test
#> asaur::pharmacoSmoking
#> Relative Efficiency: 1.14
#> term family estimate stderr pvalue method
#> 1 Surv(time = ttr, event = relapse) PATED -0.538 0.20 0.0071 PATED
#> 2 Surv(time = ttr, event = relapse) coxph -0.605 0.21 0.0046 Standard
#> 3 age gaussian 2.170 2.10 0.3011 Prognostic
#> 4 yearsSmoking gaussian 1.963 2.08 0.3442 Prognostic
#> 5 priorAttempts gaussian 15.514 16.28 0.3406 Prognostic
#> 6 longestNoSmoke gaussian 116.806 191.48 0.5419 Prognostic
#> 7 gender binomial 0.074 0.37 0.8432 Prognostic
#> 8 I(race == "black") binomial -0.543 0.40 0.1700 Prognostic
#> 9 I(race == "hispanic") binomial 0.051 0.73 0.9441 Prognostic
#> 10 I(race == "white") binomial 0.467 0.37 0.2090 Prognostic
#> 11 I(employment == "ft") binomial -0.149 0.36 0.6809 Prognostic
#> 12 I(employment == "pt") binomial 0.054 0.57 0.9241 Prognostic
#> 13 I(levelSmoking == "heavy") binomial 0.089 0.40 0.8224 Prognostic
#> corr
#> 1 NA
#> 2 1.0000
#> 3 -0.2144
#> 4 -0.1494
#> 5 0.0187
#> 6 -0.1463
#> 7 -0.0740
#> 8 0.0816
#> 9 -0.0420
#> 10 -0.0243
#> 11 -0.1217
#> 12 0.1133
#> 13 -0.0067
#> coin::glioma
#> Relative Efficiency: 1.66
#> term family estimate stderr pvalue method
#> 1 Surv(time = time, event = event) PATED -1.423 0.35 5.6e-05 PATED
#> 2 Surv(time = time, event = event) coxph -1.829 0.46 5.9e-05 Standard
#> 3 age gaussian -3.272 4.61 4.8e-01 Prognostic
#> 4 sex binomial 0.095 0.66 8.9e-01 Prognostic
#> 5 I(histology == "GBM") binomial -1.012 0.68 1.4e-01 Prognostic
#> corr
#> 1 NA
#> 2 1.00
#> 3 0.33
#> 4 0.13
#> 5 0.59
#> iBST::burn
#> Relative Efficiency: 1.15
#> term family estimate stderr pvalue method
#> 1 Surv(time = T3, event = D3) PATED -0.582 0.27 0.033 PATED
#> 2 Surv(time = T3, event = D3) coxph -0.561 0.29 0.055 Standard
#> 3 Z2 binomial -0.083 0.39 0.831 Prognostic
#> 4 Z3 binomial 0.088 0.49 0.858 Prognostic
#> 5 Z5 binomial -0.125 0.33 0.701 Prognostic
#> 6 Z6 binomial 0.442 0.40 0.263 Prognostic
#> 7 Z7 binomial 0.821 0.46 0.073 Prognostic
#> 8 Z8 binomial -0.256 0.33 0.437 Prognostic
#> 9 Z9 binomial 0.294 0.35 0.407 Prognostic
#> 10 Z10 binomial -0.448 0.36 0.209 Prognostic
#> 11 I(Z11 == 1) binomial 0.541 0.73 0.456 Prognostic
#> 12 I(Z11 == 2) binomial -0.718 0.51 0.162 Prognostic
#> 13 I(Z11 == 3) binomial 0.405 0.65 0.532 Prognostic
#> 14 Z4 gaussian -5.483 3.17 0.084 Prognostic
#> corr
#> 1 NA
#> 2 1.000
#> 3 -0.149
#> 4 0.215
#> 5 0.029
#> 6 0.113
#> 7 0.055
#> 8 -0.035
#> 9 -0.042
#> 10 -0.013
#> 11 -0.104
#> 12 0.025
#> 13 0.195
#> 14 0.074
#> invGauss::d.oropha.rec
#> Relative Efficiency: 1.06
#> term family estimate stderr pvalue method
#> 1 Surv(time = time, event = status) PATED 0.16718 0.166 0.31 PATED
#> 2 Surv(time = time, event = status) coxph 0.17374 0.171 0.31 Standard
#> 3 I(sex == 1) gaussian 0.00065 0.061 0.99 Prognostic
#> 4 age gaussian -0.37169 1.568 0.81 Prognostic
#> 5 tstage gaussian -0.03691 0.117 0.75 Prognostic
#> 6 nstage gaussian 0.13222 0.170 0.44 Prognostic
#> corr
#> 1 NA
#> 2 1.000
#> 3 0.050
#> 4 0.019
#> 5 0.181
#> 6 0.118
#> JM::aids.id
#> Relative Efficiency: 1.25
#> term family estimate stderr pvalue method
#> 1 Surv(time = Time, event = death) PATED -0.247 0.13 0.059 PATED
#> 2 Surv(time = Time, event = death) coxph -0.210 0.15 0.150 Standard
#> 3 CD4 gaussian -0.213 0.44 0.624 Prognostic
#> 4 gender binomial -0.016 0.31 0.959 Prognostic
#> 5 I(prevOI == "AIDS") binomial 0.084 0.20 0.668 Prognostic
#> 6 I(AZT == "intolerance") binomial -0.080 0.19 0.676 Prognostic
#> corr
#> 1 NA
#> 2 1.00
#> 3 -0.40
#> 4 -0.03
#> 5 0.35
#> 6 -0.23
#> mlr3proba::actg
#> Relative Efficiency: 1.09
#> term family estimate stderr pvalue method
#> 1 Surv(time = time, event = event) PATED -0.6755 0.21 0.0011 PATED
#> 2 Surv(time = time, event = event) coxph -0.6844 0.22 0.0015 Standard
#> 3 strat2 binomial -0.0011 0.12 0.9930 Prognostic
#> 4 sex binomial 0.1517 0.16 0.3303 Prognostic
#> 5 I(ivdrug == 1) binomial 0.0328 0.16 0.8388 Prognostic
#> 6 I(raceth == 1) binomial 0.0665 0.12 0.5731 Prognostic
#> 7 I(raceth == 2) binomial -0.0183 0.13 0.8884 Prognostic
#> 8 I(raceth == 3) binomial -0.0774 0.15 0.6168 Prognostic
#> 9 hemophil binomial -0.4126 0.35 0.2387 Prognostic
#> 10 I(karnof == 100) binomial -0.0537 0.12 0.6655 Prognostic
#> 11 I(karnof == 90) binomial 0.0587 0.12 0.6194 Prognostic
#> 12 I(karnof == 80) binomial -0.0460 0.16 0.7758 Prognostic
#> 13 I(karnof == 70) binomial 0.1341 0.36 0.7089 Prognostic
#> 14 cd4 gaussian 4.3155 4.13 0.2956 Prognostic
#> 15 priorzdv gaussian 0.1439 1.72 0.9334 Prognostic
#> 16 age gaussian 0.0503 0.52 0.9228 Prognostic
#> corr
#> 1 NA
#> 2 1.0000
#> 3 -0.1825
#> 4 0.0011
#> 5 0.0398
#> 6 0.0048
#> 7 -0.0435
#> 8 0.0264
#> 9 -0.0164
#> 10 -0.0961
#> 11 -0.0467
#> 12 0.1200
#> 13 0.1489
#> 14 -0.1939
#> 15 -0.0396
#> 16 0.0609
#> joint.Cox::dataOvarian1
#> Relative Efficiency: 1.1
#> term family estimate stderr pvalue
#> 1 Surv(time = t.event, event = event) PATED -0.1651 0.077 0.033
#> 2 Surv(time = t.event, event = event) coxph -0.1696 0.081 0.036
#> 3 CXCL12 gaussian -0.0341 0.061 0.576
#> 4 NCOA3 gaussian -0.0583 0.060 0.331
#> 5 PDPN gaussian 0.0238 0.066 0.720
#> 6 TEAD1 gaussian 0.0086 0.067 0.897
#> 7 TIMP2 gaussian 0.0381 0.061 0.535
#> 8 YWHAB gaussian 0.0114 0.055 0.837
#> method corr
#> 1 PATED NA
#> 2 Standard 1.000
#> 3 Prognostic 0.202
#> 4 Prognostic 0.154
#> 5 Prognostic 0.194
#> 6 Prognostic 0.188
#> 7 Prognostic 0.192
#> 8 Prognostic 0.088
#> pec::Pbc3
#> Relative Efficiency: 1.58
#> term family estimate stderr pvalue method
#> 1 Surv(time = days, event = event) PATED -0.193 0.17 0.25 PATED
#> 2 Surv(time = days, event = event) coxph -0.059 0.21 0.78 Standard
#> 3 sex binomial 0.026 0.30 0.93 Prognostic
#> 4 I(stage == 1) binomial -0.107 0.31 0.73 Prognostic
#> 5 I(stage == 2) binomial -0.336 0.26 0.20 Prognostic
#> 6 I(stage == 3) binomial 0.168 0.28 0.55 Prognostic
#> 7 I(stage == 4) binomial 0.253 0.25 0.32 Prognostic
#> 8 gibleed binomial -0.590 0.31 0.06 Prognostic
#> 9 age gaussian 0.142 1.06 0.89 Prognostic
#> 10 crea gaussian -1.150 1.97 0.56 Prognostic
#> 11 bili gaussian 6.219 7.22 0.39 Prognostic
#> 12 alkph gaussian -12.043 80.43 0.88 Prognostic
#> 13 asptr gaussian 2.641 5.68 0.64 Prognostic
#> 14 weight gaussian 0.391 1.11 0.72 Prognostic
#> corr
#> 1 NA
#> 2 1.0000
#> 3 0.1432
#> 4 -0.2463
#> 5 -0.1745
#> 6 -0.0013
#> 7 0.3681
#> 8 0.1358
#> 9 0.0618
#> 10 -0.1020
#> 11 0.4977
#> 12 0.0986
#> 13 0.2231
#> 14 -0.1465
#> pec::cost
#> Relative Efficiency: 1.47
#> term family estimate stderr pvalue method
#> 1 Surv(time = time, event = status) PATED -1.8e-01 0.079 0.024 PATED
#> 2 Surv(time = time, event = status) coxph -1.4e-01 0.095 0.140 Standard
#> 3 age gaussian 6.7e-01 0.899 0.458 Prognostic
#> 4 strokeScore gaussian -5.1e-01 1.009 0.613 Prognostic
#> 5 cholest gaussian 2.7e-02 0.118 0.819 Prognostic
#> 6 sex binomial -1.1e-01 0.163 0.514 Prognostic
#> 7 hypTen binomial 1.8e-01 0.173 0.300 Prognostic
#> 8 ihd binomial -7.5e-17 0.217 1.000 Prognostic
#> 9 prevStroke binomial -8.6e-02 0.207 0.679 Prognostic
#> 10 othDisease binomial -2.6e-02 0.230 0.909 Prognostic
#> 11 alcohol binomial -3.2e-01 0.175 0.068 Prognostic
#> 12 diabetes binomial -1.6e-01 0.234 0.485 Prognostic
#> 13 smoke binomial -2.3e-01 0.164 0.163 Prognostic
#> 14 atrialFib binomial 3.3e-01 0.246 0.181 Prognostic
#> 15 hemor binomial 3.0e-01 0.449 0.507 Prognostic
#> corr
#> 1 NA
#> 2 1.000
#> 3 0.417
#> 4 -0.268
#> 5 -0.055
#> 6 0.097
#> 7 0.081
#> 8 0.133
#> 9 0.145
#> 10 0.139
#> 11 -0.122
#> 12 0.123
#> 13 -0.093
#> 14 0.203
#> 15 0.026
#> pec::GBSG2
#> Relative Efficiency: 1.18
#> term family estimate stderr pvalue method
#> 1 Surv(time = time, event = cens) PATED -0.33 0.11 0.0039 PATED
#> 2 Surv(time = time, event = cens) coxph -0.36 0.12 0.0034 Standard
#> 3 tsize gaussian -0.82 1.13 0.4693 Prognostic
#> 4 pnodes gaussian 0.19 0.43 0.6641 Prognostic
#> 5 progrec gaussian 22.29 17.83 0.2113 Prognostic
#> 6 I(tgrade == "I") binomial 0.24 0.24 0.3302 Prognostic
#> 7 I(tgrade == "II") binomial 0.11 0.17 0.5288 Prognostic
#> 8 I(tgrade == "III") binomial -0.28 0.19 0.1469 Prognostic
#> corr
#> 1 NA
#> 2 1.000
#> 3 0.169
#> 4 0.326
#> 5 -0.187
#> 6 -0.159
#> 7 0.006
#> 8 0.123
#> randomForestSRC::follic
#> Relative Efficiency: 1.11
#> term family estimate stderr pvalue method
#> 1 Surv(time = time, event = status) PATED -0.15 0.14 0.28 PATED
#> 2 Surv(time = time, event = status) coxph -0.23 0.15 0.12 Standard
#> 3 age gaussian -2.37 1.47 0.11 Prognostic
#> 4 hgb gaussian 0.84 1.52 0.58 Prognostic
#> corr
#> 1 NA
#> 2 1.000
#> 3 0.311
#> 4 -0.082