Prioritylasso variante determining the priority datadriven in an separte step. Similiar to the 1. step
    in tsipf-lasso in the 1. step penalty factors for each modality are fit. According to these penalty factors the
    priortiy order is determined. The smaller (near zero) the penalty factor is, the greater is the importance of the
    associated modality. Ordering the penalty factors implies the priority order of the modalities.

Fraction of all pairs of subjects whose predicted survival times are correctly ordered among all subjects that can actually be ordered. In other words, it is the probability of concordance between the predicted and the observed survival. Corrected by weighting with IPCW as suggested by Uno. Implemented in survAUC::UnoC.

Integrated brier score using Kaplan-Meier estimator for weighting

Only works for methods for which probabilities are provided via pec::predictSurvProb. Currently these are only coxph and randomForestSRC. To set an upper time limit, set argument max.time (defaults to max time in test data). Implemented in pec::pec

Amount of features of feature group 'clin' used for the model

Useful for feature selection. The feature group is specified via extra.arg.
    The names of the features within the group must contain that string. Make sure names of
    features of other groups do not contain this string.

Amount of features of feature group 'cnv' used for the model

Amount of features of feature group 'mirna' used for the model

Amount of features of feature group 'mutation' used for the model

Amount of features of feature group 'rna' used for the model