Figure 5:

Average measures obtained by the tested imputation algorithms across the three outcomes (the table is also made available in Supplementary file S1 – sheet “mean_measures_m42”) when MAR missingness is simulated in the amputated datasets. For the RB and MSE measures the highlighted cells mark the models that had less losses according to the paired Wilcoxon rank-sum tests computed over the three outcomes. For the CR measure, all the models, but the (non-augmented) IPW model (where the probability of data being missing was computed by an RF including the outcome variables in the model) had comparable performance. missRanger with no pmm achieves the lowest standard error estimate (indeed the ratio SE measures - column “ratio SE” - is the lowest, as also confirmed by the paired Wilcoxon rank-sign test), IPW models obtain a standard error greater than the one computed on the unweighted dataset.