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
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