library(xtable)
library(ggplot2)
library(reshape2)
load("../Main/mainResults1213")

CV folds, ordered by iAUC

## [1] "CV fold 1"
##                  cIndex auc12. auc18. auc24.  iAUC
## gbFullMAR         0.665  0.719  0.743  0.768 0.722
## gbFullMCAR        0.669  0.709  0.722  0.755 0.713
## gbMCAR            0.655  0.691  0.731  0.757 0.708
## forestMAR         0.669  0.723  0.721  0.721 0.704
## forestMCAR        0.665  0.716  0.719  0.727 0.701
## forestStabMAR     0.654  0.677  0.724  0.740 0.698
## gbMAR             0.645  0.672  0.714  0.756 0.697
## gamMAR            0.646  0.679  0.704  0.741 0.696
## forestStabMCAR    0.652  0.674  0.717  0.733 0.695
## gbStabMCAR        0.640  0.663  0.700  0.752 0.690
## coxMAR            0.647  0.681  0.686  0.703 0.689
## gbStabMAR         0.638  0.665  0.699  0.749 0.688
## gamMCAR           0.638  0.665  0.696  0.733 0.686
## forestMARwR       0.630  0.661  0.693  0.724 0.686
## lassoMAR          0.644  0.670  0.689  0.697 0.681
## lassoMCAR         0.643  0.670  0.688  0.699 0.680
## forestStabMARwR   0.637  0.651  0.668  0.713 0.678
## lassoMARwR        0.638  0.660  0.682  0.688 0.674
## coxMCAR           0.637  0.659  0.676  0.693 0.674
## gbFullMARwR       0.596  0.619  0.696  0.723 0.671
## gamMARwR          0.618  0.631  0.685  0.726 0.668
## coxMARwR          0.628  0.640  0.664  0.678 0.662
## gbStabMARwR       0.618  0.615  0.650  0.728 0.662
## gbMARwR           0.619  0.629  0.663  0.713 0.657
## lassoDebiasMAR    0.619  0.650  0.664  0.668 0.650
## lassoDebiasMCAR   0.617  0.651  0.664  0.647 0.640
## lassoDebiasMARwR  0.611  0.634  0.661  0.652 0.639
## [1] "CV fold 2"
##                  cIndex auc12. auc18. auc24.  iAUC
## forestMAR         0.681  0.728  0.674  0.728 0.717
## gbFullMAR         0.671  0.718  0.687  0.749 0.716
## gbMCAR            0.669  0.716  0.683  0.739 0.715
## forestMCAR        0.676  0.720  0.667  0.705 0.706
## gamMARwR          0.673  0.713  0.673  0.699 0.705
## gbStabMAR         0.656  0.705  0.673  0.711 0.698
## gbStabMCAR        0.653  0.698  0.668  0.719 0.697
## lassoMCAR         0.670  0.744  0.644  0.665 0.694
## gbMAR             0.654  0.695  0.663  0.717 0.694
## gbFullMCAR        0.662  0.702  0.671  0.717 0.692
## gamMCAR           0.666  0.717  0.664  0.682 0.691
## gbStabMARwR       0.648  0.654  0.655  0.747 0.691
## lassoMAR          0.664  0.730  0.648  0.663 0.690
## gamMAR            0.665  0.723  0.646  0.674 0.690
## forestMARwR       0.627  0.644  0.682  0.732 0.684
## forestStabMCAR    0.660  0.730  0.645  0.649 0.680
## lassoDebiasMARwR  0.660  0.722  0.640  0.655 0.680
## lassoDebiasMCAR   0.657  0.730  0.626  0.650 0.680
## lassoDebiasMAR    0.656  0.725  0.629  0.652 0.678
## lassoMARwR        0.661  0.716  0.640  0.651 0.677
## forestStabMAR     0.654  0.719  0.638  0.646 0.675
## coxMCAR           0.652  0.710  0.651  0.635 0.670
## coxMARwR          0.656  0.718  0.634  0.621 0.665
## coxMAR            0.648  0.714  0.627  0.620 0.664
## forestStabMARwR   0.639  0.652  0.641  0.678 0.663
## gbMARwR           0.623  0.614  0.633  0.711 0.659
## gbFullMARwR       0.556  0.594  0.637  0.722 0.639
## [1] "CV fold 3"
##                  cIndex auc12. auc18. auc24.  iAUC
## gamMCAR           0.691  0.789  0.673  0.639 0.710
## gamMAR            0.681  0.772  0.669  0.640 0.703
## gbMCAR            0.681  0.764  0.660  0.644 0.702
## forestMCAR        0.686  0.776  0.656  0.628 0.699
## forestMAR         0.678  0.766  0.648  0.638 0.697
## forestStabMCAR    0.681  0.764  0.652  0.635 0.695
## lassoDebiasMCAR   0.674  0.757  0.657  0.657 0.692
## lassoMCAR         0.673  0.766  0.650  0.638 0.687
## lassoDebiasMAR    0.664  0.735  0.651  0.658 0.686
## gbStabMCAR        0.671  0.751  0.642  0.619 0.686
## lassoMAR          0.668  0.758  0.645  0.638 0.685
## forestStabMAR     0.673  0.763  0.636  0.627 0.685
## coxMCAR           0.671  0.765  0.651  0.632 0.685
## coxMAR            0.664  0.750  0.651  0.636 0.684
## forestMARwR       0.648  0.714  0.630  0.651 0.680
## lassoDebiasMARwR  0.659  0.721  0.650  0.654 0.678
## gbFullMARwR       0.627  0.709  0.617  0.658 0.676
## coxMARwR          0.657  0.729  0.644  0.631 0.674
## gbStabMAR         0.656  0.728  0.634  0.616 0.673
## gbFullMCAR        0.666  0.744  0.621  0.589 0.672
## gbFullMAR         0.653  0.738  0.612  0.598 0.668
## gamMARwR          0.645  0.711  0.618  0.612 0.667
## gbMAR             0.651  0.717  0.624  0.594 0.662
## lassoMARwR        0.650  0.739  0.627  0.610 0.661
## gbMARwR           0.605  0.676  0.611  0.655 0.660
## forestStabMARwR   0.643  0.697  0.611  0.611 0.659
## gbStabMARwR       0.615  0.651  0.593  0.595 0.637
## [1] "CV fold 4"
##                  cIndex auc12. auc18. auc24.  iAUC
## gbStabMCAR        0.669  0.695  0.679  0.668 0.698
## gbMCAR            0.664  0.688  0.668  0.667 0.695
## forestMAR         0.675  0.718  0.698  0.649 0.694
## gbStabMAR         0.660  0.687  0.675  0.652 0.685
## gbFullMAR         0.666  0.688  0.675  0.647 0.682
## gbFullMCAR        0.656  0.672  0.661  0.659 0.680
## gamMCAR           0.662  0.689  0.665  0.649 0.679
## forestStabMARwR   0.664  0.683  0.676  0.645 0.678
## forestMCAR        0.664  0.704  0.678  0.624 0.675
## gbMAR             0.654  0.682  0.654  0.637 0.674
## lassoMCAR         0.659  0.704  0.680  0.642 0.674
## forestStabMCAR    0.650  0.683  0.664  0.642 0.672
## forestStabMAR     0.650  0.680  0.656  0.642 0.670
## coxMCAR           0.656  0.698  0.665  0.641 0.668
## lassoDebiasMCAR   0.650  0.698  0.643  0.635 0.666
## lassoMARwR        0.653  0.699  0.677  0.625 0.664
## lassoMAR          0.649  0.701  0.664  0.625 0.662
## gamMAR            0.651  0.675  0.659  0.616 0.661
## gbStabMARwR       0.654  0.682  0.659  0.611 0.660
## gbMARwR           0.652  0.680  0.676  0.606 0.659
## forestMARwR       0.631  0.651  0.674  0.631 0.657
## coxMAR            0.646  0.686  0.659  0.619 0.653
## gamMARwR          0.650  0.677  0.658  0.597 0.652
## lassoDebiasMARwR  0.644  0.690  0.676  0.599 0.651
## lassoDebiasMAR    0.634  0.689  0.643  0.612 0.650
## coxMARwR          0.648  0.690  0.664  0.597 0.648
## gbFullMARwR       0.563  0.574  0.644  0.626 0.616
## [1] "CV fold 5"
##                  cIndex auc12. auc18. auc24.  iAUC
## forestMAR         0.685  0.719  0.711  0.669 0.706
## gbFullMAR         0.676  0.713  0.700  0.672 0.698
## forestMCAR        0.671  0.704  0.701  0.665 0.696
## gbFullMCAR        0.662  0.686  0.693  0.668 0.689
## forestStabMCAR    0.659  0.686  0.679  0.666 0.681
## forestStabMAR     0.658  0.686  0.674  0.662 0.681
## gbStabMCAR        0.659  0.694  0.678  0.669 0.678
## gbMAR             0.657  0.701  0.688  0.659 0.678
## gamMAR            0.662  0.700  0.671  0.645 0.677
## gbMCAR            0.651  0.684  0.680  0.667 0.675
## coxMAR            0.652  0.666  0.671  0.637 0.671
## gbStabMAR         0.652  0.697  0.663  0.644 0.666
## forestMARwR       0.651  0.683  0.663  0.633 0.664
## gamMCAR           0.644  0.662  0.663  0.632 0.658
## lassoMAR          0.639  0.631  0.659  0.638 0.656
## gbFullMARwR       0.594  0.604  0.651  0.672 0.653
## coxMCAR           0.627  0.616  0.649  0.612 0.642
## lassoMCAR         0.623  0.604  0.642  0.623 0.637
## gbMARwR           0.625  0.666  0.647  0.592 0.634
## coxMARwR          0.622  0.617  0.635  0.585 0.631
## lassoMARwR        0.623  0.618  0.640  0.599 0.630
## forestStabMARwR   0.618  0.638  0.632  0.593 0.628
## gbStabMARwR       0.614  0.655  0.617  0.575 0.616
## gamMARwR          0.603  0.630  0.617  0.562 0.610
## lassoDebiasMAR    0.593  0.567  0.611  0.600 0.605
## lassoDebiasMCAR   0.589  0.556  0.607  0.611 0.602
## lassoDebiasMARwR  0.581  0.555  0.596  0.574 0.588

Average Performance (over CV folds)

Method Imputation cIndex auc12. auc18. auc24. iAUC
cox MAR 0.651 0.699 0.659 0.643 0.672
cox MARwR 0.642 0.679 0.648 0.622 0.656
cox MCAR 0.649 0.689 0.658 0.642 0.668
forest MAR 0.677 0.731 0.691 0.681 0.704
forest MARwR 0.637 0.671 0.669 0.674 0.674
forest MCAR 0.672 0.724 0.684 0.670 0.695
forestStab MAR 0.658 0.705 0.665 0.663 0.682
forestStab MARwR 0.640 0.664 0.645 0.648 0.661
forestStab MCAR 0.660 0.707 0.671 0.665 0.684
gam MAR 0.661 0.710 0.670 0.663 0.685
gam MARwR 0.638 0.672 0.650 0.639 0.661
gam MCAR 0.660 0.704 0.672 0.667 0.685
gbFull MAR 0.666 0.715 0.683 0.687 0.697
gbFull MARwR 0.587 0.620 0.649 0.680 0.651
gbFull MCAR 0.663 0.703 0.674 0.678 0.689
gb MAR 0.652 0.693 0.669 0.673 0.681
gb MARwR 0.625 0.653 0.646 0.655 0.654
gb MCAR 0.664 0.709 0.684 0.695 0.699
gbStab MAR 0.652 0.696 0.669 0.674 0.682
gbStab MARwR 0.630 0.651 0.635 0.651 0.653
gbStab MCAR 0.658 0.700 0.673 0.685 0.690
lassoDebias MAR 0.633 0.673 0.640 0.638 0.654
lassoDebias MARwR 0.631 0.664 0.645 0.627 0.647
lassoDebias MCAR 0.638 0.679 0.640 0.640 0.656
lasso MAR 0.653 0.698 0.661 0.652 0.675
lasso MARwR 0.645 0.686 0.653 0.634 0.661
lasso MCAR 0.653 0.698 0.661 0.653 0.675

Subtables for each criterion

[1] “cIndex”
Imputation cIndex.cox cIndex.forest cIndex.forestStab cIndex.gam cIndex.gbFull cIndex.gb cIndex.gbStab cIndex.lassoDebias cIndex.lasso
MAR 0.651 0.677 0.658 0.661 0.666 0.652 0.652 0.633 0.653
MARwR 0.642 0.637 0.640 0.638 0.587 0.625 0.630 0.631 0.645
MCAR 0.649 0.672 0.660 0.660 0.663 0.664 0.658 0.638 0.653
[1] “auc12.”
Imputation auc12..cox auc12..forest auc12..forestStab auc12..gam auc12..gbFull auc12..gb auc12..gbStab auc12..lassoDebias auc12..lasso
MAR 0.699 0.731 0.705 0.710 0.715 0.693 0.696 0.673 0.698
MARwR 0.679 0.671 0.664 0.672 0.620 0.653 0.651 0.664 0.686
MCAR 0.689 0.724 0.707 0.704 0.703 0.709 0.700 0.679 0.698
[1] “auc18.”
Imputation auc18..cox auc18..forest auc18..forestStab auc18..gam auc18..gbFull auc18..gb auc18..gbStab auc18..lassoDebias auc18..lasso
MAR 0.659 0.691 0.665 0.670 0.683 0.669 0.669 0.640 0.661
MARwR 0.648 0.669 0.645 0.650 0.649 0.646 0.635 0.645 0.653
MCAR 0.658 0.684 0.671 0.672 0.674 0.684 0.673 0.640 0.661
[1] “auc24.”
Imputation auc24..cox auc24..forest auc24..forestStab auc24..gam auc24..gbFull auc24..gb auc24..gbStab auc24..lassoDebias auc24..lasso
MAR 0.643 0.681 0.663 0.663 0.687 0.673 0.674 0.638 0.652
MARwR 0.622 0.674 0.648 0.639 0.680 0.655 0.651 0.627 0.634
MCAR 0.642 0.670 0.665 0.667 0.678 0.695 0.685 0.640 0.653
[1] “iAUC”
Imputation iAUC.cox iAUC.forest iAUC.forestStab iAUC.gam iAUC.gbFull iAUC.gb iAUC.gbStab iAUC.lassoDebias iAUC.lasso
MAR 0.672 0.704 0.682 0.685 0.697 0.681 0.682 0.654 0.675
MARwR 0.656 0.674 0.661 0.661 0.651 0.654 0.653 0.647 0.661
MCAR 0.668 0.695 0.684 0.685 0.689 0.699 0.690 0.656 0.675

Average plot

Plot of the average results (over the CV folds) for each criterion, method and imputation method.

Same plot as above, imputation and method have just switched roles to facilitate comparison between imputation methods.

iAUC for each fold

Plot of iAUC for each fold, method and imputation.

iAUC plot

## levOrd <- names(sort(tapply(ave_df$iAUC, ave_df$Method, mean), decreasing = TRUE))
tmp <- ave_df[ave_df$Imputa == "MCAR", ]
tmp <- subset(tmp, Method != "gb")
ord <- order(tmp[, "iAUC"], decreasing = TRUE)
niceLabels <- c("Cox*", "Forest", "Forest*", "Gam*", "Boosting", 
                "Boosting*", "Debiased lasso", "Lasso")[ord]
levOrd <- tmp[ord, "Method"]
levOrd = levOrd[levOrd != "gb"]
dd2 <- dd
dd2 <- subset(dd2, Method != "gb")
dd2$Method <- factor(dd2$Method, levels = levOrd)
dd2$Imputa <- factor(dd2$Imputa, levels = c("MCAR", "MAR", "MARwR"))         
ave2 <- ave_df[, c(1, 2, 7)]
ave2 <- subset(ave2, Method != "gb")

postscript(file = "iAUC.eps", width = 10, height = 5,
           onefile = FALSE, horizontal = FALSE, paper = "special")
print(ggplot(dd2, aes(x = Method, y = value)) + 
  geom_point(color = "lightblue", size = 2) + 
  geom_point(aes(y = iAUC), data = ave2,
            color = "red", size = 3) + 
  facet_grid( ~ Imputa) + 
  coord_cartesian(ylim=c(.6, 0.8)) +
  ylab("Integrated AUC") + xlab("Method") +
  theme(legend.position = "top") + 
  theme(axis.title.y = element_text(margin = margin(0, 10, 0, 0))) +
  theme(axis.text.x  = element_text(angle = 45, vjust = 1, hjust = 1)) + 
  scale_x_discrete(labels = niceLabels))
dev.off()
## quartz_off_screen 
##                 2