I run ggforest on a cox model and I wonder now, how I have to interpret the output:
Here, several factors of the variable country are shown. I stumble over the fact, that only countries with very few amounts (Lithuania, Macedonia and Slovenia, yet, Japan e.g. does not) show significances while countries with a lot of units like Italy and South Africa do not provide significances.
How do I have to understand the last column?
edit: Output of
Call:
coxph(formula = Surv(time = time, event = status) ~
position_in_unit + country + unit_type + version_no + pos +
production_year, data = df_cox1, robust = TRUE)
n= 4266, number of events= 3808
coef exp(coef) se(coef) robust se z Pr(>|z|)
country? 6.486e-01 1.913e+00 8.443e-01 6.755e-01 0.960 0.336958
countryAlbania -1.375e-01 8.715e-01 7.924e-01 5.448e-01 -0.252 0.800697
countryAustralia -1.172e+00 3.097e-01 3.739e-01 5.604e-01 -2.092 0.036456 *
countryBrazil 5.784e-01 1.783e+00 7.948e-01 5.373e-01 1.077 0.281681
countryBulgaria 8.689e-02 1.091e+00 4.096e-01 5.426e-01 0.160 0.872781
countryCroatia -4.393e-01 6.445e-01 5.779e-01 6.317e-01 -0.696 0.486739
countryCzech Republic 2.337e-01 1.263e+00 4.229e-01 5.820e-01 0.402 0.687948
countryDenmark -1.101e+00 3.326e-01 3.658e-01 5.418e-01 -2.032 0.042164 *
countryEgypt 9.548e-01 2.598e+00 5.253e-01 5.829e-01 1.638 0.101418
countryFinland -1.071e+00 3.426e-01 4.602e-01 6.082e-01 -1.761 0.078160 .
countryGermany -4.623e-01 6.298e-01 3.501e-01 5.306e-01 -0.871 0.383657
countryGreece -8.345e-01 4.341e-01 3.579e-01 5.340e-01 -1.563 0.118157
countryHungary -5.246e-01 5.918e-01 3.652e-01 5.361e-01 -0.979 0.327810
countryIceland -7.643e-01 4.657e-01 3.813e-01 5.482e-01 -1.394 0.163285
countryIndia -4.836e-01 6.166e-01 3.600e-01 5.367e-01 -0.901 0.367583
countryItaly -7.942e-01 4.519e-01 3.758e-01 5.503e-01 -1.443 0.148909
countryJapan 6.287e-01 1.875e+00 1.089e+00 5.641e-01 1.115 0.265052
countryLithuania -1.445e+00 2.358e-01 6.139e-01 5.664e-01 -2.551 0.010740 *
countryMacedonia 1.760e+00 5.811e+00 1.063e+00 5.371e-01 3.276 0.001052 **
countryMalaysia -6.192e-01 5.384e-01 3.895e-01 5.514e-01 -1.123 0.261409
countryNetherlands 6.590e-01 1.933e+00 4.049e-01 5.516e-01 1.195 0.232144
countryNew Zealand 2.178e-01 1.243e+00 5.709e-01 6.747e-01 0.323 0.746800
countryNorway -8.852e-01 4.126e-01 3.564e-01 5.347e-01 -1.655 0.097826 .
countryPoland -5.351e-01 5.856e-01 3.725e-01 5.384e-01 -0.994 0.320277
countryPortugal -8.723e-01 4.180e-01 3.569e-01 5.347e-01 -1.631 0.102815
countryQatar -1.121e-01 8.939e-01 4.007e-01 5.619e-01 -0.200 0.841798
countryRussian Federation 3.858e-01 1.471e+00 4.246e-01 5.672e-01 0.680 0.496444
countrySchweiz 2.626e-01 1.300e+00 1.068e+00 5.384e-01 0.488 0.625795
countrySerbia -3.720e-01 6.893e-01 5.306e-01 5.869e-01 -0.634 0.526133
countrySlovakia 1.001e-01 1.105e+00 4.596e-01 6.305e-01 0.159 0.873880
countrySlovenia -1.346e+00 2.603e-01 4.541e-01 6.008e-01 -2.240 0.025083 *
countrySouth Africa 3.426e-01 1.409e+00 3.492e-01 5.318e-01 0.644 0.519441
countrySpain -1.284e-01 8.795e-01 3.672e-01 5.370e-01 -0.239 0.810985
countrySweden -5.642e-01 5.688e-01 4.139e-01 5.792e-01 -0.974 0.330031
countrySwitzerland -6.150e-01 5.406e-01 3.524e-01 5.335e-01 -1.153 0.248940
countryTunisia 8.887e-01 2.432e+00 1.068e+00 5.535e-01 1.606 0.108375
countryTurkey -3.135e-01 7.309e-01 3.540e-01 5.351e-01 -0.586 0.558043
countryUnited Arab Emirates -9.516e-01 3.861e-01 4.320e-01 6.156e-01 -1.546 0.122159
countryUnited Kingdom 1.644e+00 5.174e+00 1.122e+00 5.988e-01 2.745 0.006054 **
version_no?? -2.422e+00 8.879e-02 1.042e+00 2.728e-01 -8.877 < 2e-16 ***
version_no1 -3.496e+00 3.033e-02 1.541e+00 5.582e-01 -6.262 3.79e-10 ***
version_no10 -4.304e+00 1.351e-02 1.468e+00 3.635e-01 -11.842 < 2e-16 ***
version_no12 -3.851e+00 2.126e-02 1.447e+00 2.936e-01 -13.117 < 2e-16 ***
version_no13 -3.768e+00 2.310e-02 1.449e+00 3.041e-01 -12.392 < 2e-16 ***
version_no14 -4.565e+00 1.041e-02 1.624e+00 4.432e-01 -10.300 < 2e-16 ***
version_no16 -3.807e+00 2.220e-02 1.448e+00 3.267e-01 -11.655 < 2e-16 ***
version_no17 -1.794e+00 1.662e-01 1.609e+00 4.038e-01 -4.443 8.85e-06 ***
version_no18 -3.955e+00 1.916e-02 1.451e+00 3.142e-01 -12.589 < 2e-16 ***
version_no19 -3.597e+00 2.741e-02 1.437e+00 2.478e-01 -14.513 < 2e-16 ***
version_no2 -3.418e+00 3.279e-02 1.540e+00 5.573e-01 -6.133 8.65e-10 ***
version_no20 -3.525e+00 2.947e-02 1.455e+00 4.167e-01 -8.459 < 2e-16 ***
version_no21 -3.313e+00 3.642e-02 1.426e+00 1.638e-01 -20.218 < 2e-16 ***
version_no22 -2.483e+00 8.350e-02 1.477e+00 3.396e-01 -7.311 2.65e-13 ***
version_no23 -3.654e+00 2.588e-02 1.439e+00 2.728e-01 -13.395 < 2e-16 ***
version_no24 -4.080e+00 1.691e-02 1.447e+00 3.473e-01 -11.747 < 2e-16 ***
version_no25 -5.072e+00 6.271e-03 1.492e+00 3.898e-01 -13.012 < 2e-16 ***
version_no26 -4.168e+00 1.549e-02 1.449e+00 3.801e-01 -10.965 < 2e-16 ***
version_no27 -4.150e+00 1.577e-02 1.450e+00 3.636e-01 -11.412 < 2e-16 ***
version_no28 -3.652e+00 2.594e-02 1.469e+00 4.029e-01 -9.063 < 2e-16 ***
version_no29 -4.265e+00 1.405e-02 1.461e+00 3.925e-01 -10.865 < 2e-16 ***
version_no3 -3.600e+00 2.731e-02 1.484e+00 4.148e-01 -8.679 < 2e-16 ***
version_no30 -3.911e+00 2.003e-02 1.487e+00 4.376e-01 -8.937 < 2e-16 ***
version_no31 -4.537e+00 1.071e-02 1.469e+00 4.068e-01 -11.152 < 2e-16 ***
version_no32 -4.237e+00 1.445e-02 1.490e+00 4.346e-01 -9.749 < 2e-16 ***
version_no33 -4.496e+00 1.115e-02 1.497e+00 4.564e-01 -9.852 < 2e-16 ***
version_no4 -4.837e+00 7.929e-03 1.562e+00 5.592e-01 -8.650 < 2e-16 ***
version_no5 -3.940e+00 1.945e-02 1.486e+00 4.137e-01 -9.523 < 2e-16 ***
version_no6 -3.946e+00 1.932e-02 1.480e+00 3.980e-01 -9.916 < 2e-16 ***
version_no7 -3.701e+00 2.469e-02 1.472e+00 3.806e-01 -9.725 < 2e-16 ***
version_no8 -3.873e+00 2.080e-02 1.484e+00 4.602e-01 -8.416 < 2e-16 ***
version_no9 -4.132e+00 1.606e-02 1.504e+00 5.048e-01 -8.185 2.73e-16 ***
version_noAH -3.224e+00 3.980e-02 1.624e+00 6.091e-01 -5.293 1.20e-07 ***
version_noAI -3.113e+00 4.448e-02 1.555e+00 5.758e-01 -5.406 6.43e-08 ***
version_noAJ -1.721e+00 1.789e-01 1.611e+00 5.277e-01 -3.261 0.001110 **
version_noAK -3.463e+00 3.133e-02 1.524e+00 4.996e-01 -6.931 4.18e-12 ***
version_noAL -3.754e+00 2.342e-02 1.530e+00 5.332e-01 -7.041 1.91e-12 ***
version_noXX -4.619e+00 9.860e-03 1.507e+00 4.400e-01 -10.497 < 2e-16 ***
pos? 5.580e-02 1.057e+00 1.506e-01 1.500e-01 0.372 0.709963
pos1 -1.117e-01 8.943e-01 1.231e-01 1.167e-01 -0.957 0.338417
pos10 9.550e-02 1.100e+00 1.520e-01 1.369e-01 0.698 0.485483
pos11 1.460e-01 1.157e+00 1.603e-01 1.666e-01 0.876 0.381025
pos12 3.476e-01 1.416e+00 1.645e-01 1.738e-01 2.000 0.045532 *
pos13 1.631e-01 1.177e+00 1.730e-01 1.693e-01 0.963 0.335375
pos14 6.381e-02 1.066e+00 1.770e-01 1.780e-01 0.358 0.720015
pos15 2.723e-01 1.313e+00 1.801e-01 1.686e-01 1.615 0.106313
pos16 -5.672e-02 9.449e-01 1.829e-01 1.802e-01 -0.315 0.752910
pos17 3.711e-02 1.038e+00 1.843e-01 1.668e-01 0.223 0.823906
pos18 -1.375e-01 8.715e-01 1.869e-01 1.890e-01 -0.727 0.466920
pos19 2.193e-01 1.245e+00 1.906e-01 1.966e-01 1.116 0.264594
pos2 9.314e-02 1.098e+00 1.224e-01 1.155e-01 0.806 0.420024
pos20 -6.294e-03 9.937e-01 2.031e-01 1.961e-01 -0.032 0.974394
pos21 -5.700e-02 9.446e-01 2.111e-01 1.893e-01 -0.301 0.763315
pos22 -3.089e-01 7.343e-01 2.197e-01 2.924e-01 -1.056 0.290768
pos23 -1.127e-01 8.934e-01 2.243e-01 2.233e-01 -0.505 0.613855
pos24 3.717e-02 1.038e+00 2.436e-01 2.425e-01 0.153 0.878191
pos25 -1.168e-02 9.884e-01 2.443e-01 2.267e-01 -0.052 0.958892
pos26 -3.724e-02 9.634e-01 2.368e-01 2.838e-01 -0.131 0.895607
pos27 3.215e-03 1.003e+00 2.554e-01 3.094e-01 0.010 0.991709
pos28 -5.776e-02 9.439e-01 2.508e-01 3.091e-01 -0.187 0.851766
pos29 -5.838e-02 9.433e-01 2.654e-01 2.711e-01 -0.215 0.829518
pos3 1.204e-01 1.128e+00 1.218e-01 1.136e-01 1.059 0.289438
pos30 -2.164e-01 8.054e-01 2.908e-01 3.303e-01 -0.655 0.512462
pos31 -1.756e-02 9.826e-01 3.040e-01 3.255e-01 -0.054 0.956990
pos32 -4.603e-01 6.311e-01 3.205e-01 2.814e-01 -1.636 0.101911
pos33 -3.535e-01 7.023e-01 3.310e-01 2.715e-01 -1.302 0.192958
pos34 4.818e-01 1.619e+00 3.459e-01 2.760e-01 1.746 0.080875 .
pos35 8.048e-02 1.084e+00 3.670e-01 3.700e-01 0.218 0.827809
pos36 1.035e+00 2.815e+00 4.093e-01 3.864e-01 2.678 0.007402 **
pos37 -1.438e-01 8.660e-01 4.682e-01 5.805e-01 -0.248 0.804322
pos38 -1.161e+00 3.132e-01 7.254e-01 4.690e-01 -2.476 0.013304 *
pos39 -9.507e-01 3.865e-01 7.214e-01 6.853e-01 -1.387 0.165358
pos4 5.110e-02 1.052e+00 1.263e-01 1.175e-01 0.435 0.663758
pos40 5.205e-01 1.683e+00 1.009e+00 6.743e-01 0.772 0.440134
pos41 2.798e-01 1.323e+00 1.038e+00 2.246e-01 1.246 0.212859
pos42 4.384e-01 1.550e+00 1.010e+00 1.320e-01 3.322 0.000895 ***
pos43 -8.881e+00 1.391e-04 2.866e+02 1.013e+00 -8.766 < 2e-16 ***
pos5 4.826e-02 1.049e+00 1.301e-01 1.211e-01 0.398 0.690305
pos6 1.076e-01 1.114e+00 1.346e-01 1.247e-01 0.863 0.388107
pos7 8.903e-02 1.093e+00 1.405e-01 1.316e-01 0.677 0.498645
pos8 2.199e-01 1.246e+00 1.437e-01 1.461e-01 1.505 0.132387
pos9 1.548e-01 1.167e+00 1.497e-01 1.444e-01 1.072 0.283657
production_year2.015 2.169e+00 8.747e+00 1.173e+00 4.491e-01 4.829 1.37e-06 ***
production_year2.016 2.270e+00 9.677e+00 1.122e+00 4.320e-01 5.255 1.48e-07 ***
production_year2.017 2.582e+00 1.322e+01 1.143e+00 4.347e-01 5.940 2.86e-09 ***
production_year2000 9.028e-01 2.466e+00 1.550e+00 5.658e-01 1.596 0.110577
production_year2001 1.910e+00 6.756e+00 1.363e+00 8.974e-01 2.129 0.033267 *
production_year2002 5.756e-01 1.778e+00 1.129e+00 4.499e-01 1.279 0.200793
production_year2003 1.247e+00 3.481e+00 1.151e+00 5.023e-01 2.483 0.013029 *
production_year2004 1.467e+00 4.337e+00 1.145e+00 4.977e-01 2.948 0.003200 **
production_year2005 1.728e+00 5.628e+00 1.147e+00 5.046e-01 3.424 0.000617 ***
production_year2006 1.827e+00 6.216e+00 1.082e+00 3.810e-01 4.795 1.62e-06 ***
production_year2007 2.225e+00 9.250e+00 1.066e+00 3.395e-01 6.553 5.66e-11 ***
production_year2008 2.046e+00 7.740e+00 1.037e+00 2.629e-01 7.783 7.10e-15 ***
[ reached getOption("max.print") -- omitted 11 rows ]
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
exp(coef) exp(-coef) lower .95 upper .95
country? 1.913e+00 5.228e-01 5.090e-01 7.189447
countryAlbania 8.715e-01 1.147e+00 2.996e-01 2.535236
countryAustralia 3.097e-01 3.229e+00 1.033e-01 0.928785
countryBrazil 1.783e+00 5.608e-01 6.221e-01 5.111894
countryBulgaria 1.091e+00 9.168e-01 3.766e-01 3.159628
countryCroatia 6.445e-01 1.552e+00 1.869e-01 2.222715
countryCzech Republic 1.263e+00 7.916e-01 4.038e-01 3.952632
countryDenmark 3.326e-01 3.007e+00 1.150e-01 0.961780
countryEgypt 2.598e+00 3.849e-01 8.289e-01 8.143456
countryFinland 3.426e-01 2.919e+00 1.040e-01 1.128317
countryGermany 6.298e-01 1.588e+00 2.226e-01 1.782049
countryGreece 4.341e-01 2.304e+00 1.524e-01 1.236433
countryHungary 5.918e-01 1.690e+00 2.070e-01 1.692322
countryIceland 4.657e-01 2.147e+00 1.590e-01 1.363723
countryIndia 6.166e-01 1.622e+00 2.153e-01 1.765416
countryItaly 4.519e-01 2.213e+00 1.537e-01 1.328754
countryJapan 1.875e+00 5.333e-01 6.207e-01 5.664970
countryLithuania 2.358e-01 4.242e+00 7.768e-02 0.715474
countryMacedonia 5.811e+00 1.721e-01 2.028e+00 16.653090
countryMalaysia 5.384e-01 1.857e+00 1.827e-01 1.586360
countryNetherlands 1.933e+00 5.174e-01 6.557e-01 5.697717
countryNew Zealand 1.243e+00 8.043e-01 3.313e-01 4.665901
countryNorway 4.126e-01 2.424e+00 1.447e-01 1.176816
countryPoland 5.856e-01 1.708e+00 2.038e-01 1.682302
countryPortugal 4.180e-01 2.392e+00 1.466e-01 1.192081
countryQatar 8.939e-01 1.119e+00 2.972e-01 2.688721
countryRussian Federation 1.471e+00 6.799e-01 4.839e-01 4.470437
countrySchweiz 1.300e+00 7.691e-01 4.526e-01 3.735580
countrySerbia 6.893e-01 1.451e+00 2.182e-01 2.177623
countrySlovakia 1.105e+00 9.048e-01 3.212e-01 3.803010
countrySlovenia 2.603e-01 3.841e+00 8.020e-02 0.845095
countrySouth Africa 1.409e+00 7.099e-01 4.967e-01 3.994384
countrySpain 8.795e-01 1.137e+00 3.070e-01 2.519679
countrySweden 5.688e-01 1.758e+00 1.828e-01 1.770147
countrySwitzerland 5.406e-01 1.850e+00 1.900e-01 1.538054
countryTunisia 2.432e+00 4.112e-01 8.219e-01 7.195974
countryTurkey 7.309e-01 1.368e+00 2.561e-01 2.086281
countryUnited Arab Emirates 3.861e-01 2.590e+00 1.155e-01 1.290441
countryUnited Kingdom 5.174e+00 1.933e-01 1.600e+00 16.733713
version_no?? 8.879e-02 1.126e+01 5.202e-02 0.151551
version_no1 3.033e-02 3.297e+01 1.016e-02 0.090580
version_no10 1.351e-02 7.402e+01 6.626e-03 0.027545
version_no12 2.126e-02 4.705e+01 1.195e-02 0.037790
version_no13 2.310e-02 4.330e+01 1.273e-02 0.041916
version_no14 1.041e-02 9.602e+01 4.369e-03 0.024822
version_no16 2.220e-02 4.504e+01 1.170e-02 0.042122
version_no17 1.662e-01 6.015e+00 7.534e-02 0.366824
version_no18 1.916e-02 5.220e+01 1.035e-02 0.035461
version_no19 2.741e-02 3.648e+01 1.687e-02 0.044559
version_no2 3.279e-02 3.049e+01 1.100e-02 0.097754
version_no20 2.947e-02 3.394e+01 1.302e-02 0.066677
version_no21 3.642e-02 2.746e+01 2.642e-02 0.050214
version_no22 8.350e-02 1.198e+01 4.292e-02 0.162466
version_no23 2.588e-02 3.865e+01 1.516e-02 0.044170
version_no24 1.691e-02 5.915e+01 8.559e-03 0.033396
version_no25 6.271e-03 1.595e+02 2.921e-03 0.013463
version_no26 1.549e-02 6.457e+01 7.352e-03 0.032620
version_no27 1.577e-02 6.342e+01 7.732e-03 0.032159
version_no28 2.594e-02 3.855e+01 1.178e-02 0.057147
version_no29 1.405e-02 7.115e+01 6.511e-03 0.030334
version_no3 2.732e-02 3.661e+01 1.211e-02 0.061589
version_no30 2.003e-02 4.993e+01 8.494e-03 0.047213
version_no31 1.071e-02 9.338e+01 4.825e-03 0.023770
version_no32 1.445e-02 6.918e+01 6.167e-03 0.033878
version_no33 1.115e-02 8.967e+01 4.559e-03 0.027277
version_no4 7.929e-03 1.261e+02 2.650e-03 0.023726
version_no5 1.945e-02 5.142e+01 8.644e-03 0.043758
version_no6 1.932e-02 5.175e+01 8.858e-03 0.042156
version_no7 2.469e-02 4.050e+01 1.171e-02 0.052065
version_no8 2.080e-02 4.809e+01 8.438e-03 0.051253
version_no9 1.606e-02 6.228e+01 5.970e-03 0.043185
version_noAH 3.980e-02 2.512e+01 1.206e-02 0.131338
version_noAI 4.448e-02 2.248e+01 1.439e-02 0.137479
version_noAJ 1.789e-01 5.590e+00 6.359e-02 0.503291
version_noAK 3.133e-02 3.191e+01 1.177e-02 0.083428
version_noAL 2.342e-02 4.271e+01 8.234e-03 0.066587
version_noXX 9.860e-03 1.014e+02 4.162e-03 0.023359
pos? 1.057e+00 9.457e-01 7.880e-01 1.418884
pos1 8.943e-01 1.118e+00 7.115e-01 1.124133
pos10 1.100e+00 9.089e-01 8.413e-01 1.438846
pos11 1.157e+00 8.642e-01 8.347e-01 1.604132
pos12 1.416e+00 7.064e-01 1.007e+00 1.990290
pos13 1.177e+00 8.495e-01 8.447e-01 1.640572
pos14 1.066e+00 9.382e-01 7.519e-01 1.510905
pos15 1.313e+00 7.616e-01 9.435e-01 1.827185
pos16 9.449e-01 1.058e+00 6.638e-01 1.344998
pos17 1.038e+00 9.636e-01 7.484e-01 1.439057
pos18 8.715e-01 1.147e+00 6.018e-01 1.262273
pos19 1.245e+00 8.031e-01 8.471e-01 1.830482
pos2 1.098e+00 9.111e-01 8.752e-01 1.376483
pos20 9.937e-01 1.006e+00 6.766e-01 1.459404
pos21 9.446e-01 1.059e+00 6.518e-01 1.368880
pos22 7.343e-01 1.362e+00 4.140e-01 1.302348
pos23 8.934e-01 1.119e+00 5.768e-01 1.384005
pos24 1.038e+00 9.635e-01 6.452e-01 1.669482
pos25 9.884e-01 1.012e+00 6.339e-01 1.541215
pos26 9.634e-01 1.038e+00 5.524e-01 1.680465
pos27 1.003e+00 9.968e-01 5.470e-01 1.839782
pos28 9.439e-01 1.059e+00 5.150e-01 1.729930
pos29 9.433e-01 1.060e+00 5.545e-01 1.604791
pos3 1.128e+00 8.866e-01 9.027e-01 1.409205
pos30 8.054e-01 1.242e+00 4.215e-01 1.538914
pos31 9.826e-01 1.018e+00 5.192e-01 1.859717
pos32 6.311e-01 1.585e+00 3.635e-01 1.095560
pos33 7.023e-01 1.424e+00 4.125e-01 1.195623
pos34 1.619e+00 6.177e-01 9.426e-01 2.780753
pos35 1.084e+00 9.227e-01 5.248e-01 2.238125
pos36 2.815e+00 3.553e-01 1.320e+00 6.002843
pos37 8.660e-01 1.155e+00 2.776e-01 2.701762
pos38 3.132e-01 3.193e+00 1.249e-01 0.785227
pos39 3.865e-01 2.587e+00 1.009e-01 1.480606
pos4 1.052e+00 9.502e-01 8.359e-01 1.325066
pos40 1.683e+00 5.942e-01 4.488e-01 6.310150
pos41 1.323e+00 7.559e-01 8.518e-01 2.054726
pos42 1.550e+00 6.451e-01 1.197e+00 2.007838
pos43 1.391e-04 7.191e+03 1.909e-05 0.001013
pos5 1.049e+00 9.529e-01 8.277e-01 1.330635
pos6 1.114e+00 8.980e-01 8.722e-01 1.421808
pos7 1.093e+00 9.148e-01 8.446e-01 1.414700
pos8 1.246e+00 8.026e-01 9.356e-01 1.659099
pos9 1.167e+00 8.566e-01 8.797e-01 1.549322
production_year2000 2.466e+00 4.054e-01 8.137e-01 7.476020
production_year2001 6.756e+00 1.480e-01 1.164e+00 39.228781
production_year2002 1.778e+00 5.624e-01 7.362e-01 4.294561
production_year2003 3.481e+00 2.873e-01 1.300e+00 9.315680
production_year2004 4.337e+00 2.306e-01 1.635e+00 11.503426
production_year2005 5.628e+00 1.777e-01 2.093e+00 15.130713
production_year2006 6.216e+00 1.609e-01 2.946e+00 13.118450
production_year2007 9.250e+00 1.081e-01 4.755e+00 17.993458
production_year2008 7.740e+00 1.292e-01 4.623e+00 12.957732
production_year2009 7.252e+00 1.379e-01 4.494e+00 11.703704
production_year2010 8.400e+00 1.191e-01 5.929e+00 11.899261
production_year2011 8.402e+00 1.190e-01 4.450e+00 15.860286
production_year2012 6.220e+00 1.608e-01 3.225e+00 11.997949
production_year2013 7.360e+00 1.359e-01 3.817e+00 14.189605
production_year2014 6.766e+00 1.478e-01 3.391e+00 13.502482
production_year2015 8.034e+00 1.245e-01 3.891e+00 16.588287
production_year2016 1.187e+01 8.424e-02 5.669e+00 24.858430
production_year2017 1.056e+01 9.467e-02 4.892e+00 22.808638
production_year2018 1.624e+01 6.159e-02 6.702e+00 39.339892
Concordance= 0.629 (se = 0.005 )
Likelihood ratio test= 695.7 on 152 df, p=<2e-16
Wald test = 5622 on 152 df, p=<2e-16
Score (logrank) test = 806.3 on 152 df, p=<2e-16, Robust = 715.6 p=<2e-16
(Note: the likelihood ratio and score tests assume independence of
observations within a cluster, the Wald and robust score tests do not).
I had to remove unit_type and position_in_unit from the output as this information would lead to identifying product background.
Best Answer
The coefficients and p-values for
countryare for the differences between each country and some reference country. So the reported coefficients and p-values will depend on what country you (or the software) chose for the reference. If the reference country has a lot of cases and thus a narrow standard error, then it would be easy for a country with a few cases to show a "significant" difference based on just one or a few early failures.All of your p-values are reported that way, as all of your predictors are categorical, with each report for a difference from the category level set as the reference.
You would better examine the combined overall significance of all levels of each predictor. That's conveniently done in the R
rmspackage, whose version of theanova()function for itscph()Cox models will provide Wald tests incorporating all levels of each predictor.You also should consider whether you want to include all of those predictors as fixed effects in your model. The problems that you rightly recognize with small numbers of cases in some levels of categorical predictors can be minimized by using random effects and the "partial pooling" of information that entails. This answer explains the concept pretty clearly. Then you model the distribution of the hazards associated with, say, countries in a way that puts more emphasis on those with more cases.