test

test.R

#> asaur::pharmacoSmoking
#> Relative Efficiency: 1.14
#>                                 term estimate stderr pvalue     method    corr
#> 1  Surv(time = ttr, event = relapse)   -0.538   0.20 0.0074      PATED      NA
#> 2  Surv(time = ttr, event = relapse)   -0.605   0.21 0.0048   Standard  1.0000
#> 3                                age    2.170   2.11 0.3030 Prognostic -0.2144
#> 4                       yearsSmoking    1.963   2.08 0.3461 Prognostic -0.1494
#> 5                      priorAttempts   15.514  16.35 0.3426 Prognostic  0.0187
#> 6                     longestNoSmoke  116.806 192.25 0.5435 Prognostic -0.1463
#> 7                             gender    0.074   0.38 0.8438 Prognostic -0.0740
#> 8                 I(race == "black")   -0.543   0.40 0.1717 Prognostic  0.0816
#> 9              I(race == "hispanic")    0.051   0.73 0.9443 Prognostic -0.0420
#> 10                I(race == "white")    0.467   0.37 0.2108 Prognostic -0.0243
#> 11             I(employment == "ft")   -0.149   0.36 0.6821 Prognostic -0.1217
#> 12             I(employment == "pt")    0.054   0.57 0.9244 Prognostic  0.1133
#> 13        I(levelSmoking == "heavy")    0.089   0.40 0.8231 Prognostic -0.0067

test.R

#> coin::glioma
#> Relative Efficiency: 1.66
#>                               term estimate stderr  pvalue     method corr
#> 1 Surv(time = time, event = event)   -1.423   0.36 7.1e-05      PATED   NA
#> 2 Surv(time = time, event = event)   -1.829   0.46 7.4e-05   Standard 1.00
#> 3                              age   -3.272   4.67 4.8e-01 Prognostic 0.33
#> 4                              sex    0.095   0.67 8.9e-01 Prognostic 0.13
#> 5            I(histology == "GBM")   -1.012   0.69 1.4e-01 Prognostic 0.59

test.R

#> iBST::burn
#> Relative Efficiency: 1.15
#>                           term estimate stderr pvalue     method   corr
#> 1  Surv(time = T3, event = D3)   -0.582   0.27  0.034      PATED     NA
#> 2  Surv(time = T3, event = D3)   -0.561   0.29  0.056   Standard  1.000
#> 3                           Z2   -0.083   0.39  0.832 Prognostic -0.149
#> 4                           Z3    0.088   0.49  0.858 Prognostic  0.215
#> 5                           Z5   -0.125   0.33  0.702 Prognostic  0.029
#> 6                           Z6    0.442   0.40  0.265 Prognostic  0.113
#> 7                           Z7    0.821   0.46  0.074 Prognostic  0.055
#> 8                           Z8   -0.256   0.33  0.438 Prognostic -0.035
#> 9                           Z9    0.294   0.36  0.408 Prognostic -0.042
#> 10                         Z10   -0.448   0.36  0.210 Prognostic -0.013
#> 11                 I(Z11 == 1)    0.541   0.73  0.458 Prognostic -0.104
#> 12                 I(Z11 == 2)   -0.718   0.52  0.163 Prognostic  0.025
#> 13                 I(Z11 == 3)    0.405   0.65  0.533 Prognostic  0.195
#> 14                          Z4   -5.483   3.18  0.085 Prognostic  0.074

test.R

#> invGauss::d.oropha.rec
#> Relative Efficiency: 1.06
#>                                term estimate stderr pvalue     method  corr
#> 1 Surv(time = time, event = status)  0.16718  0.166   0.31      PATED    NA
#> 2 Surv(time = time, event = status)  0.17374  0.171   0.31   Standard 1.000
#> 3                       I(sex == 1)  0.00065  0.061   0.99 Prognostic 0.050
#> 4                               age -0.37169  1.572   0.81 Prognostic 0.019
#> 5                            tstage -0.03691  0.117   0.75 Prognostic 0.181
#> 6                            nstage  0.13222  0.171   0.44 Prognostic 0.118

test.R

#> JM::aids.id
#> Relative Efficiency: 1.25
#>                               term estimate stderr pvalue     method  corr
#> 1 Surv(time = Time, event = death)   -0.247   0.13  0.059      PATED    NA
#> 2 Surv(time = Time, event = death)   -0.210   0.15  0.150   Standard  1.00
#> 3                              CD4   -0.213   0.44  0.625 Prognostic -0.40
#> 4                           gender   -0.016   0.31  0.959 Prognostic -0.03
#> 5              I(prevOI == "AIDS")    0.084   0.20  0.668 Prognostic  0.35
#> 6          I(AZT == "intolerance")   -0.080   0.19  0.676 Prognostic -0.23

test.R

#> mlr3proba::actg
#> Relative Efficiency: 1.09
#>                                term estimate stderr pvalue     method    corr
#> 1  Surv(time = time, event = event)  -0.6755   0.21 0.0011      PATED      NA
#> 2  Surv(time = time, event = event)  -0.6844   0.22 0.0015   Standard  1.0000
#> 3                            strat2  -0.0011   0.12 0.9930 Prognostic -0.1825
#> 4                               sex   0.1517   0.16 0.3305 Prognostic  0.0011
#> 5                    I(ivdrug == 1)   0.0328   0.16 0.8389 Prognostic  0.0398
#> 6                    I(raceth == 1)   0.0665   0.12 0.5732 Prognostic  0.0048
#> 7                    I(raceth == 2)  -0.0183   0.13 0.8884 Prognostic -0.0435
#> 8                    I(raceth == 3)  -0.0774   0.15 0.6170 Prognostic  0.0264
#> 9                          hemophil  -0.4126   0.35 0.2389 Prognostic -0.0164
#> 10                 I(karnof == 100)  -0.0537   0.12 0.6656 Prognostic -0.0961
#> 11                  I(karnof == 90)   0.0587   0.12 0.6196 Prognostic -0.0467
#> 12                  I(karnof == 80)  -0.0460   0.16 0.7759 Prognostic  0.1200
#> 13                  I(karnof == 70)   0.1341   0.36 0.7091 Prognostic  0.1489
#> 14                              cd4   4.3155   4.13 0.2958 Prognostic -0.1939
#> 15                         priorzdv   0.1439   1.72 0.9334 Prognostic -0.0396
#> 16                              age   0.0503   0.52 0.9229 Prognostic  0.0609

test.R

#> joint.Cox::dataOvarian1
#> Relative Efficiency: 1.1
#>                                  term estimate stderr pvalue     method  corr
#> 1 Surv(time = t.event, event = event)  -0.1651  0.077  0.033      PATED    NA
#> 2 Surv(time = t.event, event = event)  -0.1696  0.081  0.036   Standard 1.000
#> 3                              CXCL12  -0.0341  0.061  0.576 Prognostic 0.202
#> 4                               NCOA3  -0.0583  0.060  0.331 Prognostic 0.154
#> 5                                PDPN   0.0238  0.066  0.720 Prognostic 0.194
#> 6                               TEAD1   0.0086  0.067  0.897 Prognostic 0.188
#> 7                               TIMP2   0.0381  0.061  0.535 Prognostic 0.192
#> 8                               YWHAB   0.0114  0.055  0.837 Prognostic 0.088

test.R

#> pec::Pbc3
#> Relative Efficiency: 1.58
#>                                term estimate stderr pvalue     method    corr
#> 1  Surv(time = days, event = event)   -0.193   0.17   0.25      PATED      NA
#> 2  Surv(time = days, event = event)   -0.059   0.21   0.78   Standard  1.0000
#> 3                               sex    0.026   0.30   0.93 Prognostic  0.1432
#> 4                     I(stage == 1)   -0.107   0.31   0.73 Prognostic -0.2463
#> 5                     I(stage == 2)   -0.336   0.26   0.20 Prognostic -0.1746
#> 6                     I(stage == 3)    0.168   0.28   0.55 Prognostic -0.0013
#> 7                     I(stage == 4)    0.253   0.26   0.32 Prognostic  0.3682
#> 8                           gibleed   -0.590   0.31   0.06 Prognostic  0.1358
#> 9                               age    0.142   1.06   0.89 Prognostic  0.0618
#> 10                             crea   -1.150   1.97   0.56 Prognostic -0.1020
#> 11                             bili    6.219   7.23   0.39 Prognostic  0.4977
#> 12                            alkph  -12.043  80.55   0.88 Prognostic  0.0986
#> 13                            asptr    2.641   5.69   0.64 Prognostic  0.2231
#> 14                           weight    0.391   1.11   0.72 Prognostic -0.1465

test.R

#> pec::cost
#> Relative Efficiency: 1.47
#>                                 term estimate stderr pvalue     method   corr
#> 1  Surv(time = time, event = status) -1.8e-01  0.079  0.024      PATED     NA
#> 2  Surv(time = time, event = status) -1.4e-01  0.095  0.140   Standard  1.000
#> 3                                age  6.7e-01  0.900  0.459 Prognostic  0.417
#> 4                        strokeScore -5.1e-01  1.009  0.613 Prognostic -0.268
#> 5                            cholest  2.7e-02  0.118  0.819 Prognostic -0.055
#> 6                                sex -1.1e-01  0.164  0.514 Prognostic  0.097
#> 7                             hypTen  1.8e-01  0.173  0.301 Prognostic  0.081
#> 8                                ihd -3.0e-15  0.218  1.000 Prognostic  0.133
#> 9                         prevStroke -8.6e-02  0.207  0.680 Prognostic  0.145
#> 10                        othDisease -2.6e-02  0.230  0.909 Prognostic  0.139
#> 11                           alcohol -3.2e-01  0.175  0.068 Prognostic -0.122
#> 12                          diabetes -1.6e-01  0.234  0.485 Prognostic  0.123
#> 13                             smoke -2.3e-01  0.165  0.163 Prognostic -0.093
#> 14                         atrialFib  3.3e-01  0.247  0.181 Prognostic  0.203
#> 15                             hemor  3.0e-01  0.449  0.507 Prognostic  0.026

test.R

#> pec::GBSG2
#> Relative Efficiency: 1.18
#>                              term estimate stderr pvalue     method   corr
#> 1 Surv(time = time, event = cens)    -0.33   0.11 0.0039      PATED     NA
#> 2 Surv(time = time, event = cens)    -0.36   0.12 0.0034   Standard  1.000
#> 3                           tsize    -0.82   1.13 0.4696 Prognostic  0.169
#> 4                          pnodes     0.19   0.43 0.6643 Prognostic  0.326
#> 5                         progrec    22.29  17.84 0.2116 Prognostic -0.187
#> 6                I(tgrade == "I")     0.24   0.24 0.3305 Prognostic -0.159
#> 7               I(tgrade == "II")     0.11   0.17 0.5291 Prognostic  0.006
#> 8              I(tgrade == "III")    -0.28   0.19 0.1472 Prognostic  0.123

test.R

#> randomForestSRC::follic
#> Relative Efficiency: 1.11
#>                                term estimate stderr pvalue     method   corr
#> 1 Surv(time = time, event = status)    -0.15   0.14   0.28      PATED     NA
#> 2 Surv(time = time, event = status)    -0.23   0.15   0.13   Standard  1.000
#> 3                               age    -2.37   1.47   0.11 Prognostic  0.311
#> 4                               hgb     0.84   1.52   0.58 Prognostic -0.082

test.R