## 630 339 0 1.000 0.0000 1.000 1.000
## 720 339 0 1.000 0.0000 1.000 1.000
## 810 339 0 1.000 0.0000 1.000 1.000
## 900 339 0 1.000 0.0000 1.000 1.000
## 990 339 0 1.000 0.0000 1.000 1.000
## 1080 304 31 0.908 0.0158 0.878 0.939
## 1170 261 36 0.799 0.0220 0.757 0.843
## 1260 216 34 0.692 0.0256 0.644 0.744
## 1350 177 29 0.598 0.0274 0.546 0.654
## 1440 136 28 0.499 0.0286 0.446 0.559
## 1530 102 18 0.429 0.0290 0.376 0.490
## 1620 56 24 0.312 0.0295 0.259 0.376
## 1710 24 11 0.230 0.0306 0.177 0.299The final less ugly product separating all groups in one chart
ggsurvplot(km_fit2, data=survive, risk.table=TRUE, conf.int=TRUE,
pval=TRUE, pval.method=TRUE,
ggtheme=theme_minimal())